text:
# Papers for stringologist (2019)

- [ALENEX(2019)](#alenex-2019) [[dblp]](https://dblp.org/db/conf/alenex/alenex2019.html)
- [CIAC(2019)](#ciac-2019) [[dblp]](https://dblp.org/db/conf/ciac/ciac2019.html)
- [CIKM(2019)](#cikm-2019) [[dblp]](https://dblp.org/db/conf/cikm/cikm2019.html)
- [CPM(2019)](#cpm-2019) [[dblp]](https://dblp.org/db/conf/cpm/cpm2019.html)
- [DCC(2019)](#dcc-2019) [[dblp]](https://dblp.org/db/conf/dcc/dcc2019.html)
- [DEXA (2)(2019)](#dexa-(2)-2019) [[dblp]](https://dblp.org/db/conf/dexa/dexa2019-2.html)
- [DLT(2019)](#dlt-2019) [[dblp]](https://dblp.org/db/conf/dlt/dlt2019.html)
- [ECML/PKDD (1)(2019)](#ecml/pkdd-(1)-2019) [[dblp]](https://dblp.org/db/conf/pkdd/pkdd2019-1.html)
- [ESA(2019)](#esa-2019) [[dblp]](https://dblp.org/db/conf/esa/esa2019.html)
- [FCT(2019)](#fct-2019) [[dblp]](https://dblp.org/db/conf/fct/fct2019.html)
- [FOCS(2019)](#focs-2019) [[dblp]](https://dblp.org/db/conf/focs/focs2019.html)
- [ICALP(2019)](#icalp-2019) [[dblp]](https://dblp.org/db/conf/icalp/icalp2019.html)
- [INNSBDDL (Tutorials)(2019)](#innsbddl-(tutorials)-2019) [[dblp]](https://dblp.org/db/conf/inns/inns2019t.html)
- [ISAAC(2019)](#isaac-2019) [[dblp]](https://dblp.org/db/conf/isaac/isaac2019.html)
- [ITCS(2019)](#itcs-2019) [[dblp]](https://dblp.org/db/conf/innovations/innovations2019.html)
- [IWOCA(2019)](#iwoca-2019) [[dblp]](https://dblp.org/db/conf/iwoca/iwoca2019.html)
- [LATA(2019)](#lata-2019) [[dblp]](https://dblp.org/db/conf/lata/lata2019.html)
- [MFCS(2019)](#mfcs-2019) [[dblp]](https://dblp.org/db/conf/mfcs/mfcs2019.html)
- [RECOMB(2019)](#recomb-2019) [[dblp]](https://dblp.org/db/conf/recomb/recomb2019.html)
- [SEA²(2019)](#sea²-2019) [[dblp]](https://dblp.org/db/conf/sea2/sea2019.html)
- [SODA(2019)](#soda-2019) [[dblp]](https://dblp.org/db/conf/soda/soda2019.html)
- [SOFSEM(2019)](#sofsem-2019) [[dblp]](https://dblp.org/db/conf/sofsem/sofsem2019.html)
- [SPIRE(2019)](#spire-2019) [[dblp]](https://dblp.org/db/conf/spire/spire2019.html)
- [STACS(2019)](#stacs-2019) [[dblp]](https://dblp.org/db/conf/stacs/stacs2019.html)
- [STOC(2019)](#stoc-2019) [[dblp]](https://dblp.org/db/conf/stoc/stoc2019.html)
- [Stringology(2019)](#stringology-2019) [[dblp]](https://dblp.org/db/conf/stringology/stringology2019.html)
- [WABI(2019)](#wabi-2019) [[dblp]](https://dblp.org/db/conf/wabi/wabi2019.html)
- [WADS(2019)](#wads-2019) [[dblp]](https://dblp.org/db/conf/wads/wads2019.html)
- [WALCOM(2019)](#walcom-2019) [[dblp]](https://dblp.org/db/conf/walcom/walcom2019.html)
- [WORDS(2019)](#words-2019) [[dblp]](https://dblp.org/db/conf/cwords/words2019.html)

- [ACM J. Exp. Algorithmics(2019)](#acm-j-exp-algorithmics-2019) [[dblp]](https://dblp.org/db/journals/jea/jea24.html)
- [ACM Trans. Algorithms(2019)](#acm-trans-algorithms-2019) [[dblp]](https://dblp.org/db/journals/talg/talg15.html)
- [ACM Trans. Inf. Syst.(2019)](#acm-trans-inf-syst-2019) [[dblp]](https://dblp.org/db/journals/tois/tois37.html)
- [Algorithmica(2019)](#algorithmica-2019) [[dblp]](https://dblp.org/db/journals/algorithmica/algorithmica81.html)
- [Algorithms(2019)](#algorithms-2019) [[dblp]](https://dblp.org/db/journals/algorithms/algorithms12.html)
- [Algorithms Mol. Biol.(2019)](#algorithms-mol-biol-2019) [[dblp]](https://dblp.org/db/journals/almob/almob14.html)
- [Bioinform.(2019)](#bioinform-2019) [[dblp]](https://dblp.org/db/journals/bioinformatics/bioinformatics35.html)
- [CoRR(2019)](#corr-2019) [[dblp]](https://dblp.org/db/journals/corr/corr1904.html)
- [Comput. J.(2019)](#comput-j-2019) [[dblp]](https://dblp.org/db/journals/cj/cj62.html)
- [Dagstuhl Reports(2019)](#dagstuhl-reports-2019) [[dblp]](https://dblp.org/db/journals/dagstuhl-reports/dagstuhl-reports9.html)
- [IEEE Trans. Inf. Theory(2019)](#ieee-trans-inf-theory-2019) [[dblp]](https://dblp.org/db/journals/tit/tit65.html)
- [Inf. Comput.(2019)](#inf-comput-2019) [[dblp]](https://dblp.org/db/journals/iandc/iandc266.html)
- [Inf. Process. Lett.(2019)](#inf-process-lett-2019) [[dblp]](https://dblp.org/db/journals/ipl/ipl146.html)
- [Inf. Sci.(2019)](#inf-sci-2019) [[dblp]](https://dblp.org/db/journals/isci/isci483.html)
- [Inf. Syst.(2019)](#inf-syst-2019) [[dblp]](https://dblp.org/db/journals/is/is83.html)
- [J. Comb. Optim.(2019)](#j-comb-optim-2019) [[dblp]](https://dblp.org/db/journals/jco/jco37.html)
- [J. Comput. Syst. Sci.(2019)](#j-comput-syst-sci-2019) [[dblp]](https://dblp.org/db/journals/jcss/jcss101.html)
- [Rev. Socionetwork Strateg.(2019)](#rev-socionetwork-strateg-2019) [[dblp]](https://dblp.org/db/journals/rss/rss13.html)
- [SIAM J. Comput.(2019)](#siam-j-comput-2019) [[dblp]](https://dblp.org/db/journals/siamcomp/siamcomp48.html)
- [SIAM J. Discret. Math.(2019)](#siam-j-discret-math-2019) [[dblp]](https://dblp.org/db/journals/siamdm/siamdm33.html)
- [Softw. Pract. Exp.(2019)](#softw-pract-exp-2019) [[dblp]](https://dblp.org/db/journals/spe/spe49.html)
- [Theor. Comput. Sci.(2019)](#theor-comput-sci-2019) [[dblp]](https://dblp.org/db/journals/tcs/tcs753.html)
- [Theory Comput. Syst.(2019)](#theory-comput-syst-2019) [[dblp]](https://dblp.org/db/journals/mst/mst63.html)

## Contents
#### [ALENEX 2019](https://dblp.org/db/conf/alenex/alenex2019.html)
  1. [Lightweight Distributed Suffix Array Construction.](https://doi.org/10.1137/1.9781611975499.3)

#### [CIAC 2019](https://dblp.org/db/conf/ciac/ciac2019.html)
  1. [The Parameterized Position Heap of a Trie.](https://doi.org/10.1007/978-3-030-17402-6_20)

#### [CIKM 2019](https://dblp.org/db/conf/cikm/cikm2019.html)
  1. [Improved Compressed String Dictionaries.](https://doi.org/10.1145/3357384.3357972)

#### [CPM 2019](https://dblp.org/db/conf/cpm/cpm2019.html)
  1. [A 2-Approximation Algorithm for the Complementary Maximal Strip Recovery Problem.](https://doi.org/10.4230/LIPIcs.CPM.2019.5)
  2. [A New Class of Searchable and Provably Highly Compressible String Transformations.](https://doi.org/10.4230/LIPIcs.CPM.2019.12)
  3. [A Rearrangement Distance for Fully-Labelled Trees.](https://doi.org/10.4230/LIPIcs.CPM.2019.28)
  4. [Approximating Approximate Pattern Matching.](https://doi.org/10.4230/LIPIcs.CPM.2019.15)
  5. [Cartesian Tree Matching and Indexing.](https://doi.org/10.4230/LIPIcs.CPM.2019.16)
  6. [Compressed Multiple Pattern Matching.](https://doi.org/10.4230/LIPIcs.CPM.2019.13)
  7. [Computing Runs on a Trie.](https://doi.org/10.4230/LIPIcs.CPM.2019.23)
  8. [Computing the Antiperiod(s) of a String.](https://doi.org/10.4230/LIPIcs.CPM.2019.32)
  9. [Conversion from RLBWT to LZ77.](https://doi.org/10.4230/LIPIcs.CPM.2019.9)
  10. [Dichotomic Selection on Words: A Probabilistic Analysis.](https://doi.org/10.4230/LIPIcs.CPM.2019.19)
  11. [Entropy Lower Bounds for Dictionary Compression.](https://doi.org/10.4230/LIPIcs.CPM.2019.11)
  12. [Faster Queries for Longest Substring Palindrome After Block Edit.](https://doi.org/10.4230/LIPIcs.CPM.2019.27)
  13. [Finding a Small Number of Colourful Components.](https://doi.org/10.4230/LIPIcs.CPM.2019.20)
  14. [Front Matter, Table of Contents, Preface, Conference Organization.](https://doi.org/10.4230/LIPIcs.CPM.2019.0)
  15. [Fully-Functional Bidirectional Burrows-Wheeler Indexes and Infinite-Order De Bruijn Graphs.](https://doi.org/10.4230/LIPIcs.CPM.2019.10)
  16. [Hamming Distance Completeness.](https://doi.org/10.4230/LIPIcs.CPM.2019.14)
  17. [How to Exploit Periodicity (Invited Talk).](https://doi.org/10.4230/LIPIcs.CPM.2019.1)
  18. [Indexing the Bijective BWT.](https://doi.org/10.4230/LIPIcs.CPM.2019.17)
  19. [Linking BWT and XBW via Aho-Corasick Automaton: Applications to Run-Length Encoding.](https://doi.org/10.4230/LIPIcs.CPM.2019.24)
  20. [On Maximal Repeats in Compressed Strings.](https://doi.org/10.4230/LIPIcs.CPM.2019.18)
  21. [On the Size of Overlapping Lempel-Ziv and Lyndon Factorizations.](https://doi.org/10.4230/LIPIcs.CPM.2019.29)
  22. [Online Algorithms for Constructing Linear-Size Suffix Trie.](https://doi.org/10.4230/LIPIcs.CPM.2019.30)
  23. [Optimal Rank and Select Queries on Dictionary-Compressed Text.](https://doi.org/10.4230/LIPIcs.CPM.2019.4)
  24. [Quasi-Linear-Time Algorithm for Longest Common Circular Factor.](https://doi.org/10.4230/LIPIcs.CPM.2019.25)
  25. [Quasi-Periodicity in Streams.](https://doi.org/10.4230/LIPIcs.CPM.2019.22)
  26. [Safe and Complete Algorithms for Dynamic Programming Problems, with an Application to RNA Folding.](https://doi.org/10.4230/LIPIcs.CPM.2019.8)
  27. [Searching Long Repeats in Streams.](https://doi.org/10.4230/LIPIcs.CPM.2019.31)
  28. [Simulating the DNA Overlap Graph in Succinct Space.](https://doi.org/10.4230/LIPIcs.CPM.2019.26)
  29. [Some Variations on Lyndon Words (Invited Talk).](https://doi.org/10.4230/LIPIcs.CPM.2019.2)
  30. [Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform.](https://doi.org/10.4230/LIPIcs.CPM.2019.7)
  31. [Streaming Dictionary Matching with Mismatches.](https://doi.org/10.4230/LIPIcs.CPM.2019.21)
  32. [Stringology Combats Microbiological Threats (Invited Talk).](https://doi.org/10.4230/LIPIcs.CPM.2019.3)
  33. [Sufficient Conditions for Efficient Indexing Under Different Matchings.](https://doi.org/10.4230/LIPIcs.CPM.2019.6)

#### [DCC 2019](https://dblp.org/db/conf/dcc/dcc2019.html)
  1. [A Compact Representation of Raster Time Series.](https://doi.org/10.1109/DCC.2019.00018)
  2. [A New Technique for Lossless Compression of Color Images Based on Hierarchical Prediction, Inversion and Context Adaptive Coding.](https://doi.org/10.1109/DCC.2019.00096)
  3. [BWT Tunnel Planning is Hard But Manageable.](https://doi.org/10.1109/DCC.2019.00022)
  4. [Better Than Optimal Huffman Coding?](https://doi.org/10.1109/DCC.2019.00094)
  5. [Constructing Antidictionaries in Output-Sensitive Space.](https://doi.org/10.1109/DCC.2019.00062)
  6. [Dv2v: A Dynamic Variable-to-Variable Compressor.](https://doi.org/10.1109/DCC.2019.00016)
  7. [Generalized Word Equations: A New Approach to Data Compresion.](https://doi.org/10.1109/DCC.2019.00097)
  8. [LZRR: LZ77 Parsing with Right Reference.](https://doi.org/10.1109/DCC.2019.00029)
  9. [Light Field Image Compression with Random Access.](https://doi.org/10.1109/DCC.2019.00065)
  10. [MR-RePair: Grammar Compression Based on Maximal Repeats.](https://doi.org/10.1109/DCC.2019.00059)
  11. [Multidimensional Compression with Pattern Matching.](https://doi.org/10.1109/DCC.2019.00079)
  12. [Numerical Pattern Mining Through Compression.](https://doi.org/10.1109/DCC.2019.00019)
  13. [On Lempel-Ziv Decompression in Small Space.](https://doi.org/10.1109/DCC.2019.00030)
  14. [On the Randomness of Compressed Data.](https://doi.org/10.1109/DCC.2019.00093)
  15. [Parameterized Text Indexing with One Wildcard.](https://doi.org/10.1109/DCC.2019.00023)
  16. [Practical Indexing of Repetitive Collections Using Relative Lempel-Ziv.](https://doi.org/10.1109/DCC.2019.00028)
  17. [RePair in Compressed Space and Time.](https://doi.org/10.1109/DCC.2019.00060)
  18. [Regular Expression Search on Compressed Text.](https://doi.org/10.1109/DCC.2019.00061)
  19. [Selective Dynamic Compression.](https://doi.org/10.1109/DCC.2019.00095)
  20. [Space-Efficient Computation of the Burrows-Wheeler Transform.](https://doi.org/10.1109/DCC.2019.00021)
  21. [Tunneling on Wheeler Graphs.](https://doi.org/10.1109/DCC.2019.00020)
  22. [Vectorizing Fast Compression.](https://doi.org/10.1109/DCC.2019.00110)

#### [DEXA (2) 2019](https://dblp.org/db/conf/dexa/dexa2019-2.html)
  1. [Succinct BWT-Based Sequence Prediction.](https://doi.org/10.1007/978-3-030-27618-8_7)

#### [DLT 2019](https://dblp.org/db/conf/dlt/dlt2019.html)
  1. [Computing the k-binomial Complexity of the Thue-Morse Word.](https://doi.org/10.1007/978-3-030-24886-4_21)
  2. [First Lower Bounds for Palindromic Length.](https://doi.org/10.1007/978-3-030-24886-4_17)
  3. [On Palindromic Length of Sturmian Sequences.](https://doi.org/10.1007/978-3-030-24886-4_18)
  4. [On the Length of Shortest Strings Accepted by Two-Way Finite Automata.](https://doi.org/10.1007/978-3-030-24886-4_6)
  5. [Separating Many Words by Counting Occurrences of Factors.](https://doi.org/10.1007/978-3-030-24886-4_19)
  6. [The Relative Edit-Distance Between Two Input-Driven Languages.](https://doi.org/10.1007/978-3-030-24886-4_9)
  7. [k-Spectra of Weakly-c-Balanced Words.](https://doi.org/10.1007/978-3-030-24886-4_20)

#### [ECML/PKDD (1) 2019](https://dblp.org/db/conf/pkdd/pkdd2019-1.html)
  1. [String Sanitization: A Combinatorial Approach.](https://doi.org/10.1007/978-3-030-46150-8_37)

#### [ESA 2019](https://dblp.org/db/conf/esa/esa2019.html)
  1. [Bidirectional Text Compression in External Memory.](https://doi.org/10.4230/LIPIcs.ESA.2019.41)
  2. [Longest Common Substring Made Fully Dynamic.](https://doi.org/10.4230/LIPIcs.ESA.2019.6)
  3. [On the Hardness and Inapproximability of Recognizing Wheeler Graphs.](https://doi.org/10.4230/LIPIcs.ESA.2019.51)
  4. [Repetition Detection in a Dynamic String.](https://doi.org/10.4230/LIPIcs.ESA.2019.5)

#### [FCT 2019](https://dblp.org/db/conf/fct/fct2019.html)
  1. [Circular Pattern Matching with k Mismatches.](https://doi.org/10.1007/978-3-030-25027-0_15)

#### [FOCS 2019](https://dblp.org/db/conf/focs/focs2019.html)
  1. [Approximation Algorithms for LCS and LIS with Truly Improved Running Times.](https://doi.org/10.1109/FOCS.2019.00071)
  2. [Balancing Straight-Line Programs.](https://doi.org/10.1109/FOCS.2019.00073)
  3. [Optimal Document Exchange and New Codes for Insertions and Deletions.](https://doi.org/10.1109/FOCS.2019.00029)
  4. [Sublinear Algorithms for Gap Edit Distance.](https://doi.org/10.1109/FOCS.2019.00070)
  5. [Why are Proof Complexity Lower Bounds Hard?](https://doi.org/10.1109/FOCS.2019.00080)

#### [ICALP 2019](https://dblp.org/db/conf/icalp/icalp2019.html)
  1. [Dynamic Ordered Sets with Approximate Queries, Approximate Heaps and Soft Heaps.](https://doi.org/10.4230/LIPIcs.ICALP.2019.95)
  2. [Even Faster Elastic-Degenerate String Matching via Fast Matrix Multiplication.](https://doi.org/10.4230/LIPIcs.ICALP.2019.21)

#### [INNSBDDL (Tutorials) 2019](https://dblp.org/db/conf/inns/inns2019t.html)
  1. [Learned Data Structures.](https://doi.org/10.1007/978-3-030-43883-8_2)

#### [ISAAC 2019](https://dblp.org/db/conf/isaac/isaac2019.html)
  1. [An Improved Data Structure for Left-Right Maximal Generic Words Problem.](https://doi.org/10.4230/LIPIcs.ISAAC.2019.40)
  2. [Internal Dictionary Matching.](https://doi.org/10.4230/LIPIcs.ISAAC.2019.22)
  3. [On Approximate Range Mode and Range Selection.](https://doi.org/10.4230/LIPIcs.ISAAC.2019.57)
  4. [Top Tree Compression of Tries.](https://doi.org/10.4230/LIPIcs.ISAAC.2019.4)

#### [ITCS 2019](https://dblp.org/db/conf/innovations/innovations2019.html)
  1. [Testing Local Properties of Arrays.](https://doi.org/10.4230/LIPIcs.ITCS.2019.11)

#### [IWOCA 2019](https://dblp.org/db/conf/iwoca/iwoca2019.html)
  1. [Burrows-Wheeler Transform of Words Defined by Morphisms.](https://doi.org/10.1007/978-3-030-25005-8_32)
  2. [Finding Periods in Cartesian Tree Matching.](https://doi.org/10.1007/978-3-030-25005-8_7)
  3. [Shortest Unique Palindromic Substring Queries on Run-Length Encoded Strings.](https://doi.org/10.1007/978-3-030-25005-8_35)

#### [LATA 2019](https://dblp.org/db/conf/lata/lata2019.html)
  1. [Automata over Infinite Sequences of Reals.](https://doi.org/10.1007/978-3-030-13435-8_9)
  2. [Efficient Representation and Counting of Antipower Factors in Words.](https://doi.org/10.1007/978-3-030-13435-8_31)
  3. [Generalized Register Context-Free Grammars.](https://doi.org/10.1007/978-3-030-13435-8_19)
  4. [On the Maximum Number of Distinct Palindromic Sub-arrays.](https://doi.org/10.1007/978-3-030-13435-8_32)
  5. [Palindromic Subsequences in Finite Words.](https://doi.org/10.1007/978-3-030-13435-8_34)
  6. [Recurrence in Multidimensional Words.](https://doi.org/10.1007/978-3-030-13435-8_29)
  7. [Regular Matching and Inclusion on Compressed Tree Patterns with Context Variables.](https://doi.org/10.1007/978-3-030-13435-8_25)

#### [MFCS 2019](https://dblp.org/db/conf/mfcs/mfcs2019.html)
  1. [A Constant-Time Colored Choice Dictionary with Almost Robust Iteration.](https://doi.org/10.4230/LIPIcs.MFCS.2019.64)
  2. [From Regular Expression Matching to Parsing.](https://doi.org/10.4230/LIPIcs.MFCS.2019.71)
  3. [Indexing Graph Search Trees and Applications.](https://doi.org/10.4230/LIPIcs.MFCS.2019.67)
  4. [RLE Edit Distance in Near Optimal Time.](https://doi.org/10.4230/LIPIcs.MFCS.2019.66)
  5. [The Power Word Problem.](https://doi.org/10.4230/LIPIcs.MFCS.2019.43)
  6. [Uniform Random Expressions Lack Expressivity.](https://doi.org/10.4230/LIPIcs.MFCS.2019.51)
  7. [Upper Bounds on the Length of Minimal Solutions to Certain Quadratic Word Equations.](https://doi.org/10.4230/LIPIcs.MFCS.2019.44)

#### [RECOMB 2019](https://dblp.org/db/conf/recomb/recomb2019.html)
  1. [Efficient Construction of a Complete Index for Pan-Genomics Read Alignment.](https://doi.org/10.1007/978-3-030-17083-7_10)

#### [SEA² 2019](https://dblp.org/db/conf/sea2/sea2019.html)
  1. [Searching for Best Karatsuba Recurrences.](https://doi.org/10.1007/978-3-030-34029-2_22)

#### [SODA 2019](https://dblp.org/db/conf/soda/soda2019.html)
  1. [Efficiently Approximating Edit Distance Between Pseudorandom Strings.](https://doi.org/10.1137/1.9781611975482.71)
  2. [Few Matches or Almost Periodicity: Faster Pattern Matching with Mismatches in Compressed Texts.](https://doi.org/10.1137/1.9781611975482.69)
  3. [List Decoding with Double Samplers.](https://doi.org/10.1137/1.9781611975482.129)
  4. [Lower Bounds for Oblivious Data Structures.](https://doi.org/10.1137/1.9781611975482.149)
  5. [Lower bounds for text indexing with mismatches and differences.](https://doi.org/10.1137/1.9781611975482.70)
  6. [Optimal Construction of Compressed Indexes for Highly Repetitive Texts.](https://doi.org/10.1137/1.9781611975482.82)
  7. [Synchronization Strings: Highly Efficient Deterministic Constructions over Small Alphabets.](https://doi.org/10.1137/1.9781611975482.132)
  8. [The streaming k-mismatch problem.](https://doi.org/10.1137/1.9781611975482.68)

#### [SOFSEM 2019](https://dblp.org/db/conf/sofsem/sofsem2019.html)
  1. [On Infinite Prefix Normal Words.](https://doi.org/10.1007/978-3-030-10801-4_11)

#### [SPIRE 2019](https://dblp.org/db/conf/spire/spire2019.html)
  1. [A New Linear-Time Algorithm for Centroid Decomposition.](https://doi.org/10.1007/978-3-030-32686-9_20)
  2. [A Practical Alphabet-Partitioning Rank/Select Data Structure.](https://doi.org/10.1007/978-3-030-32686-9_32)
  3. [Adaptive Succinctness.](https://doi.org/10.1007/978-3-030-32686-9_33)
  4. [An Index for Sequencing Reads Based on the Colored de Bruijn Graph.](https://doi.org/10.1007/978-3-030-32686-9_22)
  5. [An Optimal Algorithm to Find Champions of Tournament Graphs.](https://doi.org/10.1007/978-3-030-32686-9_19)
  6. [Approximation Ratios of RePair, LongestMatch and Greedy on Unary Strings.](https://doi.org/10.1007/978-3-030-32686-9_1)
  7. [BM25 Beyond Query-Document Similarity.](https://doi.org/10.1007/978-3-030-32686-9_5)
  8. [Bounds and Estimates on the Average Edit Distance.](https://doi.org/10.1007/978-3-030-32686-9_7)
  9. [COBS: A Compact Bit-Sliced Signature Index.](https://doi.org/10.1007/978-3-030-32686-9_21)
  10. [Compact Data Structures for Shortest Unique Substring Queries.](https://doi.org/10.1007/978-3-030-32686-9_8)
  11. [Direct Linear Time Construction of Parameterized Suffix and LCP Arrays for Constant Alphabets.](https://doi.org/10.1007/978-3-030-32686-9_27)
  12. [Fast Cartesian Tree Matching.](https://doi.org/10.1007/978-3-030-32686-9_9)
  13. [Fast Identification of Heavy Hitters by Cached and Packed Group Testing.](https://doi.org/10.1007/978-3-030-32686-9_17)
  14. [Fast, Small, and Simple Document Listing on Repetitive Text Collections.](https://doi.org/10.1007/978-3-030-32686-9_34)
  15. [Faster Dynamic Compressed d-ary Relations.](https://doi.org/10.1007/978-3-030-32686-9_30)
  16. [Faster Repetition-Aware Compressed Suffix Trees Based on Block Trees.](https://doi.org/10.1007/978-3-030-32686-9_31)
  17. [Implementing the Topological Model Succinctly.](https://doi.org/10.1007/978-3-030-32686-9_35)
  18. [Inducing the Lyndon Array.](https://doi.org/10.1007/978-3-030-32686-9_10)
  19. [Linear Time Maximum Segmentation Problems in Column Stream Model.](https://doi.org/10.1007/978-3-030-32686-9_23)
  20. [Lossless Image Compression Using List Update Algorithms.](https://doi.org/10.1007/978-3-030-32686-9_2)
  21. [Minimal Absent Words in Rooted and Unrooted Trees.](https://doi.org/10.1007/978-3-030-32686-9_11)
  22. [Network-Based Pooling for Topic Modeling on Microblog Content.](https://doi.org/10.1007/978-3-030-32686-9_6)
  23. [On Longest Common Property Preserved Substring Queries.](https://doi.org/10.1007/978-3-030-32686-9_12)
  24. [On the Computation of Longest Previous Non-overlapping Factors.](https://doi.org/10.1007/978-3-030-32686-9_26)
  25. [Online Algorithms on Antipowers and Antiperiods.](https://doi.org/10.1007/978-3-030-32686-9_13)
  26. [Parallel External Memory Wavelet Tree and Wavelet Matrix Construction.](https://doi.org/10.1007/978-3-030-32686-9_28)
  27. [Polynomial-Delay Enumeration of Maximal Common Subsequences.](https://doi.org/10.1007/978-3-030-32686-9_14)
  28. [Position Bias Estimation for Unbiased Learning-to-Rank in eCommerce Search.](https://doi.org/10.1007/978-3-030-32686-9_4)
  29. [Range Shortest Unique Substring Queries.](https://doi.org/10.1007/978-3-030-32686-9_18)
  30. [Rpair: Rescaling RePair with Rsync.](https://doi.org/10.1007/978-3-030-32686-9_3)
  31. [Run-Length Encoding in a Finite Universe.](https://doi.org/10.1007/978-3-030-32686-9_25)
  32. [SACABench: Benchmarking Suffix Array Construction.](https://doi.org/10.1007/978-3-030-32686-9_29)
  33. [Searching Runs in Streams.](https://doi.org/10.1007/978-3-030-32686-9_15)
  34. [Space- and Time-Efficient Storage of LiDAR Point Clouds.](https://doi.org/10.1007/978-3-030-32686-9_36)
  35. [Space-Efficient Merging of Succinct de Bruijn Graphs.](https://doi.org/10.1007/978-3-030-32686-9_24)
  36. [Weighted Shortest Common Supersequence Problem Revisited.](https://doi.org/10.1007/978-3-030-32686-9_16)

#### [STACS 2019](https://dblp.org/db/conf/stacs/stacs2019.html)
  1. [Constant-Time Retrieval with O(log m) Extra Bits.](https://doi.org/10.4230/LIPIcs.STACS.2019.24)
  2. [Depth First Search in the Semi-streaming Model.](https://doi.org/10.4230/LIPIcs.STACS.2019.42)
  3. [Fast and Longest Rollercoasters.](https://doi.org/10.4230/LIPIcs.STACS.2019.30)

#### [STOC 2019](https://dblp.org/db/conf/stoc/stoc2019.html)
  1. [Local decodability of the Burrows-Wheeler transform.](https://doi.org/10.1145/3313276.3316317)
  2. [Optimal succinct rank data structure via approximate nonnegative tensor decomposition.](https://doi.org/10.1145/3313276.3316352)
  3. [String synchronizing sets: sublinear-time BWT construction and optimal LCE data structure.](https://doi.org/10.1145/3313276.3316368)

#### [Stringology 2019](https://dblp.org/db/conf/stringology/stringology2019.html)
  1. [
      k-Abelian Pattern Matching: Revisited, Corrected, and Extended.](http://www.stringology.org/event/2019/p04.html)
  2. [A Fast SIMD-Based Chunking Algorithm.](http://www.stringology.org/event/2019/p08.html)
  3. [Algorithms to Compute the Lyndon Array Revisited.](http://www.stringology.org/event/2019/p03.html)
  4. [An Improvement of the Franek-Jennings-Smyth Pattern Matching Algorithm.](http://www.stringology.org/event/2019/p06.html)
  5. [Bidirectional Adaptive Compression.](http://www.stringology.org/event/2019/p09.html)
  6. [Computing Maximal Palindromes and Distinct Palindromes in a Trie.](http://www.stringology.org/event/2019/p02.html)
  7. [Lexicalized Syntactic Analysis by Restarting Automata.](http://www.stringology.org/event/2019/p07.html)
  8. [Online Parameterized Dictionary Matching with One Gap.](http://www.stringology.org/event/2019/p05.html)
  9. [Optimal Time and Space Construction of Suffix Arrays and LCP Arrays for Integer Alphabets.](http://www.stringology.org/event/2019/p11.html)
  10. [Pattern Matching on Weighted Strings.](http://www.stringology.org/event/2019/p01.html)
  11. [Selective Dynamic Compression.](http://www.stringology.org/event/2019/p10.html)
  12. [Translating Between Wavelet Tree and Wavelet Matrix Construction.](http://www.stringology.org/event/2019/p12.html)

#### [WABI 2019](https://dblp.org/db/conf/wabi/wabi2019.html)
  1. [Finding All Maximal Perfect Haplotype Blocks in Linear Time.](https://doi.org/10.4230/LIPIcs.WABI.2019.8)

#### [WADS 2019](https://dblp.org/db/conf/wads/wads2019.html)
  1. [Dynamic Dictionary Matching in the Online Model.](https://doi.org/10.1007/978-3-030-24766-9_30)
  2. [Orthogonal Range Reporting and Rectangle Stabbing for Fat Rectangles.](https://doi.org/10.1007/978-3-030-24766-9_21)

#### [WALCOM 2019](https://dblp.org/db/conf/walcom/walcom2019.html)
  1. [Applications of V-Order: Suffix Arrays, the Burrows-Wheeler Transform & the FM-index.](https://doi.org/10.1007/978-3-030-10564-8_26)

#### [WORDS 2019](https://dblp.org/db/conf/cwords/words2019.html)
  1. [Generalized Lyndon Factorizations of Infinite Words.](https://doi.org/10.1007/978-3-030-28796-2_8)
  2. [Matching Patterns with Variables.](https://doi.org/10.1007/978-3-030-28796-2_1)
  3. [Repetitions in Infinite Palindrome-Rich Words.](https://doi.org/10.1007/978-3-030-28796-2_7)

#### ACM J. Exp. Algorithmics 2019
  1. [Better External Memory LCP Array Construction.](https://doi.org/10.1145/3297723)

#### ACM Trans. Algorithms 2019
  1. [Sparse Dynamic Programming on DAGs with Small Width.](https://doi.org/10.1145/3301312)

#### ACM Trans. Inf. Syst. 2019
  1. [Brotli: A General-Purpose Data Compressor.](https://doi.org/10.1145/3231935)

#### Algorithmica 2019
  1. [Can We Recover the Cover?](https://doi.org/10.1007/s00453-019-00559-8)
  2. [Correction to: Longest Common Substring with Approximately k Mismatches.](https://doi.org/10.1007/s00453-019-00560-1)
  3. [Fixed Block Compression Boosting in FM-Indexes: Theory and Practice.](https://doi.org/10.1007/s00453-018-0475-9)
  4. [Longest Common Substring with Approximately k Mismatches.](https://doi.org/10.1007/s00453-019-00548-x)
  5. [Mind the Gap! - Online Dictionary Matching with One Gap.](https://doi.org/10.1007/s00453-018-0526-2)
  6. [Tight Tradeoffs for Real-Time Approximation of Longest Palindromes in Streams.](https://doi.org/10.1007/s00453-019-00591-8)

#### Algorithms 2019
  1. [Compaction of Church Numerals.](https://doi.org/10.3390/a12080159)
  2. [Space-Efficient Fully Dynamic DFS in Undirected Graphs.](https://doi.org/10.3390/a12030052)

#### Algorithms Mol. Biol. 2019
  1. [External memory BWT and LCP computation for sequence collections with applications.](https://doi.org/10.1186/s13015-019-0140-0)
  2. [Linear time minimum segmentation enables scalable founder reconstruction.](https://doi.org/10.1186/s13015-019-0147-6)
  3. [Prefix-free parsing for building big BWTs.](https://doi.org/10.1186/s13015-019-0148-5)
  4. [SNPs detection by eBWT positional clustering.](https://doi.org/10.1186/s13015-019-0137-8)

#### Bioinform. 2019
  1. [A framework for space-efficient variable-order Markov models.](https://doi.org/10.1093/bioinformatics/btz268)
  2. [Compressed filesystem for managing large genome collections.](https://doi.org/10.1093/bioinformatics/btz192)
  3. [Fully-sensitive seed finding in sequence graphs using a hybrid index.](https://doi.org/10.1093/bioinformatics/btz341)

#### CoRR 2019
  1. [3SUM with Preprocessing: Algorithms, Lower Bounds and Cryptographic Applications.](https://arxiv.org/abs/1907.08355)
  2. [A Compact Representation of Raster Time Series.](https://arxiv.org/abs/1901.01944)
  3. [A Detailed Analysis of Quicksort Algorithms with Experimental Mathematics.](https://arxiv.org/abs/1905.00118)
  4. [A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets.](https://arxiv.org/abs/1905.08977)
  5. [A New Class of Searchable and Provably Highly Compressible String Transformations.](https://arxiv.org/abs/1902.01280)
  6. [A New Deterministic Algorithm for Dynamic Set Cover.](https://arxiv.org/abs/1909.11600)
  7. [A New Lower Bound for Semigroup Orthogonal Range Searching.](https://arxiv.org/abs/1903.07967)
  8. [A Simple Reduction for Full-Permuted Pattern Matching Problems on Multi-Track Strings.](https://arxiv.org/abs/1909.02364)
  9. [A Simple Solution to the Level-Ancestor Problem.](https://arxiv.org/abs/1903.01387)
  10. [A fast algorithm for constructing balanced binary search trees.](https://arxiv.org/abs/1902.02499)
  11. [A multidimensional analog to the Burrows-Wheeler transform.](https://arxiv.org/abs/1905.03424)
  12. [A randomized strategy in the mirror game.](https://arxiv.org/abs/1901.07809)
  13. [A study for Image compression using Re-Pair algorithm.](https://arxiv.org/abs/1901.10744)
  14. [A sub-quadratic algorithm for the longest common increasing subsequence problem.](https://arxiv.org/abs/1902.06864)
  15. [ALLSAT compressed with wildcards: Frequent Set Mining.](https://arxiv.org/abs/1910.14508)
  16. [Abelian periods of factors of Sturmian words.](https://arxiv.org/abs/1905.06138)
  17. [Abelian-square factors and binary words.](https://arxiv.org/abs/1907.05369)
  18. [About Fibonacci trees. I.](https://arxiv.org/abs/1904.12135)
  19. [Algorithms to compute the Burrows-Wheeler Similarity Distribution.](https://arxiv.org/abs/1903.10583)
  20. [An Average-Compress Algorithm for the Sample Mean Problem under Dynamic Time Warping.](https://arxiv.org/abs/1909.13541)
  21. [An Efficient Word Lookup System by using Improved Trie Algorithm.](https://arxiv.org/abs/1911.01763)
  22. [An Incompressibility Theorem for Automatic Complexity.](https://arxiv.org/abs/1908.10843)
  23. [An Index for Sequencing Reads Based on The Colored de Bruijn Graph.](https://arxiv.org/abs/1908.02211)
  24. [An efficient sorting algorithm - Ultimate Heapsort(UHS).](https://arxiv.org/abs/1902.00257)
  25. [An in-place, subquadratic algorithm for permutation inversion.](https://arxiv.org/abs/1901.01926)
  26. [Analyzing Trade-offs in Reversible Linear and Binary Search Algorithms.](https://arxiv.org/abs/1910.10406)
  27. [Apply Sorting Algorithms to FAST Problem.](https://arxiv.org/abs/1910.06920)
  28. [Approximate Similarity Search Under Edit Distance Using Locality-Sensitive Hashing.](https://arxiv.org/abs/1907.01600)
  29. [Approximating the Geometric Edit Distance.](https://arxiv.org/abs/1910.00773)
  30. [Balancing Straight-Line Programs.](https://arxiv.org/abs/1902.03568)
  31. [Belga B-trees.](https://arxiv.org/abs/1903.03560)
  32. [Beyond the Inverted Index.](https://arxiv.org/abs/1908.04517)
  33. [Bidirectional Text Compression in External Memory.](https://arxiv.org/abs/1907.03235)
  34. [Bloom filter variants for multiple sets: a comparative assessment.](https://arxiv.org/abs/1908.10644)
  35. [Borders, Palindrome Prefixes, and Square Prefixes.](https://arxiv.org/abs/1906.03689)
  36. [Cache-Friendly Search Trees; or, In Which Everything Beats std: : set.](https://arxiv.org/abs/1907.01631)
  37. [Cartesian Tree Matching and Indexing.](https://arxiv.org/abs/1905.08974)
  38. [Characteristic Parameters and Special Trapezoidal Words.](https://arxiv.org/abs/1906.01346)
  39. [Circ-Tree: A B+-Tree Variant with Circular Design for Persistent Memory.](https://arxiv.org/abs/1912.09783)
  40. [Circular Pattern Matching with k Mismatches.](https://arxiv.org/abs/1907.01815)
  41. [Communication cost of consensus for nodes with limited memory.](https://arxiv.org/abs/1901.01665)
  42. [Compact Data Structures for Shortest Unique Substring Queries.](https://arxiv.org/abs/1905.12854)
  43. [Compact Fenwick trees for dynamic ranking and selection.](https://arxiv.org/abs/1904.12370)
  44. [Compacted binary trees admit a stretched exponential.](https://arxiv.org/abs/1908.11181)
  45. [Competitive Online Search Trees on Trees.](https://arxiv.org/abs/1908.00848)
  46. [Compressed Indexes for Fast Search of Semantic Data.](https://arxiv.org/abs/1904.07619)
  47. [Compressed Range Minimum Queries.](https://arxiv.org/abs/1902.04427)
  48. [Computing runs on a trie.](https://arxiv.org/abs/1901.10633)
  49. [Constant Delay Traversal of Grammar-Compressed Graphs with Bounded Rank.](https://arxiv.org/abs/1907.10444)
  50. [Constant factor approximations to edit distance on far input pairs in nearly linear time.](https://arxiv.org/abs/1904.05459)
  51. [Constant-factor approximation of near-linear edit distance in near-linear time.](https://arxiv.org/abs/1904.05390)
  52. [Constrained Orthogonal Segment Stabbing.](https://arxiv.org/abs/1904.13369)
  53. [Constructing Antidictionaries in Output-Sensitive Space.](https://arxiv.org/abs/1902.04785)
  54. [Constructing the Bijective BWT.](https://arxiv.org/abs/1911.06985)
  55. [Conversion from RLBWT to LZ77.](https://arxiv.org/abs/1902.05224)
  56. [Convex Graph Invariant Relaxations For Graph Edit Distance.](https://arxiv.org/abs/1904.08934)
  57. [Counting Small Permutation Patterns.](https://arxiv.org/abs/1911.01414)
  58. [Data structures to represent sets of k-long DNA sequences.](https://arxiv.org/abs/1903.12312)
  59. [DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks.](https://arxiv.org/abs/1907.11900)
  60. [Depth First Search in the Semi-streaming Model.](https://arxiv.org/abs/1901.03689)
  61. [Determining satisfiability of 3-SAT in polynomial time.](https://arxiv.org/abs/1903.10081)
  62. [Direct Linear Time Construction of Parameterized Suffix and LCP Arrays for Constant Alphabets.](https://arxiv.org/abs/1906.00563)
  63. [Don't Persist All : Efficient Persistent Data Structures.](https://arxiv.org/abs/1905.13011)
  64. [Dv2v: A Dynamic Variable-to-Variable Compressor.](https://arxiv.org/abs/1911.04202)
  65. [Dynamic Optimality Refuted - For Tournament Heaps.](https://arxiv.org/abs/1908.00563)
  66. [Dynamic Packed Compact Tries Revisited.](https://arxiv.org/abs/1904.07467)
  67. [Dynamic Palindrome Detection.](https://arxiv.org/abs/1906.09732)
  68. [Dynamic Partition Bloom Filters: A Bounded False Positive Solution For Dynamic Set Membership (Extended Abstract).](https://arxiv.org/abs/1901.06493)
  69. [Dynamic Path-Decomposed Tries.](https://arxiv.org/abs/1906.06015)
  70. [E2FM: an encrypted and compressed full-text index for collections of genomic sequences.](https://arxiv.org/abs/1910.04640)
  71. [ER-index: a referential index for encrypted genomic databases.](https://arxiv.org/abs/1910.02851)
  72. [Edge minimization in de Bruijn graphs.](https://arxiv.org/abs/1911.00044)
  73. [Efficient Online String Matching Based on Characters Distance Text Sampling.](https://arxiv.org/abs/1908.05930)
  74. [Efficient computation of the Jacobi symbol.](https://arxiv.org/abs/1907.07795)
  75. [Efficient processing of raster and vector data.](https://arxiv.org/abs/1912.11866)
  76. [Encoding 3SUM.](https://arxiv.org/abs/1903.02645)
  77. [Energy consumption in compact integer vectors: A study case.](https://arxiv.org/abs/1911.09370)
  78. [Engineering Faster Sorters for Small Sets of Items.](https://arxiv.org/abs/1908.08111)
  79. [Engineering Top-Down Weight-Balanced Trees.](https://arxiv.org/abs/1910.07849)
  80. [Entropy Bounds for Grammar-Based Tree Compressors.](https://arxiv.org/abs/1901.03155)
  81. [Entropy Trees and Range-Minimum Queries In Optimal Average-Case Space.](https://arxiv.org/abs/1903.02533)
  82. [Enumerating Range Modes.](https://arxiv.org/abs/1907.10984)
  83. [Enumerative Data Compression with Non-Uniquely Decodable Codes.](https://arxiv.org/abs/1911.05676)
  84. [Even Faster Elastic-Degenerate String Matching via Fast Matrix Multiplication.](https://arxiv.org/abs/1905.02298)
  85. [Every nonnegative real number is an abelian critical exponent.](https://arxiv.org/abs/1906.00665)
  86. [EvoZip: Efficient Compression of Large Collections of Evolutionary Trees.](https://arxiv.org/abs/1910.07819)
  87. [Exhaustive Exact String Matching: The Analysis of the Full Human Genome.](https://arxiv.org/abs/1907.11232)
  88. [Extending General Compact Querieable Representations to GIS Applications.](https://arxiv.org/abs/1911.08376)
  89. [Fast Cartesian Tree Matching.](https://arxiv.org/abs/1908.04937)
  90. [Fast Concurrent Data Sketches.](https://arxiv.org/abs/1902.10995)
  91. [Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series.](https://arxiv.org/abs/1903.03003)
  92. [Fast Fibonacci heaps with worst case extensions.](https://arxiv.org/abs/1911.11637)
  93. [Fast Multiple Pattern Cartesian Tree Matching.](https://arxiv.org/abs/1911.01644)
  94. [Fast Sequence Segmentation using Log-Linear Models.](https://arxiv.org/abs/1902.03285)
  95. [Fast hashing with Strong Concentration Bounds.](https://arxiv.org/abs/1905.00369)
  96. [Fast, Small, and Simple Document Listing on Repetitive Text Collections.](https://arxiv.org/abs/1902.07599)
  97. [Faster Dynamic Compressed d-ary Relations.](https://arxiv.org/abs/1911.08971)
  98. [Faster Integer Multiplication Using Preprocessing.](https://arxiv.org/abs/1911.07124)
  99. [Faster Privacy-Preserving Computation of Edit Distance with Moves.](https://arxiv.org/abs/1911.10719)
  100. [Faster Repetition-Aware Compressed Suffix Trees based on Block Trees.](https://arxiv.org/abs/1902.03274)
  101. [Faster and simpler algorithms for finding large patterns in permutations.](https://arxiv.org/abs/1902.08809)
  102. [Faster queries for longest substring palindrome after block edit.](https://arxiv.org/abs/1901.10722)
  103. [Finding First and Most-Beautiful Queens by Integer Programming.](https://arxiv.org/abs/1907.08246)
  104. [Finding monotone patterns in sublinear time.](https://arxiv.org/abs/1910.01749)
  105. [Finite test sets for morphisms which are square-free on some of Thue's square-free ternary words.](https://arxiv.org/abs/1902.05651)
  106. [Flat combined Red Black Trees.](https://arxiv.org/abs/1912.11417)
  107. [Fully-Dynamic Space-Efficient Dictionaries and Filters with Constant Number of Memory Accesses.](https://arxiv.org/abs/1911.05060)
  108. [Fully-functional bidirectional Burrows-Wheeler indexes.](https://arxiv.org/abs/1901.10165)
  109. [Gardens of Eden in the Game of Life.](https://arxiv.org/abs/1912.00692)
  110. [Generalized Dictionary Matching under Substring Consistent Equivalence Relations.](https://arxiv.org/abs/1909.07538)
  111. [Generalized de Bruijn words and the state complexity of conjugate sets.](https://arxiv.org/abs/1903.05442)
  112. [GraCT: A Grammar-based Compressed Index for Trajectory Data.](https://arxiv.org/abs/1911.04198)
  113. [Grammar Compressed Sequences with Rank/Select Support.](https://arxiv.org/abs/1911.09077)
  114. [Heuristic algorithms for the Longest Filled Common Subsequence Problem.](https://arxiv.org/abs/1904.07902)
  115. [How far away must forced letters be so that squares are still avoidable?](https://arxiv.org/abs/1903.04214)
  116. [How to Store a Random Walk.](https://arxiv.org/abs/1907.10874)
  117. [Implementing the Topological Model Succinctly.](https://arxiv.org/abs/1911.09498)
  118. [Improved Compressed String Dictionaries.](https://arxiv.org/abs/1911.08372)
  119. [Improved local search for graph edit distance.](https://arxiv.org/abs/1907.02929)
  120. [In Search of the Fastest Concurrent Union-Find Algorithm.](https://arxiv.org/abs/1911.06347)
  121. [In oder Aus.](https://arxiv.org/abs/1902.07353)
  122. [Indexing Graph Search Trees and Applications.](https://arxiv.org/abs/1906.07871)
  123. [Inducing the Lyndon Array.](https://arxiv.org/abs/1905.12987)
  124. [Internal Dictionary Matching.](https://arxiv.org/abs/1909.11577)
  125. [It is high time we let go of the Mersenne Twister.](https://arxiv.org/abs/1910.06437)
  126. [LISA: Towards Learned DNA Sequence Search.](https://arxiv.org/abs/1910.04728)
  127. [Learning Multi-dimensional Indexes.](https://arxiv.org/abs/1912.01668)
  128. [Learning Sublinear-Time Indexing for Nearest Neighbor Search.](https://arxiv.org/abs/1901.08544)
  129. [Lempel-Ziv-like Parsing in Small Space.](https://arxiv.org/abs/1903.01909)
  130. [Leyenda: An Adaptive, Hybrid Sorting Algorithm for Large Scale Data with Limited Memory.](https://arxiv.org/abs/1909.08006)
  131. [Lightweight merging of compressed indices based on BWT variants.](https://arxiv.org/abs/1903.01465)
  132. [Linear-size Suffix Tries for Parameterized Strings.](https://arxiv.org/abs/1902.00216)
  133. [Listing Conflicting Triples in Optimal Time.](https://arxiv.org/abs/1911.11048)
  134. [Local Decode and Update for Big Data Compression.](https://arxiv.org/abs/1909.06444)
  135. [Lock-Free Hopscotch Hashing.](https://arxiv.org/abs/1911.03028)
  136. [Longest Common Subsequence on Weighted Sequences.](https://arxiv.org/abs/1901.04068)
  137. [Loop Programming Practices that Simplify Quicksort Implementations.](https://arxiv.org/abs/1906.05384)
  138. [Lp Pattern Matching in a Stream.](https://arxiv.org/abs/1907.04405)
  139. [Lyndon words versus inverse Lyndon words: queries on suffixes and bordered words.](https://arxiv.org/abs/1911.01851)
  140. [Matching Patterns with Variables.](https://arxiv.org/abs/1906.06965)
  141. [Matching reads to many genomes with the r-index.](https://arxiv.org/abs/1908.01263)
  142. [Matching strings in encoded sequences.](https://arxiv.org/abs/1903.09625)
  143. [Memory Lower Bounds for Self-Stabilization.](https://arxiv.org/abs/1905.08563)
  144. [Mergeable Dictionaries With Shifts.](https://arxiv.org/abs/1901.00718)
  145. [Minimal Absent Words in Rooted and Unrooted Trees.](https://arxiv.org/abs/1907.12034)
  146. [Minimal Unique Substrings and Minimal Absent Words in a Sliding Window.](https://arxiv.org/abs/1909.02804)
  147. [Multiple Set Matching and Pre-Filtering with Bloom Multifilters.](https://arxiv.org/abs/1901.01825)
  148. [Multiplication method for factoring natural numbers.](https://arxiv.org/abs/1903.12449)
  149. [Nearly Optimal Static Las Vegas Succinct Dictionary.](https://arxiv.org/abs/1911.01348)
  150. [New Bounds on Antipowers in Binary Words.](https://arxiv.org/abs/1912.08147)
  151. [New Paths from Splay to Dynamic Optimality.](https://arxiv.org/abs/1907.06310)
  152. [New results on pseudosquare avoidance.](https://arxiv.org/abs/1904.09157)
  153. [Non-Rectangular Convolutions and (Sub-)Cadences with Three Elements.](https://arxiv.org/abs/1910.11564)
  154. [On Approximate Range Mode and Range Selection.](https://arxiv.org/abs/1907.08579)
  155. [On Greedy Algorithms for Binary de Bruijn Sequences.](https://arxiv.org/abs/1902.08744)
  156. [On Huang and Wong's Algorithm for Generalized Binary Split Trees.](https://arxiv.org/abs/1901.03783)
  157. [On Longest Common Property Preserved Substring Queries.](https://arxiv.org/abs/1906.05486)
  158. [On Occupancy Moments and Bloom Filter Efficiency.](https://arxiv.org/abs/1908.04810)
  159. [On Prefix-Sorting Finite Automata.](https://arxiv.org/abs/1902.01088)
  160. [On Slicing Sorted Integer Sequences.](https://arxiv.org/abs/1907.01032)
  161. [On dynamic succinct graph representations.](https://arxiv.org/abs/1911.03195)
  162. [On long words avoiding Zimin patterns.](https://arxiv.org/abs/1902.05540)
  163. [On the Average Case of MergeInsertion.](https://arxiv.org/abs/1905.09656)
  164. [On the Complexity of BWT-runs Minimization via Alphabet Reordering.](https://arxiv.org/abs/1911.03035)
  165. [On the Complexity of Exact Pattern Matching in Graphs: Binary Strings and Bounded Degree.](https://arxiv.org/abs/1901.05264)
  166. [On the Complexity of Exact Pattern Matching in Graphs: Determinism and Zig-Zag Matching.](https://arxiv.org/abs/1902.03560)
  167. [On the Hardness and Inapproximability of Recognizing Wheeler Graphs.](https://arxiv.org/abs/1902.01960)
  168. [On the Reproducibility of Experiments of Indexing Repetitive Document Collections.](https://arxiv.org/abs/1912.11944)
  169. [On the cyclic regularities of strings.](https://arxiv.org/abs/1908.01664)
  170. [Online Algorithms for Constructing Linear-size Suffix Trie.](https://arxiv.org/abs/1901.10045)
  171. [Optimal Adaptive Detection of Monotone Patterns.](https://arxiv.org/abs/1911.01169)
  172. [Optimal In-place Algorithms for Basic Graph Problems.](https://arxiv.org/abs/1907.09280)
  173. [Optimal Joins using Compact Data Structures.](https://arxiv.org/abs/1908.01812)
  174. [Order-Preserving Pattern Matching Indeterminate Strings.](https://arxiv.org/abs/1905.02589)
  175. [Orthogonal Range Reporting and Rectangle Stabbing for Fat Rectangles.](https://arxiv.org/abs/1905.02322)
  176. [Padovan heaps.](https://arxiv.org/abs/1902.10812)
  177. [Palindromic Subsequences in Finite Words.](https://arxiv.org/abs/1901.07502)
  178. [Palindromic Ziv-Lempel and Crochemore Factorizations of m-Bonacci Infinite Words.](https://arxiv.org/abs/1905.01340)
  179. [Parallel Finger Search Structures.](https://arxiv.org/abs/1908.02741)
  180. [Parallel decompression of gzip-compressed files and random access to DNA sequences.](https://arxiv.org/abs/1905.07224)
  181. [Partial Sums on the Ultra-Wide Word RAM.](https://arxiv.org/abs/1908.10159)
  182. [Pinning Down the Strong Wilber 1 Bound for Binary Search Trees.](https://arxiv.org/abs/1912.02900)
  183. [Practical Repetition-Aware Grammar Compression.](https://arxiv.org/abs/1910.13479)
  184. [Prefix Block-Interchanges on Binary and Ternary Strings.](https://arxiv.org/abs/1906.04897)
  185. [Proving tree algorithms for succinct data structures.](https://arxiv.org/abs/1904.02809)
  186. [Pseudo-solutions of word equations.](https://arxiv.org/abs/1906.10535)
  187. [Quantum Computing: Lecture Notes.](https://arxiv.org/abs/1907.09415)
  188. [Quasi-Linear-Time Algorithm for Longest Common Circular Factor.](https://arxiv.org/abs/1901.11305)
  189. [QuickSort: Improved right-tail asymptotics for the limiting distribution, and large deviations.](https://arxiv.org/abs/1903.07775)
  190. [Quotient Hash Tables - Efficiently Detecting Duplicates in Streaming Data.](https://arxiv.org/abs/1901.04358)
  191. [RAMBO: Repeated And Merged Bloom Filter for Multiple Set Membership Testing (MSMT) in Sub-linear time.](https://arxiv.org/abs/1910.02611)
  192. [RECIPE : Converting Concurrent DRAM Indexes to Persistent-Memory Indexes.](https://arxiv.org/abs/1909.13670)
  193. [RLE edit distance in near optimal time.](https://arxiv.org/abs/1905.01254)
  194. [Re-Pair In-Place.](https://arxiv.org/abs/1908.04933)
  195. [RecSplit: Minimal Perfect Hashing via Recursive Splitting.](https://arxiv.org/abs/1910.06416)
  196. [Reducing approximate Longest Common Subsequence to approximate Edit Distance.](https://arxiv.org/abs/1904.05451)
  197. [Repetitions in infinite palindrome-rich words.](https://arxiv.org/abs/1904.10028)
  198. [Resolution of the Burrows-Wheeler Transform Conjecture.](https://arxiv.org/abs/1910.10631)
  199. [Revisiting Consistent Hashing with Bounded Loads.](https://arxiv.org/abs/1908.08762)
  200. [Rpair: Rescaling RePair with Rsync.](https://arxiv.org/abs/1906.00809)
  201. [Run-Length Encoding in a Finite Universe.](https://arxiv.org/abs/1909.06794)
  202. [SOSD: A Benchmark for Learned Indexes.](https://arxiv.org/abs/1911.13014)
  203. [Selection on X1+X2+⋅⋅⋅ + Xm with layer-ordered heaps.](https://arxiv.org/abs/1910.11993)
  204. [Separate Chaining Meets Compact Hashing.](https://arxiv.org/abs/1905.00163)
  205. [Separating many words by counting occurrences of factors.](https://arxiv.org/abs/1905.07223)
  206. [Set Cover in Sub-linear Time.](https://arxiv.org/abs/1902.03534)
  207. [Shed More Light on Bloom Filter's Variants.](https://arxiv.org/abs/1903.12525)
  208. [Shortest Unique Palindromic Substring Queries on Run-Length Encoded Strings.](https://arxiv.org/abs/1903.06290)
  209. [Simulating the DNA String Graph in Succinct Space.](https://arxiv.org/abs/1901.10453)
  210. [Sorted Top-k in Rounds.](https://arxiv.org/abs/1906.05208)
  211. [Space Efficient Algorithms for Breadth-Depth Search.](https://arxiv.org/abs/1906.07874)
  212. [Space Efficient Construction of Lyndon Arrays in Linear Time.](https://arxiv.org/abs/1911.03542)
  213. [Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform.](https://arxiv.org/abs/1901.05226)
  214. [Space-Efficient Construction of Compressed Suffix Trees.](https://arxiv.org/abs/1908.04686)
  215. [Space-Efficient Data Structures for Lattices.](https://arxiv.org/abs/1902.05166)
  216. [Space-efficient merging of succinct de Bruijn graphs.](https://arxiv.org/abs/1902.02889)
  217. [Sparse Regular Expression Matching.](https://arxiv.org/abs/1907.04752)
  218. [Speeding up the Karatsuba algorithm.](https://arxiv.org/abs/1905.07455)
  219. [Splaying Preorders and Postorders.](https://arxiv.org/abs/1907.06309)
  220. [Stack Sorting with Increasing and Decreasing Stacks.](https://arxiv.org/abs/1910.03578)
  221. [Stack sorting with restricted stacks.](https://arxiv.org/abs/1907.08142)
  222. [String Attractors and Combinatorics on Words.](https://arxiv.org/abs/1907.04660)
  223. [String Indexing with Compressed Patterns.](https://arxiv.org/abs/1909.11930)
  224. [String Sanitization: A Combinatorial Approach.](https://arxiv.org/abs/1906.11030)
  225. [String Synchronizing Sets: Sublinear-Time BWT Construction and Optimal LCE Data Structure.](https://arxiv.org/abs/1904.04228)
  226. [String factorisations with maximum or minimum dimension.](https://arxiv.org/abs/1912.10140)
  227. [Sublinear Algorithms for Gap Edit Distance.](https://arxiv.org/abs/1910.00901)
  228. [Succinct Data Structures for Families of Interval Graphs.](https://arxiv.org/abs/1902.09228)
  229. [Succinct Representation for (Non)Deterministic Finite Automata.](https://arxiv.org/abs/1907.09271)
  230. [Suffix Trees, DAWGs and CDAWGs for Forward and Backward Tries.](https://arxiv.org/abs/1904.04513)
  231. [Superset Technique for Approximate Recovery in One-Bit Compressed Sensing.](https://arxiv.org/abs/1910.13971)
  232. [Survey of Information Encoding Techniques for DNA.](https://arxiv.org/abs/1906.11062)
  233. [Techniques for Inverted Index Compression.](https://arxiv.org/abs/1908.10598)
  234. [The Alternating BWT: an algorithmic perspective.](https://arxiv.org/abs/1907.02308)
  235. [The Bloom Clock.](https://arxiv.org/abs/1905.13064)
  236. [The One-Way Communication Complexity of Dynamic Time Warping Distance.](https://arxiv.org/abs/1903.03520)
  237. [The PGM-index: a multicriteria, compressed and learned approach to data indexing.](https://arxiv.org/abs/1910.06169)
  238. [The Parameterized Position Heap of a Trie.](https://arxiv.org/abs/1903.06289)
  239. [The Strong 3SUM-INDEXING Conjecture is False.](https://arxiv.org/abs/1907.11206)
  240. [The Tandem Duplication Distance is NP-hard.](https://arxiv.org/abs/1906.05266)
  241. [The Weak Circular Repetition Threshold Over Large Alphabets.](https://arxiv.org/abs/1912.11388)
  242. [The k-d tree data structure and a proof for neighborhood computation in expected logarithmic time.](https://arxiv.org/abs/1903.04936)
  243. [The power word problem.](https://arxiv.org/abs/1904.08343)
  244. [The repetition threshold for binary rich words.](https://arxiv.org/abs/1908.03169)
  245. [The smallest grammar problem revisited.](https://arxiv.org/abs/1908.06428)
  246. [Top Tree Compression of Tries.](https://arxiv.org/abs/1902.02187)
  247. [Towards Better Compressed Representations.](https://arxiv.org/abs/1911.02889)
  248. [Towards a Definitive Measure of Repetitiveness.](https://arxiv.org/abs/1910.02151)
  249. [Tree-Shape Grammars for Random Access.](https://arxiv.org/abs/1910.07145)
  250. [Unconstrained Church-Turing thesis cannot possibly be true.](https://arxiv.org/abs/1901.04911)
  251. [Weighted Shortest Common Supersequence Problem Revisited.](https://arxiv.org/abs/1909.11433)
  252. [What Storage Access Privacy is Achievable with Small Overhead?](https://arxiv.org/abs/1904.05452)
  253. [When a Dollar Makes a BWT.](https://arxiv.org/abs/1908.09125)
  254. [Words Avoiding Reversed Factors, Revisited.](https://arxiv.org/abs/1911.11704)
  255. [Words With Few Palindromes, Revisited.](https://arxiv.org/abs/1911.12464)
  256. [Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters.](https://arxiv.org/abs/1912.08258)
  257. [k-Spectra of c-Balanced Words.](https://arxiv.org/abs/1904.09125)
  258. [scaleBF: A High Scalable Membership Filter using 3D Bloom Filter.](https://arxiv.org/abs/1903.06570)

#### Comput. J. 2019
  1. [Context Sensitive Rewriting Codes for Flash Memory†.](https://doi.org/10.1093/comjnl/bxy020)
  2. [Edit Distance with Multiple Block Operations†.](https://doi.org/10.1093/comjnl/bxy066)

#### Dagstuhl Reports 2019
  1. [25 Years of the Burrows-Wheeler Transform (Dagstuhl Seminar 19241).](https://doi.org/10.4230/DagRep.9.6.55)

#### IEEE Trans. Inf. Theory 2019
  1. [RePair and All Irreducible Grammars are Upper Bounded by High-Order Empirical Entropy.](https://doi.org/10.1109/TIT.2018.2871452)

#### Inf. Comput. 2019
  1. [Lempel-Ziv compressed structures for document retrieval.](https://doi.org/10.1016/j.ic.2019.01.006)
  2. [On-line weighted pattern matching.](https://doi.org/10.1016/j.ic.2019.01.001)

#### Inf. Process. Lett. 2019
  1. [Applying the Positional Burrows-Wheeler Transform to all-pairs Hamming distance.](https://doi.org/10.1016/j.ipl.2019.02.003)
  2. [Comparison of LZ77-type parsings.](https://doi.org/10.1016/j.ipl.2018.09.005)

#### Inf. Sci. 2019
  1. [GraCT: A Grammar-based Compressed Index for Trajectory Data.](https://doi.org/10.1016/j.ins.2019.01.035)

#### Inf. Syst. 2019
  1. [On the reproducibility of experiments of indexing repetitive document collections.](https://doi.org/10.1016/j.is.2019.03.007)

#### J. Comb. Optim. 2019
  1. [Efficient enumeration of non-equivalent squares in partial words with few holes.](https://doi.org/10.1007/s10878-018-0300-z)

#### J. Comput. Syst. Sci. 2019
  1. [Hide and seek with repetitions.](https://doi.org/10.1016/j.jcss.2018.10.004)

#### Rev. Socionetwork Strateg. 2019
  1. [Storing Partitions of Integers in Sublinear Space.](https://doi.org/10.1007/s12626-019-00044-2)

#### SIAM J. Comput. 2019
  1. [Bicriteria Data Compression.](https://doi.org/10.1137/17M1121457)
  2. [Truly Subcubic Algorithms for Language Edit Distance and RNA Folding via Fast Bounded-Difference Min-Plus Product.](https://doi.org/10.1137/17M112720X)

#### SIAM J. Discret. Math. 2019
  1. [Rollercoasters: Long Sequences without Short Runs.](https://doi.org/10.1137/18M1192226)

#### Softw. Pract. Exp. 2019
  1. [A compact index for order-preserving pattern matching.](https://doi.org/10.1002/spe.2694)

#### Theor. Comput. Sci. 2019
  1. [A substring-substring LCS data structure.](https://doi.org/10.1016/j.tcs.2018.06.034)
  2. [Algorithms to compute the Burrows-Wheeler Similarity Distribution.](https://doi.org/10.1016/j.tcs.2019.03.012)
  3. [Approximate cover of strings.](https://doi.org/10.1016/j.tcs.2019.05.020)
  4. [Document listing on repetitive collections with guaranteed performance.](https://doi.org/10.1016/j.tcs.2018.11.022)
  5. [Efficient dynamic dictionary matching with DAWGs and AC-automata.](https://doi.org/10.1016/j.tcs.2018.04.016)
  6. [Improved upper bounds on all maximal α-gapped repeats and palindromes.](https://doi.org/10.1016/j.tcs.2018.06.033)
  7. [Maximal common subsequence algorithms.](https://doi.org/10.1016/j.tcs.2019.06.020)
  8. [On overabundant words and their application to biological sequence analysis.](https://doi.org/10.1016/j.tcs.2018.09.011)
  9. [On the size of the smallest alphabet for Lyndon trees.](https://doi.org/10.1016/j.tcs.2018.06.044)
  10. [Path queries on functions.](https://doi.org/10.1016/j.tcs.2018.10.021)
  11. [Universal compressed text indexing.](https://doi.org/10.1016/j.tcs.2018.09.007)

#### Theory Comput. Syst. 2019
  1. [Pattern Matching and Consensus Problems on Weighted Sequences and Profiles.](https://doi.org/10.1007/s00224-018-9881-2)

repository: stringologytimes/StringologyTimes

gha_language: TypeScript

repo_name: stringologytimes/StringologyTimes


text:
- **Assignee**: This would typically be used to assign work to an individual if jira is being used to track project work. For most of our Issue type ‘Assignee’ has no significance and will be hidden.

We will be using this for some issues as the person who needs to next respond, provide information, push forward or make progress on an issue type. If you think of a game of tennis, the ball is in the Assignee’s court.

E.G. An Outcome with the status ‘Needs more details’ – Could be assigned to the person who we think might be able to provide the additional detail.

- **Reporter**: The person who created the item. This has no other significance in our workflow.

repository: BigPeeg/Squads-And-Maps

branch_name: refs/heads/master

extension: md

license_type: permissive

repo_name: BigPeeg/Squads-And-Maps


text:
# jloan

Loan Schedule For Java

[![Codacy Badge](https://api.codacy.com/project/badge/Grade/841ed6f10f7146bfb3d319c85d0cfc63)](https://www.codacy.com/manual/timmson/jloan)
[![Gradle Package](https://github.com/timmson/jloan/workflows/Gradle%20Package/badge.svg)](https://github.com/timmson/jloan/actions?query=workflow%3A%22Gradle%20Package%22)

## Example of usage

[see more](./tree/master/src/test/java/ru/timmson/jloan)

````java
class Example {

    public static void  main(String[] args) {

            final Loan loan = annuityLoanBuilder()
                    .amount(500000) //amount
                    .annualInterestRate(11.5) //interest
                    .termInMonth(12) //term
                    .paymentOnDay(25) //day of payment
                    .issueDate(2018, 10, 25) //issue date
                    .build();

            final LoanSchedule schedule = loan.getSchedule();

            System.out.println(schedule);
    }
}
````

## Set fixed payment
````java
final Loan loan = annuityLoanBuilder()
...
    .paymentAmount(57000) //57000.00 will be setted as payment through all monthes except last
...
````

## Set production calendar
````java
final Loan loan = annuityLoanBuilder()
...
    .productionCalendar(RussianProductionCalendar.getInstance()) // you can implement ProductionCalendar youself
...
````

### Add Early repayment
````java
final Loan loan = annuityLoanBuilder()
...
    addEarlyRepayment(LocalDate.of(2016, 12, 26), BigDecimal.valueOf(44000)) // you can implement ProductionCalendar youself
...
````

license: MIT

repository: timmson/jloan

repo_name: timmson/jloan


text:
---
title: "Extend R.apex"
description: "Extend R.apex"
buttonTitle: "Done"
parentId: "getting_started"
layout: "tutorial"
time: 90
weight: 8
---

## {$page.title}

It is your personal preference to choose between functional composition and function chaining. And the key takeaway is to use whatever is suitable in your case.

It is sad that the discovery of R.apex almost comes to an end. Realizing that the functions provided by R.apex is limited, you have to come up with your functions to tackle all the difficult business logic. The suggestion will be to encapsulate your core business logic in small custom functions and glue them together with the power of R.apex to build your own application. And this is the way you extend R.apex.

gha_license_id: MIT


text:
Simple Node Config
===========
[![Build Status](https://travis-ci.org/AgencyPMG/node-super-config.svg?branch=master)](https://travis-ci.org/AgencyPMG/node-super-config) [![Coverage Status](https://coveralls.io/repos/AgencyPMG/node-super-config/badge.png?branch=master)](https://coveralls.io/r/AgencyPMG/node-super-config?branch=master)

This light-weight NodeJS package allows you to load your config files, as well as easily edit them with getters and setters. The files have to be in JSON format.

##Examples

###Loading Config Files
Store the `super-config` class in a variable and load as many configuration files as you have.
```
var config = require('super-config');

config.loadConfig([
    __dirname + '/app/config/config',
    __dirname + '/app/config/local'
]);
```
**It's that simple.**

### Example config file
```js
module.exports = {
    database: {
        host:'<IP_ADDRESS>',
        port:'27017',
        dbname:'example_DB'
    },
    someOtherSetting: 1234,
    name: 'myname'
}
```

###Getting Information
Let's pretend our config file contains this section of code:
```js
database: {
    host:'<IP_ADDRESS>',
    port:'27017',
    dbname:'example_DB'
}
```
It would pretty nice if we could easily retrieve that information right? Here's how-to:
```js
var host = config.get('database.host', '');
var port = config.get('database.port', '');
var dbName = config.get('database.dbname', '');
```
**It's that simple.**

###Setting Information
Need to set some information in the config object? Not a problem:
```js
config.set('database.host', 'mydbserver');
```

**Simple Config, it's THAT simple.**

repository: AgencyPMG/node-super-config

gha_language: JavaScript

repo_name: AgencyPMG/node-super-config


text:
# PythonTutorials
This repo will serve beginners as a quick start guide to start working on Python.
We have included each and every program files starting from my scratch.

PYTHON Environment Used : 3.7.2


text:
# Dean Attali's Shiny Server

> *Copyright 2016 [Dean Attali](http://deanattali.com). Licensed under the MIT license.*

This repo contains the setup of [my Shiny server](http://daattali.com/shiny/).  It is a git repo under `/srv/shiny-server` on my server.

To learn how you can get your own Shiny Server in a similar way, [read my tutorial about how to set up Shiny Server](http://deanattali.com/2015/05/09/setup-rstudio-shiny-server-digital-ocean/).

Shiny servers can host shiny apps and R markdown documents.

The [config](./config) directory contains a few configuration files that are used on the server.

---

Original author: Dean Attali [deanattali.com](http://deanattali.com)

repository: ycalvinner/shiny-server

repo_name: ycalvinner/shiny-server


text:
---
layout: post
title: "Age prediction's child diseases"
modified:
categories: blog
excerpt:
tags: ["face detection","microsoft", "age & gender prediction", "machine vision"]
date: 2015-05-01T16:00:00-00:00
share: true
---

In this [(second) machine age][second-machine-age], it was only a matter of time before
machines would start guessing our age. Researchers from Microsoft have
recently released an online tool called "[How Old Do I
Look?][how-old]". When given a photo, the tool will not only tell you how
old you are, but also your gender.

Since one is never too old to learn
— especially about oneself — I gave
it a go. Contrary to this [rather biased article in The
Guardian][guardian-how-old], I wanted to use more than a single
data point per person to evaluate the predictor's quality. (Data) Science oblige!

Enter my often mocked selfie archive, painstakenly collected over the
years for exactly this kind of scientific purpose. Thirteen pictures
from the last year were pseudo-randomly selected, with some variation in
hairstyle, location, sunlight, season, hours of sleep, bespectacledness, and headwear.

Let's start with the good news: in 13 out of 13 cases, my gender was determined as
being of the **male** kind. To whom it may concern, and for the record: this prediction is **100%
congruent with the actual situation**.

Then again, according to Microsoft, my **average age** over the last year
was (38 + 39 + 42 + 43 + 43 + 45 + 47 + 48 + 54 + 54 + 55 + 55 + 58) /
13 = **47,8** years. This is **almost 2 years more than the actual**
average age I had when the photos were taken. Not brilliant, but not
that bad either, given the relatively small test sample size.

With a **standard deviation** of **6.7 years** (about 1/7 of the
average), the age predictor does allow itself a fair amount of
variability. As the saying goes: _with age comes wisdom, but sometimes age comes
alone._ I'm talking about the predictor, of course — it may
still have some child diseases to outgrow.

On a less serious and scientific note: both my daughters will no doubt revel in joy that **funny hats** do not make a
middle-aged person — let alone a father — look any
younger. Quite the contrary.

[how-old]: http://how-old.net
[second-machine-age]: http://www.secondmachineage.com
[guardian-how-old]: http://www.theguardian.com/media/2015/may/01/how-old-do-i-look-another-way-to-feel-bad-about-yourself-online


text:
![dogescript](doge.gif)

## dogescript 3

(aka when Zach went insane)

This is an implementation of the best new compile-to-JS language, dogescript. Wow.

Many things has been added in this implementation, such as, "native" DSON, new syntax, and a rebuilt parser.

This is not affiliated with the official [dogescript orginization](https://github.com/dogescript) in any way.

All rights of dogescript goes to Zach a.k.a [remixz](https://github.com/remixz)

**Note that not everything works in this implementation**

```
    wow
         such dogescript
     very compiled
                  next-generation
       npm wow
```

### Installation

`npm install -g dogescript-3`

### Usage

#### Command Line

`dogescript-3` without a file launches a REPL.

`dogescript-3 location/to/dogescript.djs` pipes the result to stdout. Use a command like `dogescript-3 dogescript.djs > compiled.js` to save to a file.

#### Javascript

`dogescript(file)`
* `file` - A string of Dogescript.

### Language documentation

* Introduction to Dogescript - http://alexdantas.net/stuff/posts/introduction-to-dogescript/
* `LANGUAGE.md`

### Projects using dogescript

* [Doge Adventure!](https://github.com/ngscheurich/doge-adventure): A text adventure game inspired by [leonsumbitches](http://dailydoge.tumblr.com/post/21839788086/leonsumbitches-you-have-encountered-a-doge).
* [Doge Game of Life](https://github.com/eerwitt/doge-game-of-life): Conway's Game of Life in dogescript.
* [doge-toe](http://alexdantas.net/games/doge-toe/): Tic-Tac-Toe in dogescript.

### Utilities

#### Syntax highlighting

* [vim-dogescript](https://github.com/valeriangalliat/vim-dogescript): Vim highlighting.
* [dogescript-mode](https://github.com/alexdantas/dogescript-mode): Emacs highlighting.

#### Build plugins

* [dogeify](https://github.com/remixz/dogeify): A [Browserify](http://browserify.org/) transform for dogescript, also usable in [Gulp](https://github.com/gulpjs/gulp)
* [dogescript-loader](https://github.com/Bartvds/dogescript-loader): A [Webpack](https://Webpack.github.io) loader to bundle dogescript modules.
* [grunt-dogescript](https://github.com/Bartvds/grunt-dogescript): A [Grunt](http://gruntjs.com) plugin to compile dogescript (written in Dogescript!).
* [require-doge](https://github.com/Bartvds/require-doge): Directly require() dogescript .djs files in [node.js](http://www.nodejs.org).
* [lineman-dogescript](https://github.com/linemanjs/lineman-dogescript): A [Lineman](http://linemanjs.com/) plugin to compile dogescript.

### Contributors

The "original" [dogescript](https://github.com/dogescript/dogescript) has been made possible thanks to the contributions of many people. Thank you to everyone who has contributed in some way!

```bash
$ git log --format='%aN' | sort -u

Bart van der Schoor
Ben Atkin
Chad Engler
Chris Wheatley
Daniel Lockhart
Elan Shanker
Erik Erwitt
Jacob Groundwater
Joe Dailey
Johann Philipp Strathausen
Joseph Dailey
Nicholas Scheurich
Patrick Piemonte
Ray Toal
Zach Bruggeman
achesak
alehander42
dogejs
jasdev
noformnocontent
```


text:
gson-deep-merge
===============

[![CircleCI](https://circleci.com/gh/brymck/gson-deep-merge.svg?style=svg)](https://circleci.com/gh/brymck/gson-deep-merge)
[![codecov](https://codecov.io/gh/brymck/gson-deep-merge/branch/master/graph/badge.svg)](https://codecov.io/gh/brymck/gson-deep-merge)

`gson-deep-merge` is a library that allows deep merging of objects with Gson.

Usage
-----

Include this in your POM:

```xml
<dependency>
  <groupId>com.github.brymck</groupId>
  <artifactId>gson-deep-merge</artifactId>
  <version>0.9.0</version>
</dependency>
```

And use it as so, given two instances `original` and `update` of class `Example`:

```java
Gson gson = new Gson();
GsonDeepMerge gsonDeepMerge = new GsonDeepMerge();

Example merged = gsonDeepMerge.deepMerge(gson, original, update, Example.class);
```

One obvious use case for tools like Kotlin is to embed this in an extension function.
For instance, given the above `Example` class:

```kotlin
// Extension implementation
private val gson = Gson()
private val gsonDeepMerge = GsonDeepMerge()

fun Example.deepMerge(other: Example): Example =
  gsonDeepMerge.deepMerge(gson, this, other, this::class.java)

// Usage
val foo = Example(foo = Foo())
val bar = Example(bar = Bar())
val fooBar = foo.deepMerge(bar);
```

repository: brymck/gson-deep-merge

gha_language: Java

repo_name: brymck/gson-deep-merge


text:
---
layout: post

title: "Two Weeks of Easy Meal Prep"
permalink: /easy-meal-prep-with-nutrition-solutions/

banner: true
banner_url: "https://dwxg8af4z2ddw.cloudfront.net/food-bg.jpg"

category: general
comments: false

---

In my last post about [turning 35](on-turning-35), I touched a little bit about my weight.

Part of my plan for getting myself straightened out is fixing my eating habits. Three weeks ago I stumbled upon an easy solution to the food problem. No, it's not weight watchers.

I found a company based in our home state of Florida called [Nutrition Solutions](https://nutritionsolutionslifestyle.com). They offer a variety of pre-made meal plans for athletes, body builders and people trying to lose weight.

Nutrition Solutions prepares and ships out pre-made meals once a week for the whole week on a weekly subscription basis. They ship to the lower 48 usually next day air. The meals arrive fresh and stored in ice. We usually immediately freeze ours.

![Nutrition Solutions](https://dwxg8af4z2ddw.cloudfront.net/2017-07-20 13.14.10.jpg)

The benefit of all this is that meal prep is made easy. No figuring out what to eat for the week. Or trying to solve macros and calories. No arguing or debating with the wife on what to make/cook.

It also eliminates decision fatigue completely with what to eat.

I chose their [FAT LOSS 5 DAY PLAN](https://nutritionsolutionslifestyle.com/weight-loss-meals-plans/) w/o Breakfast for $141 per week. Which just happens to fit in our food budget anyhow.  You get 20 entrees which, works out to two meals per day for two people.

The best thing is, everything is low carb with this method. I'm eating less than 100 grams of carbs.

Each weekday morning, I skip breakfast. Usually, I just have bullet proof coffee after my workout. Then around 1 or 2, I'll have one of the prepared meals. And then on the weekend, I fast with water only.

To be honest, it's been a bit of an eye opener on portion sizes. I've been keeping a food journal for the past two weeks as we've done this.

For example, one meal from last week "Southwestern Chicken" had 36 grams of carbs. 35 grams of Protein, 9 grams of fat and 365 calories total.

And this is what it looked like:

![Southwestern Chicken](https://dwxg8af4z2ddw.cloudfront.net/2017-07-13 18.54.32.jpg)

Meal Quality
---

In a word, excellent. It's not a TV dinner, that's for sure. Nutrition Solutions has a rotating menu. We've been on it for two weeks, and the meals haven't been the same once yet. Our 3rd-week menu was just sent to us, and it's completely different. The foods are similar. And the dishes usually contain one meat item and two or three vegetable items.

![Meatballs](https://dwxg8af4z2ddw.cloudfront.net/2017-07-17 12.41.37.jpg)

The quality and variety has been great. And it's already fueled some weight loss for both of us. My wife has had the most success, loosing 12lbs in the first week. I've lost 7lbs.

We're going to continue with this for a full four weeks to see how we do. And then I think we might attempt to replicate the meal plan on our own for some additional cost savings.

But for now, this makes it easier for myself and my wife to work towards our goals.

If you're interested in trying this service, [USE THIS LINK](http://nutritionsolutions.refr.cc/michaelkey) to get $10 dollars off your order.

branch_name: refs/heads/gh-pages

gha_language: HTML


text:
# GitHub and Government [![Test site build](https://github.com/github/government.github.com/actions/workflows/build.yml/badge.svg)](https://github.com/github/government.github.com/actions/workflows/build.yml)

![screenshot](assets/img/screenshot.png)

Gather, curate, and feature stories of people using GitHub as part of their open government innovations.

The site is open source (here's all the code!) and is a tool _for_ and _by_ the community.

Submit [issues](https://github.com/github/government.github.com/issues/new) and [pull requests](https://github.com/github/government.github.com/compare/) for stories, site ideas or copy edits.

### Goals

- Share stories of real world experiences using GitHub in open Government
- Demystify open source terminology
- Showcase the community using GitHub to promote connections and sharing between individuals and organizations.
- Make getting started with GitHub easier

### Under the Hood

This site is made with [Jekyll](https://jekyllrb.com), an open source static site generator. This means the Jekyll program takes the content we want to be on the site and turns them into HTML files ready to be hosted somewhere. Awesomely, GitHub provides free web hosting for repositories, called [GitHub Pages](https://pages.github.com/), and that's how this site is hosted. The content for the site is on a branch named [gh-pages](https://github.com/github/government.github.com/tree/gh-pages).

## Contributing

#### Fix/Edit Content

If you see an error or a place where content should be updated or improved, just fork this repository to your account, make the change you'd like and then submit a pull request. If you're not able to make the change, file an [issue](https://github.com/github/government.github.com/issues/new).

#### Add Organization

If you know of an [GitHub organization](https://help.github.com/articles/about-organizations/) that should be added to the organization list that generates the matrix of avatars on the [Community](https://government.github.com/community/) page: fork this repository, open the [_data/civic_hackers.yml](_data/civic_hackers.yml), [_data/governments.yml](_data/governments.yml), or[_data/research.yml](_data/research.yml) file and add it to the appropriate section of the list in the format being used. Commit your change and submit a pull request to us!

---

## To Set up Locally

You can take all the files of this site and run them just on your computer as if it were live online, only it's just on your machine.

#### Requirements

* [Jekyll](https://jekyllrb.com/)
* [Ruby](https://www.ruby-lang.org/en/)
* [Git](https://git-scm.com/)
* A JavaScript runtime ([node.js](https://nodejs.org/en))

_If you have installed [GitHub Desktop](https://desktop.github.com), Git was also installed automatically._

To copy the repository's files from here onto your computer and to view and serve those files locally, at your computer's command line type:

```bash
git clone https://github.com/github/government.github.com.git
cd government.github.com
script/bootstrap
script/server
```
Open `http://localhost:4000` in your browser

## Deploying

government.github.com now utilizes a two-repo approach to managing staging and production deployments:

- **Production:** [github/government.github.com](https://github.com/github/government.github.com/) (this repository)
- **Staging:** [government/staging](https://ghe.io/government/staging)

For small changes, you can deploy right to production by merging a pull request. For larger changes, push your branch to the staging repo from Terminal. Here's how to setup staging and deploy to it:

```
$ script/stage staging
```

This script will generate the government site (without starting the local server) and prep it for staging. It does this by creating a temporary Git repo within the compiled `_site` directory and force pushing that to a separate remote repo (in this case, https://ghe.io/government/staging).

Pushing to the staging repo requires authenticating with GitHub via Terminal. You'll be asked for a username and password when running `script/stage`. Use your GHE.io username and, since we enforce 2FA, use a [personal access token](https://help.github.com/articles/creating-a-personal-access-token-for-the-command-line/) as your password.

_Having trouble deploying to a staging server? Delete the entire `_site` directory and try again. Sometimes the temporary Git repository we make in the script can go awry._

When you're done with staging and your pull request has been approved, you can merge your branch. Your changes will be automatically deployed to the production site in a few minutes.

----

#### Triage Issues [![Open Source Helpers](https://www.codetriage.com/github/government.github.com/badges/users.svg)](https://www.codetriage.com/github/government.github.com)

In addition to contributing changes, you can help to triage issues. This can include asking for vital information or requesting formatting changes. If you would like to start triaging issues, one easy way to get started is to [subscribe to government.github.com on CodeTriage](https://www.codetriage.com/github/government.github.com).

----

Don't see what you're looking for? Create an [issue](https://github.com/github/government.github.com/issues/new), we'll do our best to help you out.

## License

The data in `_data` is free to use without restriction. For clarity these files, and contributions to these files, are released under [CC0-1.0](https://creativecommons.org/publicdomain/zero/1.0/).

When using the GitHub logos, be sure to follow the [GitHub logo guidelines](https://github.com/logos).


text:
# HDRI Skybox Librarian

An  **HDRI Skybox Librarian** is an HDRI skybox records database.

An **HDRI skybox** is a background image with real-world lighting data. See the `hdri.py` example controller.

```python
from tdw.librarian import HDRISkyboxLibrarian

lib = HDRISkyboxLibrarian()
```

```python
from tdw.librarian import HDRISkyboxLibrarian

lib = HDRISkyboxLibrarian(library="path/to/your/database/file.json")
```

An HDRI Skybox Librarian contains `HDRISkyboxRecord` objects.

```python
record = lib.records[0]
print(record.name) # aft_lounge_4k
```

## Default Libraries

There is only one HDRI skybox library: `hdri_skyboxes.json`. You can define it explicitly, or not.

```python
from tdw.librarian import HDRISkyboxLibrarian

# These constructors will load the same records database.
lib = HDRISkyboxLibrarian()
lib = HDRISkyboxLibrarian(library="hdri_skyboxes.json")
```

## Command API

Send the `add_hdri_skybox` command to add an HDRI skybox from a remote or local asset bundle.

```python
from tdw.controller import Controller

c = Controller()

init(c) # Initialize the scene. Your code here.
record = get_record() # Get an HDRI skybox record. Your code here.

c.communicate({"$type": "add_hdri_skybox",
                "name": record.name,
                "url": record.get_url(),
                "exposure": record.exposure,
                "initial_skybox_rotation": record.initial_skybox_rotation,
                "sun_elevation": record.sun_elevation,
                "sun_initial_angle": record.sun_initial_angle,
                "sun_intensity": record.sun_intensity})
```

The `Controller` class includes a few helper functions for adding HDRI skyboxes. See the [Controller documentation](../controller.md).

## HDRISkyboxRecord API

A record of an HDRI Skybox asset bundle.

```python
from tdw.librarian import HDRISkyboxRecord

record = HDRISkyboxRecord () # Creates a record with blank or default values.
```

```python
from tdw.librarian import HDRISkyboxRecord

record = HDRISkyboxRecord(data=data) # Creates a record from JSON data.
```

### Fields

| Field                    | Type           | Description                                                  |
| ------------------------ | -------------- | ------------------------------------------------------------ |
| `name`                   | str            | The name of the skybox.                                      |
| `urls`                   | Dict[str, str] | A dictionary of URLs or local filepaths of asset bundles per platform. See: `HDRISkyboxRecord.get_url()` |
| `color_temperature`      | float          |                                                              |
| `sun_elevation`          | float          |                                                              |
| `sun_initial_angle`      | float          |                                                              |
| `sun_intensity`          | float          |                                                              |
| `intial_skybox_rotation` | float          |                                                              |
| `exposure`               | float          |                                                              |
| `location`               | str            | Interior or exterior. Useful for deciding what skybox to load. |

### Functions

##### `def get_url(self) -> str:`

Returns the URL of the asset bundle for this platform. This is a wrapper for `record.urls`.

```python
lib = HDRISkyboxLibrarian()
record = lib.records[0]

print(record.get_url())
```

***

## HDRISkyboxLibrarian API

### Fields

| Field         | Type                   | Description                                                  |
| ------------- | ---------------------- | ------------------------------------------------------------ |
| `library`     | str                    | The path to the records database file.                       |
| `data`        | dict                   | The raw JSON dictionary loaded from the records database file. |
| `description` | str                    | A brief description of the library.                          |
| `records`     | List[HDRISkyboxRecord] | The list of HDRI skybox records.                             |

### Static Functions

##### `def create_library(description: str, path: str) -> None:`

Create a new library JSON file.

```python
HDRISkyboxLibrarian.create_library("My library", path="path/to/new/library.json")
```

| Parameter     | Type | Description                                               |
| ------------- | ---- | --------------------------------------------------------- |
| `description` | str  | A description of the library.                             |
| `path`        | str  | The absolute filepath to the .json records database file. |

***

##### `def get_library_filenames() -> List[str]:`

Returns a list of the filenames of the libraries of this type in the `tdw` module.

```python
filenames = HDRISkyboxLibrarian.get_library_filenames()

print(filenames) # ['hdri_skyboxes.json']
```

***

##### `def get_default_library() -> List[str]:`

Returns the filename of the default library (which is always the first element in the list returned by `get_library_filenames()`.

```python
default_library = HDRISkyboxLibrarian.get_default_library()

print(default_library) # hdri_skyboxes.json
```

### Functions

##### `def get_record(self, name: str) -> Optional[HDRISkyboxRecord]:`

Returns a record with the specified name. If that record can't be found, returns None.

```python
lib = HDRISkyboxLibrarian()
record = lib.get_record("aft_lounge_4k")

print(record.name) # aft_lounge_4k
```

| Parameter | Type | Description             |
| --------- | ---- | ----------------------- |
| `name`    | str  | The name of the record. |

***

##### `def search_records(self, search: str) -> List[HDRISkyboxRecord]:`

Returns a list of records whose names include the search keyword.

```python
lib = HDRISkyboxLibrarian()
records = lib.search_records("lounge")

for record in records:
    print(record.name) # aft_lounge_4k
```

| Parameter | Type | Description                                  |
| --------- | ---- | -------------------------------------------- |
| `search`  | str  | The string to search for in the skybox name. |

***

##### `def add_or_update_record(self, record: HDRISkyboxRecord, overwrite: bool, write: bool = True, quiet: bool = True) -> bool:`

Add a new record or update an existing record.

```python
record = define_record() # Provide your own code here.
lib = HDRISkyboxLibrarian()

lib.add_or_update_record(record, False, write=True, quiet=False)
```

| Parameter   | Type             | Description                                                  |
| ----------- | ---------------- | ------------------------------------------------------------ |
| `record`    | HDRISkyboxRecord | The new or modified record.                                  |
| `overwrite` | bool             | **If True:** If there is a record with the same name as this record, replace it with the new record and return True. Otherwise, return False.
**If False:** If there is a record with the same name as this record, don't add the skybox, and suggest a new name. |
| `write`     | bool             | If true, write the library data to disk  (overwriting the existing file). |
| `quiet`     | bool             | If true, don't print out messages to the console.            |

***

##### `def remove_record(self, record: Union[str, HDRISkyboxRecord], write: bool = True) -> bool:`

Remove a record. Returns true if the record was removed.

```python
record = define_record() # Provide your own code here.
lib = HDRISkyboxLibrarian()

lib.remove_record(record) # Returns False.
```

```python
lib = HDRISkyboxLibrarian()

lib.remove_record("aft_lounge_4k") # Returns True.
```

| Parameter | Type                      | Description                                                  |
| --------- | ------------------------- | ------------------------------------------------------------ |
| `record`  | HDRISkyboxRecord _or_ str | The record or the name of the record.                        |
| `write`   | bool                      | If true, write the library data to disk  (overwriting the existing file). |

***

##### `def write(self, pretty=True) -> None:`

Write the library data to disk (overwriting the existing file).

| Parameter | Type | Description                                                  |
| --------- | ---- | ------------------------------------------------------------ |
| `pretty`  | bool | "Pretty print" the JSON data with line breaks and indentations. |

***

##### `def get_valid_record_name(self, name: str, overwrite: bool) -> Tuple[bool, str, List[str]]:`

Generates a valid record name. Returns: true if the name is good as-is, the new name, and a list of problems with the old name.

```python
lib = HDRISkyboxLibrarian()

ok, name, problems = lib.get_valid_record_name("aft_lounge_4k", True)

print(ok) # True
print(name) # aft_lounge_4k
```

```python
lib = HDRISkyboxLibrarian()

ok, name, problems = lib.get_valid_record_name("aft_lounge_4k", False)

print(ok) # False
print(name) # aft_lounge_4kabcd
print(problems) # ["A record named aft_lounge_4k already exists, and we don't want to overwrite it."]
```

| Parameter   | Type | Description                                                  |
| ----------- | ---- | ------------------------------------------------------------ |
| `name`      | str  | The name of a record we'd like to add.                       |
| `overwrite` | str  | **If True:** raise an exception if a record named `name` doesn't already exist.
**If False:** If the record exists, suggest a new name. |

***

repository: threedworld-mit/tdw

gha_language: Python

repo_name: threedworld-mit/tdw


text:
# aws-serverless-restful-wrapper

---
**NOTE**
This package is no longer maintained and was moved to [@cloudifyjs/restful](https://www.npmjs.com/package/@cloudifyjs/restful).
---

An API Gateway event wrapper for AWS Lambda functions for REST APIs

[![CircleCI](https://circleci.com/gh/diegotremper/aws-serverless-restful-wrapper.svg?style=svg)](https://circleci.com/gh/diegotremper/aws-serverless-restful-wrapper)
![npm](https://img.shields.io/npm/v/aws-serverless-restful-wrapper)
![npm](https://img.shields.io/npm/dw/aws-serverless-restful-wrapper)
[![codecov](https://codecov.io/gh/diegotremper/aws-serverless-restful-wrapper/branch/master/graph/badge.svg)](https://codecov.io/gh/diegotremper/aws-serverless-restful-wrapper)
[![dependencies Status](https://david-dm.org/diegotremper/aws-serverless-restful-wrapper/status.svg)](https://david-dm.org/diegotremper/aws-serverless-restful-wrapper)
[![devDependencies Status](https://david-dm.org/diegotremper/aws-serverless-restful-wrapper/dev-status.svg)](https://david-dm.org/diegotremper/aws-serverless-restful-wrapper?type=dev)
[![Known Vulnerabilities](https://snyk.io/test/github/diegotremper/aws-serverless-restful-wrapper/badge.svg?targetFile=package.json)](https://snyk.io/test/github/diegotremper/aws-serverless-restful-wrapper?targetFile=package.json) [![Greenkeeper badge](https://badges.greenkeeper.io/diegotremper/aws-serverless-restful-wrapper.svg)](https://greenkeeper.io/)

## Install

```$ npm install aws-serverless-restful-wrapper```

## Features

* Support request validation with [@hapijs/joi](https://github.com/hapijs/joi)
* Support [RESTful](https://restfulapi.net/) principle
* Support [HATEOAS](https://restfulapi.net/hateoas/) principle

## Usage

### Fetch a single document

```GET /todos/{id}```

```javascript
const restful = require('aws-serverless-restful-wrapper')

module.exports.get = restful.document({
  target: async (path, query, headers) => {
    console.log('Returning todo')
    return {
      id: '123',
      text: 'My task',
      checked: true
    }
  }
})
```

### API Gateway Response:
```json
HTTP 200
Content-Type: 'application/json'

{
  "id": "123",
  "text": "My task",
  "checked": true
}
```

### Fetch a collection

```javascript
const restful = require('aws-serverless-restful-wrapper')

module.exports.get = restful.collection({
  target: async (path, query, headers) => {
    console.log('Returning todos')
    return [
      {
        id: '1',
        text: 'My task 1',
        checked: true
      },
      {
        id: '2',
        text: 'My task 2',
        checked: true
      }
    ]
  }
})
```

### API Gateway Response:

```json
HTTP 200
Content-Type: 'application/json'

[
  {
    "id": "1",
    "text": "My task 1",
    "checked": true
  },
  {
    "id": "2",
    "text": "My task 2",
    "checked": true
  }
]
```

### Using Joi validation

```javascript
const Joi = require('@hapi/joi')
const restful = require('aws-serverless-restful-wrapper')

module.exports.get = restful.document({
  validators: {
    path: Joi.object({
      id: Joi.string().required()
    })
  },
  target: async (path, query, headers) => {
    console.log('Returning todo')
    return {
      text: 'My task',
      checked: true
    }
  }
})
```

## Contributing

* Write docs
* Suggest a feature
* Submit PRs
  * Logging
  * Support for XML based REST
* [Write exemples](https://github.com/diegotremper/aws-serverless-restful-wrapper-examples)

## License

This source code is licensed under the MIT license found in
the [LICENSE.txt](https://github.com/diegotremper/aws-serverless-restful-wrapper/blob/master/LICENSE) file.


text:
#Services block
This block handles a content that describes the services your company offer. It provides two blocks:

- AgencyService
- AgencyServicesCollection

The AgencyService is the single service
The AgencyServicesCollection is a collection of AgencyService blocks

## Get the block
This block is included into the **redkitecms-plugins** library which is already bundled with RedKite CMS 2 since alpha 3 release. It is installed using composer, so add the library to your **composer.json** as follows:

    "require": {
       [...]
       "redkite-labs/redkitecms-plugins": "@dev",
    }

To get the library just run:

    php composer.phar update

## AgencyService Definition
Here it is the service definition:

    children:
      item1:
        children:
          item1:
            value: ''
            tags:
              class: 'fa fa-circle fa-stack-2x text-primary'
            type: Icon
          item2:
            value: ''
            tags:
              class: 'fa fa-shopping-cart fa-stack-1x fa-inverse'
            type: Icon
        tags:
          class: 'fa-stack fa-4x'
        type: IconStacked
        value: ''
    tags:
      class: col-md-4
    type: AgencyService
    service_title: 'Service title'
    service_description: 'Lorem ipsum dolor sit amet, consectetur adipisicing elit. Minima maxime quam architecto quo inventore harum ex magni, dicta impedit.'

The **children part** defines a [fontawesome stacked icon](http://fortawesome.github.io/Font-Awesome/examples/) you can easily customize changing the **item2** entry. For example, to display a bomb icon you would change that entry as follows:

    item2:
        value: ''
        tags:
          class: 'fa fa-bomb fa-stack-1x fa-inverse'
        type: Icon

To change the icon dimension your change the item class:

    tags:
        class: 'fa-stack fa-2x'

To change the block dimension just change the block class:

    children:
        [..]
        tags:
          class: col-md-6

Then, to change the title and the displayed text, just edit the **service_title** and **service_description** properties:

    service_title: 'E-Commerce'
    service_description: 'It is easy to sell your products from your website...'

## AgencyServicesCollection Definition

As explained at the beginning, This block collections AgencyService blocks, so you can edit them as explained above. To add a new item just click the button on the inline editor.


text:
## Testing with a proxy

Using a SUSE manager proxy with the testsuite is not mandatory.

If you do not want a proxy, do not define `$PROXY` environment variable
before you run the testsuite. That's all.

If you want a proxy, make this variable point to the machine that will be
the proxy:

```bash
export PROXY=myproxy.example.com
```

and then run the testsuite.

### With sumaform

Sumaform can prepare a proxy virtual machine and declare the `$PROXY`
variable on the controller (in `/root/.bashrc`).

For details on how to declare a proxy in your `main.tf` file,
refer to the "Proxies" chapter of the
[advanced instructions](https://github.com/moio/sumaform/blob/master/README_ADVANCED.md)
for sumaform.

repository: MalloZup/spacewalk-testsuite-base

repo_name: MalloZup/spacewalk-testsuite-base


text:
---
layout: post
title: The last 3 weeks in Krita Animation
---

Hello planet! Over the past few weeks I have been working on Krita Animation to make it more usable by adding essential animation features and fixing various loose ends. So here is an update on what has been done so far(Also this happens to be my first update on my Google Summer of Code, 2014 project).

**Fixed loading of animation layers**: Initially the animation layers did not load correctly. Only the first animation layer used to be loaded properly. And there were bugs with the layer box in the timeline GUI too. This has been fixed now.

[![Support for Multiple Animation Layers in Krita](https://img.youtube.com/vi/3VKcvJT8rQ8/0.jpg)](https://www.youtube.com/watch?v=3VKcvJT8rQ8)

**Auto frame breaking**: This feature is specifically helpful for animators who don’t like to click the buttons or use the keyboard for adding frames, but directly start drawing on a new frame after selecting the frame. There is an option to disable this feature as it might sometimes get in the way of the workflow. Also there is an option to either insert a blank frame or key frame on frame break. [Here](https://www.youtube.com/watch?v=zHun3tkrjJ8) is a video demonstrating auto frame breaking.

[![Auto Frame Breaking in Krita Animation](https://img.youtube.com/vi/zHun3tkrjJ8/0.jpg)](https://www.youtube.com/watch?v=zHun3tkrjJ8)

**Frame Navigation actions**: Actions for jumping to next and previous keyframes, next and previous frames have also been added with Keyboard shortcuts. This is specifically very helpful for animators who use keyboard to switch frames without clicking the buttons or using the timeline.

![Frame Navigation Actions](https://i.imgur.com/ERZnNTT.png)

**Changing the timeline width**: Added an option to change the timeline width according to the number of frames required in a particular animation.

![Changing the timeline width](https://i.imgur.com/D8OUZCt.png)

**Animation import**: Currently the animation frames and layers get imported in Krita Animation. But the timeline GUI doesn’t get updated accordingly.

**The Road Ahead**

These are the things I have been intending to add or fix in the next few days:

- The Onion skin Docker, which is a critical feature and is currently work in progress. There should be something substantial on this soon.
- Add code to make the timeline GUI refresh/update on its own during import, frame and layer deletion, etc.
- Frame and layer deletion, layer locking, moving frames and layers.
- Animation export to PNG sequences.
- Animation player and scrubbing, caching of probable frames(with some logic like locality of reference).
- …And lots of bug fixes :)

Also there have been some queries about how to test this stuff. So the only way to test it right now is by building from the source code after checking out the animation development branch, which is ‘animator-plugin-somsubhra’.
That is all I have for now. Thanks for reading!

Oh, and by the way Krita started its first donation campaign on Kickstarter to raise money for the 2.9 release and make it more awesome. Here is a direct link to the Kickstarter page: [https://www.kickstarter.com/projects/krita/krita-open-source-digital-painting-accelerate-deve](https://www.kickstarter.com/projects/krita/krita-open-source-digital-painting-accelerate-deve)

![Krita Kickstarter](http://3.bp.blogspot.com/-2FNKM4yhkL8/U5YTz32kjkI/AAAAAAAABvM/vpAUSGmgJz4/s1600/kickstarter_logo2.png)

gha_language: CSS

gha_license_id: NOASSERTION


text:
Node API for theVelops project

Node and express API that performs CRUD

Getting Started

Download the project and use the terminal to navigate to the designated folder. Type "npm start" to start the server on nodemon and visit http://localhost:3000/api-docs/ to see swagger's documentation.

Available methods:

get: http://localhost:3000/users

post: http://localhost:3000/users

 Example: {

  "email"<EMAIL_ADDRESS>  "first_name": "example",
  "last_name": "example",
  "personal_phone": "9999999",
  "password": "123",
}
get {id}: http://localhost:3000/users/{id}

put {id}: http://localhost:3000/users/{id}

delete {id}: http://localhost:3000/users/{id}

Database

The database being used is mongodb Atlas

Author

Bruno Sugahara

repository: BrunoSugahara/node-thevelops

repo_name: BrunoSugahara/node-thevelops