text:
@inproceedings{10.1145/3411763.3451520,
author = {Obukhova, Natalia},
title = {A Meta-Analysis of Effect Sizes of CHI Typing Experiments},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451520},
doi = {10.1145/3411763.3451520},
abstract = {While designing an HCI experiment, planning the sample size with a priori power analysis is often skipped due to the lack of reference effect sizes. On the one hand, it can lead to a false-negative result, missing the effect that is present in the population. On the other hand, it poses a risk of spending more resources if the number of participants is too high. In this work, I present the reference for small, medium, and large effect sizes for typing experiments based on a meta-analysis of well-cited papers from CHI conference. This effect size ruler can be used to conduct a priori power analysis or assess the magnitude of the found effect. This work also includes comparisons to other fields and conclude with a discussion of the existing issues with reporting practices and data availability. This paper and all data and materials are freely available at https://osf.io/nqzpr.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {476},
numpages = {7},
keywords = {experimental design, systematic review, text entry, controlled experiments, power analysis},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451517,
author = {Xia, Chengshuo},
title = {Optimal Sensor Position: Exploring the Interface Between the User and Sensor in Activity Recognition System},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451517},
doi = {10.1145/3411763.3451517},
abstract = {Human activity recognition systems combined with machine learning normally serve users based on the fixed sensor position. Uniform sensor position normally cannot satisfy the user’s demand according to different conditions. In this paper, we recognized the sensor position as an interface between the user and sensor system. We designed the optimization scheme to generate the best sensor position for activity recognition system. The user can indicate his/her preferred or disliked position and sensor numbers and the proposed optimization evaluates which position or positions combination can generate best accuracy under user’s preference. With the experiment, the proposed scheme can be employed to discover the optimal position to help the HAR system in a simple and customized way.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {487},
numpages = {5},
keywords = {sensor position, Activity recognition, interface, optimization},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451512,
author = {von Frankenberg, Nadine},
title = {Towards Resolving Thermal Comfort Conflicts in Shared Spaces},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451512},
doi = {10.1145/3411763.3451512},
abstract = {Thermal comfort is an important factor in building control, affecting occupant health, satisfaction, and productivity. Building management systems in commercial spaces commonly operate on predefined temperature setpoints and control strategies. Many systems target aggregated cohort comfort and neglect to consider the individual occupant’s thermal preferences, leading to high dissatisfaction rates. While recent studies focus on personalized comfort models, such systems mainly operate on occupant preference prediction and do not investigate the reasons for discomfort. This paper presents TREATI’s human-in-the-loop decision-making process. TREATI is a framework that targets thermal comfort conflict resolution in shared spaces using rationale management techniques while considering both individual and cohort comfort. TREATI uses several levels of abstraction separating device management, event processing, context, and rationale management. This separation allows users to adapt the framework to existing building management systems to provide fair decision-making.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {478},
numpages = {5},
keywords = {building control, IEQ, human-in-the-loop, rationale management},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451230,
author = {Fassl, Matthias and Gr\"{o}ber, Lea Theresa and Krombholz, Katharina},
title = {Stop the Consent Theater},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451230},
doi = {10.1145/3411763.3451230},
abstract = {The current web pesters visitors with consent notices that claim to “value” their privacy, thereby habituating them to accept all data practices. Users’ lacking comprehension of these practices voids any claim of informed consent. Market forces specifically designed these consent notices in their favor to increase users’ consent rates. Some sites even ignore users’ decisions entirely, which results in a mere theatrical performance of consent procedures designed to appear as if it fulfills legal requirements. Improving users’ online privacy cannot rely on individuals’ consent alone. We have to look for complementary approaches as well. Current online data practices are driven by powerful market forces whose interests oppose users’ privacy expectations – making turnkey solutions difficult. Nevertheless, we provide a bird’s-eye view on privacy-improving approaches beyond individuals’ consent.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {35},
numpages = {7},
keywords = {Surveillance Capitalism, Cookie Consent Notices, Online Behavioral Advertising},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450405,
author = {Hofmann, Megan and Bennett, Cynthia L and Feng, Jinjuan Heidi and Jain, Dhruv and Ladner, Richard and Mankoff, Jennifer},
title = {2021 SIG on Access in SIGCHI},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450405},
doi = {10.1145/3411763.3450405},
abstract = {Accessibility, diversity, and inclusion are key concerns for the CHI community. In 2019, Accessibility was one of the top keywords among conference publications. Despite the focus of research, many scholars with disabilities still struggle to access SIGCHI events and activities. At this SIG at CHI 2021, Access-SIGCHI, along with AccessComputing and SIGACCESS, will host an open discussion about the state of accessibility within SIGCHI and discuss opportunities for organizers and volunteers to improve accessibility. The event is open to all, but we are particularly excited to bring together people with disabilities and organizers from across SIGCHI to collaboratively develop a plan for increase access across all SIGCHI events.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {156},
numpages = {3},
keywords = {accessibility},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450401,
author = {Sturdee, Miriam and Lewis, Makayla and Spiel, Katta and Priego, Ernesto and Fern\'{a}ndez Camporro, Marina and Hoang, Thuong},
title = {SketCHI 4.0: Hands-On Special Interest Group on Remote Sketching in HCI},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450401},
doi = {10.1145/3411763.3450401},
abstract = {Sketching is a physical activity: moving a stylus to create marks on paper or screen, from mind to visual output. But sketching can also translate to the virtual space. When we sketch collaboratively, we look for cues, exchange ideas, and annotate work via mark-making or comment. The digital medium has evolved to explore the potentials of sketching online, and this Special Interest Group aims to bring together researchers and practitioners interested in Sketching in HCI to explore the new virtual landscape of sketching, popularised by the constraints of the current world situation. We invite you to join our virtual group, discuss and share sketches, query the existing state-of-the-art, and help pave the way for the development of this medium in the virtual space with your imagery and ideation.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {164},
numpages = {4},
keywords = {drawing, sketching, visualisation, collaboration, visual thinking},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450397,
author = {Rogers, Yvonne and Brereton, Margot and Dourish, Paul and Forlizzi, Jodi and Olivier, Patrick},
title = {The Dark Side of Interaction Design},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450397},
doi = {10.1145/3411763.3450397},
abstract = {This panel will provoke the audience into reflecting on the dark side of interaction design. It will ask what role the HCI community has played in the inception and rise of digital addiction, digital persuasion, data exploitation and dark patterns and what to do about this state of affairs. The panelists will present their views about what we have unleashed. They will examine how ‘stickiness’ came about and how we might give users control over their data that is sucked up in this process. Finally, they will be asked to consider the merits and prospects of an alternative agenda, that pushes for interaction design to be fairer, more ethically-grounded and more transparent, while at the same time addressing head-on the dark side of interaction design.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {152},
numpages = {2},
keywords = {digital addiction, dark patterns, nudging, data exploitation, Interaction Design, dark side},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450392,
author = {Cooney, Sarah},
title = {Riding the Bus in Los Angeles: Creating Cultural Micro-Exposures via Technology},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450392},
doi = {10.1145/3411763.3450392},
abstract = {The HCI community has largely failed to serve the millions of people in rural communities in the developed world. In part, I believe this is because our plural values do not match the more traditional, conservative values often found in rural communities. However, these rural communities, and in particular the marginalized populations within them, could greatly benefit from our work. I believe that one way to set the stage for deeper engagement with rural communities is by creating cultural micro-exposures—small brushes with the everyday realities of a culture or lived experience that is different from one’s own—using technology.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {13},
numpages = {9},
keywords = {cultural learning, rural HCI, cultural exchange, personal reflection, digital experiences},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450382,
author = {Tomlinson, Bill and Nardi, Bonnie and Stokols, Daniel and Raturi, Ankita},
title = {Ecosystemas: Representing Ecosystem Impacts in Design},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450382},
doi = {10.1145/3411763.3450382},
abstract = {Personas—distilled representations of particular user groups—are a key part of many design processes. Researchers have created animal personas to represent nonhuman animals as stakeholders in design efforts. However neither human nor animal personas allow for the representation of broader-scale ecological impacts in design decisions. To address this gap, we present an additional conceptual tool for design: the ecosystema. This design construct is analogous to a persona, but at the level of an entire ecosystem rather than of a particular human population or animal species. These constructs could allow ecosystem-wide impacts to influence design processes more effectively, and may provide greater leverage on current environmental crises than existing human-centered techniques.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {14},
numpages = {10},
keywords = {design, ecosystem, human-computer interaction, Sustainability, persona.},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450372,
author = {Lindley, Joseph and Sturdee, Miriam and Philip Green, David and Alter, Hayley},
title = {This is Not a Paper: Applying a Design Research Lens to Video Conferencing, Publication Formats, Eggs… and Other Things.},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450372},
doi = {10.1145/3411763.3450372},
abstract = {This is like an abstract to a paper, but it is more abstract. In fact, it is the introduction to something which is a not paper. The global Covid-19 pandemic of 2020 represented an inflection point for our post-post-modern world, a moment where our old normal was dramatically arrested. We are now in a state of comprehensive flux as ‘new normals’ emerge, begin to solidify, and may evolve into an—as yet undetermined—futures. This not paper is a facet and exploration of that flux as it relates to publication and conference culture, video conferencing systems, and how we both conduct, and share, research. You should read the whole of this abstract, but then you should take a step inside the not paper, it lives on the web over here https://designresearch.works/thisisnotapaper/},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {16},
numpages = {6},
keywords = {Gather Town, Alternative publication formats, Non-archival and non-linear rhetoric},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3450364,
author = {Howell, Noura and F. Schulte, Britta and Twigger Holroyd, Amy and Fat\'{a}s Arana, Roc\'{\i}o and Sharma, Sumita and Eden, Grace},
title = {Calling for a Plurality of Perspectives on Design Futuring: An Un-Manifesto},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3450364},
doi = {10.1145/3411763.3450364},
abstract = {The Futures Cone, a prominent model in design futuring, is useful for promoting discussions about possible, plausible, probable, and preferable futures. Yet this model has limitations, such as representing diverse human experiences as a singular point of “the present” and implicitly embedding notions of linear progress. Responding to this, we argue that a plurality of perspectives is needed to engage imaginations that depict a diverse unfolding of potential futures. Through reflecting on our own cultural and professional backgrounds, we offer five perspectives for design futuring as a contribution to this plurality: Parallel Presents, “I Am Time”, Epithelial Metaphors, the Uncertainties Cone, and Meet (with) “Speculation”. These perspectives open alternative approaches to design futuring, move outside prevalent notions of technological progress, and foreground interdependent, relational agencies.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {31},
numpages = {10},
keywords = {speculative design, design futuring, un-manifesto, discursive design, plurality},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3445004,
author = {Read, Janet and Gilutz, Shuli},
title = {Working with Children in HCI: Research, Design and Evaluation},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3445004},
doi = {10.1145/3411763.3445004},
abstract = {Child Computer Interaction is concerned with the research, design, and evaluation of interactive technologies for children. Whilst many aspects of general HCI can be applied into this field, there are important adaptations to be made when conducting work for and with children throughout all stages of the design cycle. This course overviews the main tools and techniques in use by the CCI community presented alongside examples and experiences from academia and industry. The course is hands on and provides highly useful checklists and tips to ensure children (and researchers and developers) get the most out of participation in HCI activities.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {144},
numpages = {3},
keywords = {Design, Ethics, Child Computer Interaction, Children, UX research, Evaluation, Research},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3445003,
author = {Palanque, Philippe},
title = {Introductory Course on Automation and Its Use for Interactive Systems Design and Engineering},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3445003},
doi = {10.1145/3411763.3445003},
abstract = {This course takes both a practical and theoretical approach to introduce the principles, methods and tools for automation. Examples are taken from industries that have been embedding automation in their systems for a long time (such as aviation, automotive, satellite ground segments …), but the main focus is on designing and assessing automation for interactive systems. Interactive hands-on exercise of how to "do it right", will be provided answering questions such as: How to add automation in interaction techniques to improve efficiency? How to migrate tasks towards automation to improve effectiveness? How to design usable automation at system, application and interaction levels? Is more automation always better? If not, when do we stop automating? And more....},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {147},
numpages = {4},
keywords = {Usability and Reliability of partly-autonomous systems, Automation, Interactive systems engineering, Interactive systems design},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3445000,
author = {Gall Krogh, Peter and Koskinen, Ilpo},
title = {Drifting by Intention – Four Epistemic Traditions in Constructive Design Research},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3445000},
doi = {10.1145/3411763.3445000},
abstract = {It is assumed that to appreciate a knowledge contribution in research-through-design, we all agree on what the act of designing is and should deliver in research. However, just from a glance at contributions in an HCI context, this is far from the case. The course is based on the book: Drifting by intention – four epistemic traditions in constructive design research authored by the instructors. It unpacks different ways of knowing in practice-based design and provides operational models and hands-on exercises applied on participants cases to help plan and articulate the contribution of design in each participant's individual research project.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {146},
numpages = {3},
keywords = {Constructive Design Research, Drifting, Research through Design, Epistemology},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3443452,
author = {Wang, Jennifer and Moulden, Angela},
title = {AI Trust Score: A User-Centered Approach to Building, Designing, and Measuring the Success of Intelligent Workplace Features},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3443452},
doi = {10.1145/3411763.3443452},
abstract = {This paper describes how to help product teams move increasingly towards responsible AI experiences by examining user trust within business contexts. We discuss the development, application, and validation of the AI Trust Score, which allows teams to measure the success of an AI feature from enterprise users’ perspectives. The Trust Score is a multi-dimensional metric which consists of several statements users respond to that inform their trust, including whether an AI feature helps with job efficiency and effectiveness and understanding how and when to use the feature for their job role. The metric, along with usability feedback, can be adapted to encourage UX-related conversations and actions within product or feature development processes.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {54},
numpages = {7},
keywords = {Artificial intelligence, measurement, methods, user experience},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3443424,
author = {Peng, Zhenhui},
title = {Designing and Evaluating Intelligent Agents’ Interaction Mechanisms for Assisting Human in High-Level Thinking Tasks},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3443424},
doi = {10.1145/3411763.3443424},
abstract = {In the twenty-first century, people need to learn and apply high-level thinking skills, such as decision-making, problem-solving, and critical thinking, in their daily lives. Traditionally when in need, people can get help from human assistants to complete these thinking tasks, yet, such human experts are not always accessible. Intelligent agents, such as physical robots and virtual chatbots, are promising alternatives to the human assistants in these tasks. My doctoral research focuses on designing intelligent agents to assist human users and evaluating the impact of their interaction mechanisms (i.e., way of behaving) on user experience. Specifically, my works surround this theme by proposing: 1) an anticipation-autonomy framework that models the service robot’s proactivity in decision-making support contexts (decision-making); 2) a bot assistant that helps users to solve the problem of writing poor-quality comments in online mental health communities either by assessing the writing performance or recommending writing examples (problem-solving); and 3) a chatbot in comparison to a non-conversational tool for facilitating people to read academic papers critically (critical thinking). My dissertation contributes to the design of intelligent agents for helping people in high-level thinking tasks and insights for developing appropriate interaction mechanisms for these agents in the future.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {70},
numpages = {6},
keywords = {Robot, Intelligent agents, Decision-making, Bot, Problem-solving, Critical thinking},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3441350,
author = {Dingler, Tilman and Tag, Benjamin and Lorenz-Spreen, Philipp and Vargo, Andrew W. and Knight, Simon and Lewandowsky, Stephan},
title = {Workshop on Technologies to Support Critical Thinking in an Age of Misinformation},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3441350},
doi = {10.1145/3411763.3441350},
abstract = {Serious concerns have been raised about social media’s and online news outlets’ contribution to a pandemic of misinformation. The sheer volume and tendency of misinformation to exploit people’s cognitive biases have eroded the public’s trust in media outlets, governmental institutions, and the democratic process. With Human-Computer Interaction being at the forefront of designing and developing user-facing computing systems, we bear special opportunities to address these issues and work on solutions to mitigate problems arising from misinformation. This workshop brings together designers, developers, and thinkers across disciplines to redefine computing systems by focusing on technologies and applications that instil and nurture critical thinking in their users. By focusing on the problem of misinformation and users’ cognitive security, this workshop will sketch out blueprints for systems and interfaces that contribute to advancing technology and media literacy, building critical thinking skills, and helping users telling fake from truth.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {105},
numpages = {5},
keywords = {Cognitive biases, Misinformation, Human-Computer Interaction},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3441333,
author = {Tachtler, Franziska and Aal, Konstantin and Ertl, Tanja and Diethei, Daniel and Niess, Jasmin and Khwaja, Mohammed and Talhouk, Reem and Vilaza, Giovanna Nunes and Lazem, Shaimaa and Singh, Aneesha and Barry, Marguerite and Wulf, Volker and Fitzpatrick, Geraldine},
title = {Artificially Intelligent Technology for the Margins: A Multidisciplinary Design Agenda},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3441333},
doi = {10.1145/3411763.3441333},
abstract = {There has been increasing interest in socially just use of Artificial Intelligence (AI) and Machine Learning (ML) in the development of technology that may be extended to marginalized people. However, the exploration of such technologies entails the development of an understanding of how they may increase and/or counter marginalization. The use of AI/ML algorithms can lead to several challenges, such as privacy and security concerns, biases, unfairness, and lack of cultural awareness, which especially affect marginalized people. This workshop will provide a forum to share experiences and challenges of developing AI/ML health and social wellbeing technologies with/for marginalized people and will work towards developing design methods to engage in the re-envisioning of AI/ML technologies for and with marginalized people. In doing so we will create cross-research area dialogues and collaborations. These discussions build a basis to (1) explore potential tools to support designing AI/ML systems with marginalized people, and (2) develop a design agenda for future research and AI/ML technology for and with marginalized people.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {86},
numpages = {7},
keywords = {Ethics, Marginalized people, Global South, Data, Privacy, ML, HCI4D, Security, ICT4D, AI},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3441332,
author = {Baldauf, Matthias and Fr\"{o}hlich, Peter and Sadeghian, Shadan and Palanque, Philippe and Roto, Virpi and Ju, Wendy and Baillie, Lynne and Tscheligi, Manfred},
title = {Automation Experience at the Workplace},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3441332},
doi = {10.1145/3411763.3441332},
abstract = {Automation is transforming traditional workplaces and work processes tremendously. While automated systems are no longer restricted to manufacturing environments but pervade various work domains in manifold appearances, automation initiatives and research are still driven from a technology and performance perspective. The goal of this workshop is to provide an interdisciplinary forum for automation-focused user experience research. It will bring together researchers and practitioners from different disciplines to create and transfer knowledge on automation experiences of skilled workers and professionals at workplaces across domains. In a keynote talk, participant presentations, and the group-wise drafting of research ideas, the workshop will address three recent main challenges: encountering workplace automation, collaborating as well as building meaningful relationships with workplace automation. The outcome of this workshop will be a research agenda consisting of ideas for promising future research on automation experiences at the workplace.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {89},
numpages = {6},
keywords = {human-automation collaboration, user experience, Automation},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3441313,
author = {Watson, Benjamin and Spjut, Josef and Kim, Joohwan and Listman, Jennifer and Kim, Sunjun and Wimmer, Raphael and Putrino, David and Lee, Byungjoo},
title = {Esports and High Performance HCI},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3441313},
doi = {10.1145/3411763.3441313},
abstract = {Competitive esports is a growing worldwide phenomenon now rivaling traditional sports, with over 450 million views and 1 billion US dollars in revenue each year. For comparison, Major League Baseball has 500 million views and $10 billion in revenue, FIFA Soccer 900 million and $1.6 billion. Despite this significant popularity, much of the world remains unaware of esports — and in particular, research on and for esports is still extremely scarce compared to esports’ impact and potential. The Esports and High Performance HCI (EHPHCI) workshop will begin addressing that research gap. In esports, athletes compete through the computer interface. Because this interface can make the difference between winning and losing, esports athletes are among the most expert computer interface users in the world, as other athletes are experts in using balls and shoes in traditional sports. The premise of this workshop is that people will apply esports technology broadly, improving performance in a wide range of human activity. The workshop will gather experts in engineering, human factors, psychology, design and the social and health sciences to discuss this deeply multidisciplinary enterprise.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {103},
numpages = {5},
keywords = {esports, expert users, expert interaction techniques},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3457783,
author = {Yang, Qian},
title = {SIGCHI Outstanding Dissertation Award: Profiling Artificial Intelligence as a Material for User Experience Design},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3457783},
doi = {10.1145/3411763.3457783},
abstract = {HCI has become especially interested in the promises and challenges of user experience of AI, such as user acceptance, human-agent teamwork, and accessibility. Less discussed, however, is that the field of HCI routinely grapples with such challenges; across the various technologies commonly referred to as AI (e.g., predictive modeling, computer vision, NLP), what shared characteristics made human-AI interaction appeared uniquely difficult to design in the first place? Synthesizing my hands-on design and research over the past six years, in my dissertation, I worked to articulate whether, why, and how human-AI interaction appears uniquely challenging to design with established HCI methods. In this extended abstract, I first describe a human-AI interaction design framework as an answer to this question. I then discuss one critical implication of this framework: Framing data-driven AI systems as living socio-technical systems that co-evolve with their users. I analogize this reframing to the shift from desktop computing to ubiquitous computing and outline the ethnographic, design, and technological research opportunities it reveals.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {8},
numpages = {3},
keywords = {sketching, artificial intelligence, prototyping., User experience},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451843,
author = {Schwartz, R.X. and Monge Roffarello, Alberto and De Russis, Luigi and Apostolellis, Panagiotis},
title = {Reducing Risk in Digital Self-Control Tools: Design Patterns and Prototype},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451843},
doi = {10.1145/3411763.3451843},
abstract = {Many users take advantage of digital self-control tools to self-regulate their device usage through interventions such as timers and lockout mechanisms. One of the major challenges faced by these tools is the user reacting against their self-imposed constraints and abandoning the tool. Although lower-risk interventions would reduce the likelihood of abandonment, previous research on digital self-control tools has left this area of study relatively unexplored. In response, this paper contributes two foundational principles relating risk and effectiveness; four widely applicable novel design patterns for reducing risk of abandonment of digital self-control tools (continuously variable interventions, anti-aging design, obligatory bundling of interventions, and intermediary control systems); and a prototype digital self-control tool that implements these four low-risk design patterns.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {334},
numpages = {7},
keywords = {digital behavior control intervention, DSCT, Digital self-control tool, digital wellbeing, online controlled experiment, design pattern, DBCI},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451839,
author = {Reichherzer, Carolin and Fraser, Jack and Rompapas, Damien Constantine and Billinghurst, Mark},
title = {SecondSight: A Framework for Cross-Device Augmented Reality Interfaces},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451839},
doi = {10.1145/3411763.3451839},
abstract = {This paper describes a modular framework developed to facilitate the design space exploration of cross-device Augmented Reality (AR) interfaces that combine an AR head-mounted display (HMD) with a smartphone. Currently, there is a growing interest in how AR HMDs can be used with smartphones to improve the user’s AR experience. In this work, we describe a framework that enables rapid prototyping and evaluation of an interface. Our system enables different modes of interaction, content placement, and simulated AR HMD field of view to assess which combination is best suited to inform future researchers on design recommendations. We provide examples of how the framework could be used to create sample applications, the types of the studies which could be supported, and example results from a simple pilot study.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {234},
numpages = {6},
keywords = {Augmented Reality, field of view, smartphone, interaction methods, cross-device interaction},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451832,
author = {Takeuchi, Yuichiro},
title = {Ninja Codes: Exploring Neural Generationof Discreet Visual Codes},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451832},
doi = {10.1145/3411763.3451832},
abstract = {In this paper we report the results of our early explorations regarding Ninja Codes, a new class of visual codes intended to be used in a variety of interactive applications including augmented reality, motion/gesture control, contactless data transfer, robotics, etc. By harnessing the power of adversarial examples, Ninja Codes can be rendered discreet, concealed to human eyes but easily recognizable to detectors based on deep neural networks. The paper will provide a high-level overview of Ninja Codes, and describe an initial, proof-of-concept implementation built on top of existing face detection software. We see this work as a promising step toward a new family of methods by which digital information can be seamlessly encoded into real-world objects and environments.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {224},
numpages = {6},
keywords = {Ninja Codes, neural network, visual codes, adversarial examples},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451829,
author = {Tran O'Leary, Jasper and Lee, Khang and Peek, Nadya},
title = {A Grammar of Digital Fabrication Machines},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451829},
doi = {10.1145/3411763.3451829},
abstract = {Digital fabrication tools for makers have increased access to manufacturing processes such as 3D printing and computer-controlled laser cutting or milling. Despite research advances in novel hardware and software tools for fabrication tasks, there is no formal way to reason about the fabrication machine itself. There is no standard format for representing the high-level features of machines and trade-offs between them; instead, this important information is relegated to folk knowledge. To make machine information explicit, we present Taxon, a machine specification language broad enough to represent many machines, while also allowing for enough expressivity to meaningfully compare and infer performance. We describe and detail the motivation behind the design of Taxon, as well as how Taxon programs compile to a simulation of physical machines. We discuss opportunities for future work in digital fabrication that requires a standard, formalized representation of machines.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {376},
numpages = {6},
keywords = {user interfaces, prototyping, programming languages, Digital fabrication},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451818,
author = {Qin, Fang and Cheng, Huai-Yu and Sneeringer, Rachel and Vlachostergiou, Maria and Acharya, Sampada and Liu, Haolin and Majidi, Carmel and Islam, Mohammad and Yao, Lining},
title = {ExoForm: Shape Memory and Self-Fusing Semi-Rigid Wearables},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451818},
doi = {10.1145/3411763.3451818},
abstract = {Semi-rigid and rigid structures have been utilized in many on-body applications including musculoskeletal support (e.g., braces and splints). However, most of these support structures are not very compliant, so effortless custom fitting becomes a unique design challenge. Furthermore, the weight and space needed to transport these structures impede adoption in mobile environments. Here, we introduce ExoForm, a compact, customizable, and semi-rigid wearable material system with self-fusing edges that can semi-autonomously assemble on-demand while providing integrated sensing, control, and mobility. We present a comprehensive and holistic engineering strategy that includes optimized material composition, computationally-guided design and fabrication, semi-autonomous self-morphing assembly and fusing steps, heating control, and sensing for our easy-to-wear ExoForm. Finally, we fabricate wearable braces using the ExoForm method as a demonstration along with preliminary evaluation of ExoForm's performance.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {249},
numpages = {8},
keywords = {4D printing, Shape change, Tangible interaction, Semi-rigid wearables, Personal fabrication},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451813,
author = {Rahman, Jessica Sharmin and Gedeon, Tom and Caldwell, Sabrina and Jones, Richard L},
title = {Can Binaural Beats Increase Your Focus? Exploring the Effects of Music in Participants’ Conscious and Brain Activity Responses},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451813},
doi = {10.1145/3411763.3451813},
abstract = {Music is a universal medium that can elicit strong emotion, and can significantly help us in gaining focus while doing specific tasks. However, it is unclear what types of music can help to improve focus while doing other activities. In this paper, we investigate the effects of six different music stimuli on participants’ verbal and physiological responses while identifying genuine and acted emotions from video clips. Initial analysis was conducted on the comments participants made on the different stimuli in order to identify emerging patterns. Then, participants’ verbal and EEG responses were collected, processed and analyzed to classify two types of emotion. Empirical analysis of the results show that binaural beats, which are believed to increase focus on tasks, can often cause discomfort and therefore hinder focus. On the other hand, music containing a sombre tone, or familiar popular music with high level valence can help improve focus. Identifying which music stimuli can improve focus can be highly beneficial in managing day-to-day tasks and activities. This study will also be useful in broadening the range of music stimuli used in affective computing studies.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {349},
numpages = {6},
keywords = {EEG, Physiological Signals, Affective Computing, Classification, Music Stimuli, Binaural Beats, Emotion Recognition},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451801,
author = {Chen, Si and Wang, Dennis and Huang, Yun},
title = {Exploring the Complementary Features of Audio and Text Notes for Video-Based Learning in Mobile Settings},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451801},
doi = {10.1145/3411763.3451801},
abstract = {In this paper, we compared audio and text note-taking behaviors for video-based learning in various mobile settings. We designed and implemented a note-taking tool and conducted a task-based study to examine how users took audio and text notes differently. Our results show that participants’ audio notes were significantly longer than text notes; longer audio notes were taken to capture unfamiliar video content and participants’ emotions. However, audio notes also raised several privacy concerns. Text notes allowed participants to revise for better accuracy and deeper reflection. Our findings of the complementary features of audio and text notes for video-based learning shed light on designing future note-taking tools that can be used to facilitate learning in varied mobile settings.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {310},
numpages = {7},
keywords = {Audio interaction, Note-taking, Mixed-method study},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451798,
author = {Shen, Haifeng and Liao, Kewen and Liao, Zhibin and Doornberg, Job and Qiao, Maoying and van den Hengel, Anton and Verjans, Johan W.},
title = {Human-AI Interactive and Continuous Sensemaking: A Case Study of Image Classification Using Scribble Attention Maps},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451798},
doi = {10.1145/3411763.3451798},
abstract = {Advances in Artificial Intelligence (AI), especially the stunning achievements of Deep Learning (DL) in recent years, have shown AI/DL models possess remarkable understanding towards the logic reasoning behind the solved tasks. However, human understanding towards what knowledge is captured by deep neural networks is still elementary and this has a detrimental effect on human’s trust in the decisions made by AI systems. Explainable AI (XAI) is a hot topic in both AI and HCI communities in order to open up the blackbox to elucidate the reasoning processes of AI algorithms in such a way that makes sense to humans. However, XAI is only half of human-AI interaction and research on the other half - human’s feedback on AI explanations together with AI making sense of the feedback - is generally lacking. Human cognition is also a blackbox to AI and effective human-AI interaction requires unveiling both blackboxes to each other for mutual sensemaking. The main contribution of this paper is a conceptual framework for supporting effective human-AI interaction, referred to as interactive and continuous sensemaking (HAICS). We further implement this framework in an image classification application using deep Convolutional Neural Network (CNN) classifiers as a browser-based tool that displays network attention maps to the human for explainability and collects human’s feedback in the form of scribble annotations overlaid onto the maps. Experimental results using a real-world dataset has shown significant improvement of classification accuracy (the AI performance) with the HAICS framework.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {290},
numpages = {8},
keywords = {attention map, image classification, explainable AI, scribble interaction, interactive sensemaking},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451792,
author = {Arce-Lopera, Carlos and Ospina, Rafael and Daniela Victoria, Maria},
title = {Augmented Reality Game for Brand Recognition and Recall: AR for Brand Recognition and Recall},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451792},
doi = {10.1145/3411763.3451792},
abstract = {Augmented Reality (AR) technology offers the opportunity to change the customer experience in the retail context. For example, AR applications can be used as a bridge to close the gap between physical and online shops, mixing the best characteristics of both. Different researchers have measured the quality of the user's experience through AR. However, here we focused not only on user experience but also on the impact of AR on brand recall and recognition. We analyzed the impact on brand recall and recognition of an AR application by comparing three contexts: a traditional context where participants look at three products, a focused context where participants have only one product to look at, and a technology-enhanced context where participants interacted with the product using the designed AR experience. Experimental results revealed that AR improved brand recall and recognition by creating an engaging environment. Moreover, participants in the AR context recalled additional information about the product. Also, the AR experience motivated them to participate in an omnichannel activity based on a QR interaction. These results show the influence of well-designed AR experiences on brand recall and recognition opening the possibility for new technology in retail environments.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {382},
numpages = {5},
keywords = {Customer experience, Augmented Reality, Brand Recognition, Brand Recall, Omnichannel, QR, Technology in Retail},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451791,
author = {St\"{o}ver, Alina and Gerber, Nina and Kaushik, Sushma and M\"{u}hlh\"{a}user, Max and Marky, Karola},
title = {Investigating Simple Privacy Indicators for Supporting Users When Installing New Mobile Apps},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451791},
doi = {10.1145/3411763.3451791},
abstract = {Mobile devices have become daily companions for millions of users. They have access to privacy-sensitive data about their users which stresses the importance of privacy. Users have to make privacy-related decisions already before app installation because once installed, apps can access potential privacy-sensitive data. In this work-in-progress, we present an in-depth investigation of privacy indicator visualizations for mobile app stores. We report the results of two consecutive user studies in which we investigate 1) visual depiction, 2) score, and 3) monetary value of collected data. Our studies reveal that a visual depiction by a privacy meter were easiest to understand for users, scores were easiest to spot, and monetary value was most difficult to interpret and requires further investigation.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {366},
numpages = {7},
keywords = {privacy indicator, information privacy, mobile privacy},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451785,
author = {Zhang, Chao and Yao, Cheng and Liu, Jianhui and Zhou, Zili and Zhang, Weilin and Liu, Lijuan and Ying, Fangtian and Zhao, Yijun and Wang, Guanyun},
title = {StoryDrawer: A Co-Creative Agent Supporting Children's Storytelling through Collaborative Drawing},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451785},
doi = {10.1145/3411763.3451785},
abstract = {Storytelling is a common creative activity for children. During storytelling, children need creative support and are subjected to cognitive challenges. This paper explores a co-creative agent - StoryDrawer, which supports children in creating oral stories through collaborative drawing. StoryDrawer works with children in two strategies: Child says and AI draws; and Child scribbles and AI completes. These two collaborative strategies allow children to draw their stories as an externalization and provoke unexpected ideas. This paper presents the interaction design, collaborative strategies and implementation of StoryDrawer, and conducts a user study for the fun and task effectiveness of StoryDrawer. The results reveal that our system can encourage children's active participation in storytelling and help them create novel stories through human-computer collaboration.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {354},
numpages = {6},
keywords = {Creativity support tool, Human-AI collaboration, Oral expression, Children, Storytelling, Co-creative system},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451784,
author = {de Belen, Ryan Anthony Jalova and Bednarz, Tomasz and Sowmya, Arcot},
title = {EyeXplain Autism: Interactive System for Eye Tracking Data Analysis and Deep Neural Network Interpretation for Autism Spectrum Disorder Diagnosis},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451784},
doi = {10.1145/3411763.3451784},
abstract = {Over the past decade, Deep Neural Networks (DNN) applied to eye tracking data have seen tremendous progress in their ability to perform Autism Spectrum Disorder (ASD) diagnosis. Despite their promising accuracy, DNNs are often seen as ’black boxes’ by physicians unfamiliar with the technology. In this paper, we present EyeXplain Autism, an interactive system that enables physicians to analyse eye tracking data, perform automated diagnosis and interpret DNN predictions. Here we discuss the design, development and sample scenario to illustrate the potential of our system to aid in ASD diagnosis. Unlike existing eye tracking software, our system combines traditional eye tracking visualisation and analysis tools with a data-driven knowledge to enhance medical decision-making for physicians.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {364},
numpages = {7},
keywords = {Autism Diagnosis, Eye Tracking, Visualization, Deep Neural Network, Explainable AI},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451783,
author = {Seaborn, Katie and Pennefather, Peter and Miyake, Norihisa and Otake-Matsuura, Mihoko},
title = {Crossing the Tepper Line: An Emerging Ontology for Describing the Dynamic Sociality of Embodied AI},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451783},
doi = {10.1145/3411763.3451783},
abstract = {Artificial intelligences (AI) are increasingly being embodied and embedded in the world to carry out tasks and support decision-making with and for people. Robots, recommender systems, voice assistants, virtual humans—do these disparate types of embodied AI have something in common? Here we show how they can manifest as “socially embodied AI.” We define this as the state that embodied AI “circumstantially” take on within interactive contexts when perceived as both social and agentic by people. We offer a working ontology that describes how embodied AI can dynamically transition into socially embodied AI. We propose an ontological heuristic for describing the threshold: the Tepper line. We reinforce our theoretical work with expert insights from a card sort workshop. We end with two case studies to illustrate the dynamic and contextual nature of this heuristic.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {281},
numpages = {6},
keywords = {Ontology, Artificial agents, Social embodiment, Social perceptions, AI},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451778,
author = {de Wit, Jan},
title = {A Unified Model of Game Design, Through the Lens of User Experience},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451778},
doi = {10.1145/3411763.3451778},
abstract = {In this paper, two cornerstone game design and research models — the Mechanics, Dynamics, Aesthetics framework and the magic circle — are revisited and inspected through a lens of user experience design. This suggests two aspects that are missing from these models: a clear distinction between the intended and actual player experience, and the inclusion of transfer of knowledge, actions, and emotions between the game world and the real world, as part of the player experience. Based on these observations, a new unified model is proposed.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {255},
numpages = {6},
keywords = {game analysis, game design, game user experience},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451766,
author = {Rettinger, Maximilian and M\"{u}ller, Niklas and Holzmann-Littig, Christopher and Wijnen-Meijer, Marjo and Rigoll, Gerhard and Schmaderer, Christoph},
title = {VR-Based Equipment Training for Health Professionals},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451766},
doi = {10.1145/3411763.3451766},
abstract = {It is common knowledge that health professionals’ device training is a major problem, as the inadequate quality of device training puts patients at risk [2]. To find a way to counter this problem, we propose a virtual reality training simulation. The corresponding use case is exemplified by a priming procedure of a dialysis machine. This is achieved by users going through sequential interaction tasks in Virtual Reality Training using a head-mounted display. We evaluate this training method’s potential within a user study, comparing it to traditional training methods, Group Training, and Video Training. Our findings demonstrate that Virtual Reality Training using a head-mounted display is a more effective and efficient method of learning how to prime a dialysis machine. Compared to other training methods, Virtual Reality Training takes longer on average, but the resulting learning effect is also higher. Furthermore, VR-training is more cost-effective than personal training and can be repeatedly performed as it dispenses with the need for teaching professionals.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {252},
numpages = {6},
keywords = {User Studies, Virtual Reality, Medical Training, Dialysis, Equipment Training, Instruction Manual, VR},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451759,
author = {Mucha, Henrik and Robert, Sebastian and Breitschwerdt, Ruediger and Fellmann, Michael},
title = {Interfaces for Explanations in Human-AI Interaction: Proposing a Design Evaluation Approach},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451759},
doi = {10.1145/3411763.3451759},
abstract = {Explanations in Human-AI Interaction are communicated to human decision makers through interfaces. Yet, it is not clear what consequences the exact representation of such explanations as part of decision support systems (DSS) and working on machine learning (ML) models has on human decision making. We observe a need for research methods that allow for measuring the effect different eXplainable AI (XAI) interface designs have on people’s decision making. In this paper, we argue for adopting research approaches from decision theory for HCI research on XAI interface design. We outline how we used estimation tasks in human-grounded design research in order to introduce a method and measurement for collecting evidence on XAI interface effects. To this end, we investigated representations of LIME explanations in an estimation task online study as proof-of-concept for our proposal.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {327},
numpages = {6},
keywords = {Explainable Artificial Intelligence (XAI), Explanatory User Interfaces, Human-AI Interaction},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451754,
author = {Song, Sichao and Baba, Jun and Nakanishi, Junya and Yoshikawa, Yuichiro and Ishiguro, Hiroshi},
title = {Teleoperated Robot Sells Toothbrush in a Shopping Mall: A Field Study},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451754},
doi = {10.1145/3411763.3451754},
abstract = {Social robots have been used to provide services in many public spaces. However, many of them are autonomous robots that have poor natural language conversation skills. It is considered a difficult task for an autonomous robot to be a salesperson. In this paper, we propose the use of a teleoperated robot with a human operator for sales purposes. We conducted an exploratory field experiment in which we built a sales booth in a shopping mall and used our teleoperated robot as the salesperson to promote the sales of toothbrushes. We found that our robot has the ability to attract people’s attention and influence their shopping behavior. Furthermore, we discuss the research challenges in designing and applying teleoperated robots to real sales situations.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {221},
numpages = {6},
keywords = {teleoperated robot, conversation, field study, sales, human-robot interaction},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451748,
author = {Kapler, Thomas and W. S. Gray, Derek and Marie Vasquez, Holland and Wright, William},
title = {Causeworks Collaboration: Simultaneous Causal Model Construction and Analysis},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451748},
doi = {10.1145/3411763.3451748},
abstract = {Military planners use “Operational Design” (OD) methods to develop an understanding of systems and relationships in complex operational environments. Here, we present Causeworks, a visual analytics application for OD teams to collaboratively build causal models of environments and use analytics to understand and find solutions to affect them. Collaborative causal modelling can help teams craft better plans, but there are unique challenges in developing synchronous collaboration tools for building and using causal models. Collaboration systems typically organize information around varying degrees of synchronization between data “values” and user “views.” Our contribution is in extending this collaboration framework to include analytics as layers that are by nature derived from the data values but utilized and displayed temporarily as private views. We describe how Causeworks overlays analytics inputs and outputs over a shared causal model to flexibly support multiple modeling tasks simultaneously in a collaborative environment with minimal state management burden on users.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {461},
numpages = {6},
keywords = {Collaborative and social computing, Collaborative visualizations},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451737,
author = {Ohshima, Hiroyuki and Kobayashi, Makoto and Shimada, Shigenobu},
title = {Development of Blind Football Play-by-Play System for Visually Impaired Spectators: Tangible Sports},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451737},
doi = {10.1145/3411763.3451737},
abstract = {In the field of sports, visually impaired spectators are unfortunately at a disadvantage in terms of understanding the precise developments of a game. To provide such information to them, making play-by-play announcements of the live coverage of the game is the best approach; however, this is infeasible as it is difficult to employ a professional commentator for every game. Therefore, this study proposes a blind football play-by-play system, combining a tactile graphic display function and a position acquisition function, to aid visually impaired spectators understand game developments. To conduct a basic study, an experimental system was developed herein, which detects the positions of the players and ball using image processing technology and deep learning, and shows these positions via a refreshable tactile display. The validity of the proposed system was then established through subjective experiments. This system provides a rich user experience to the spectators as well as being a powerful feedback tool to the players. Moreover, an audio–tactile graphic system, which can be used to overcome tactile cognitive limitations, can be implemented as an application of the system in the future.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {209},
numpages = {6},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451735,
author = {Chen, Jin and Chen, Cheng and B. Walther, Joseph and Sundar, S. Shyam},
title = {Do You Feel Special When an AI Doctor Remembers You? Individuation Effects of AI vs. Human Doctors on User Experience},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451735},
doi = {10.1145/3411763.3451735},
abstract = {You may feel special and believe that you are getting personalized care when your doctor remembers your name and your unique medical history. But, what if it is an AI doctor and not human? Since AI systems are driven by personalization algorithms, it is possible to design AI doctors that can individuate patients with great precision. Is this appreciated or perceived as eerie and intrusive, thereby negatively affecting doctor-patient interaction? We decided to find out by designing a healthcare chatbot that identified itself as AI, Human, or Human assisted by AI. In a user study assessing Covid-19 risk, participants interacted twice, 10 days apart, with a bot that either individuated them or not. Data show that individuation by an AI doctor lowers patient compliance. Surprisingly, a majority of participants in the human doctor condition thought that they chatted with an AI doctor. Findings provide implications for design of healthcare chat applications.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {299},
numpages = {7},
keywords = {AI resistance, Healthcare chatbot, Artificial intelligence, Individuation},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451733,
author = {Zhang, Zeyuan and Qin, Ling},
title = {InterRings: Towards Understanding Design Micro-Games to Fit Daily Work Routine},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451733},
doi = {10.1145/3411763.3451733},
abstract = {Prior game researchers mostly focused on designing the ”macro” context which requires a decent proportion of time to engage and play, from which players may benefit. However, the demanding time and effort restrict playability during working hours. To our knowledge, there is little research exploring game design in a manner that enables momentary detachment from primary work for a mind refreshment and effortlessly resumes the suspended work after playing. In this paper, we propose a novel micro-game concept that enables the gamification of micro-breaks within working hours. To examine our concept, we adapted a conventional water-ring game into an interactive prototype, InterRings, which empowers users to play with handy objects. Our mixed observational studies and interviews revealed high acceptability and feasibility of the micro-game concept. Conclusively, three design guidelines are summarised for future development of micro-games.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {345},
numpages = {6},
keywords = {Multi-tasking, Micro-games, Workplace Well-being, Ubiquitous Computing},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451730,
author = {Shakeri, Hanieh and Neustaedter, Carman},
title = {Painting Portals: Connecting Homes through Live Paintings},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451730},
doi = {10.1145/3411763.3451730},
abstract = {Feeling co-present and connected over distance is a challenge. To create a sense of sharing a space over distance and being together in the periphery of daily life, we designed and implemented a pair of connected picture frames that display paintings generated from live camera streams. These paintings are abstracted based on the distance of the user from the device, and are sent between two portals that can be placed anywhere in the world. We deployed the Painting Portals during a week-long field study investigating how a distance-separated mother and daughter experienced the use of the Painting Portals. We generated recommendations for future design and research, including: (1) stylizing the paintings in a way that better captures emotion/sentiment, (2) placing multiple Painting Portals in different common areas throughout a home, (3) incorporating a video call feature into the Painting Portals, and (4) adding the option to turn off one’s camera for more privacy.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {367},
numpages = {6},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451726,
author = {Tekler, Zeynep Duygu and Low, Raymond and Choo, Kenny Tsu Wei and Blessing, Lucienne},
title = {User Perceptions and Adoption of Plug Load Management Systems in the Workplace},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451726},
doi = {10.1145/3411763.3451726},
abstract = {Smart energy management systems incorporate advanced sensing and control technologies that enable users to monitor and reduce their energy consumption through interactive visualisations and automated control features. Plug load management systems (PLMS), in particular, are applications of such systems targeting electrical devices found in homes and workplaces. While past studies have mostly focused on PLMS adoption in homes, past literature indicates several key differences in user motivation as office users typically do not bear the cost of their consumption. This reduces their motivation to embrace such systems, resulting in low adoption rates. In our research, we examined user perception of adopting PLMS in the workplace through a series of focus group discussions and an online survey guided by findings from the focus group discussions. By analysing the quantitative and qualitative responses from 101 participants, we identified six design implications to guide the development of future PLMS in the workplace.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {213},
numpages = {6},
keywords = {Plug Loads, Office Equipment, Smart Energy Management Systems, Office Workplace},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451712,
author = {Seaborn, Katie and Urakami, Jacqueline},
title = {Measuring Voice UX Quantitatively: A Rapid Review},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451712},
doi = {10.1145/3411763.3451712},
abstract = {Computer voice is experiencing a renaissance through the growing popularity of voice-based interfaces, agents, and environments. Yet, how to measure the user experience (UX) of voice-based systems remains an open and urgent question, especially given that their form factors and interaction styles tend to be non-visual, intangible, and often considered disembodied or “body-less.” As a first step, we surveyed the ACM and IEEE literatures to determine which quantitative measures and measurements have been deemed important for voice UX. Our findings show that there is little consensus, even with similar situations and systems, as well as an overreliance on lab work and unvalidated scales. In response, we offer two high-level descriptive frameworks for guiding future research, developing standardized instruments, and informing ongoing review work. Our work highlights the current strengths and weaknesses of voice UX research and charts a path towards measuring voice UX in a more comprehensive way.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {416},
numpages = {8},
keywords = {voice user experience, voice agents, voice assistants, Voice user interfaces},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451706,
author = {Thach, Kong Saoane and Lederman, Reeva and Waycott, Jenny},
title = {Guidelines for Developing the VR Program in Residential Aged Care: A Preliminary Study from Staff Members’ Perspective},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451706},
doi = {10.1145/3411763.3451706},
abstract = {Despite there being evident benefits of using virtual reality (VR) in aged care, it is not yet widely used in residential aged care homes. One factor that may contribute to this is the willingness of staff to use VR as part of the social program offered in aged care homes. Therefore, we need to understand staff perceptions of VR programs, especially suggestions for improvement. In an analysis of responses from 10 staff working in residential aged care (also known as nursing homes), we found that staff have concerns about the suitability of VR for older people with cognitive impairments and mobility restrictions. Many older adults living in aged care have these conditions. Our findings suggest that providing staff with training on how to facilitate various kinds of valuable VR experiences and providing a clear picture of its benefits and drawbacks will help to make it suitable for people living in aged care. Furthermore, there should be greater investment in technological infrastructure and co-design of VR in aged care.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {423},
numpages = {6},
keywords = {technology adoption, older adults, Virtual reality, residential aged care},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451677,
author = {Xia, Chengshuo and Sugiura, Yuta},
title = {From Virtual to Real World: Applying Animation to Design the Activity Recognition System},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451677},
doi = {10.1145/3411763.3451677},
abstract = {Following the conventional pipeline, the training dataset of a human activity recognition system relies on the detection of the significant signal variation regions. Such position-specific classifiers provide less flexibility for users to alter the sensor positions. In this paper, we proposed to employ the simulated sensor to generate the corresponding signal from human motion animation as the dataset. Visualizing the corresponding items from the real world, the user can determine the sensor’s placement arbitrarily and obtain accuracy feedback as well as the classifier interface to get relief from the cost of a conventional training model. With the cases validation, the classifier trained by simulated sensor data can effectively recognize the real-world activity.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {216},
numpages = {6},
keywords = {Activity recognition, Sensor simulation, Machine learning},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451674,
author = {Nurain, Novia and Caldeira, Clara and Connelly, Kay},
title = {Older Adults’ Experiences of Autonomy During COVID-19 Pandemic},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451674},
doi = {10.1145/3411763.3451674},
abstract = {A sense of autonomy is important to ensure a good quality of life for older adults. However, the recent COVID-19 pandemic challenged older adults’ autonomy. The government has imposed rules and regulations to slow down the spread of the virus that reduced older adults’ abilities to go outside. We conducted semi-structured interviews with 15 older adults living alone in community-dwellings to understand the influence of the pandemic on their experiences of autonomy. Our findings show that even though older adults experienced limited autonomy due to extrinsic (e.g., government regulation, influence of others) and intrinsic (e.g., risk perception) factors, they experienced new opportunities for autonomy through engagement in various self-chosen activities at home. The insights from the study pave ways for future research and design of aging in place technology focusing on providing a sense of autonomy.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {250},
numpages = {6},
keywords = {pandemic, autonomy, older adults},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451667,
author = {Griswold-Steiner, Isaac and Diarrassouba, N'godjigui and Arangath, Shreyesh and Serwadda, Abdul},
title = {User Perceptions of Defensive Techniques Against Keystroke Timing Attacks During Password Entry},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451667},
doi = {10.1145/3411763.3451667},
abstract = {To protect the password from visual attacks, most password entry screens use a password masking scheme that displays a series of placeholder characters (e.g., dots and asterisks) instead of the actual password. Recent research has however shown the security provided by this form of password masking to be weak against keystroke timing-analytics attacks. The underlying idea behind these attacks is that, even when a password is masked as described above, the timing between consecutive placeholder characters gives away information about the password since the relative locations of characters on the keyboard dictate how fast fingers move between them. In this paper we argue that, for security-sensitive applications, password masking mechanisms ought to hide the true intervals between password characters in order to overcome these kinds of attacks. Making adjustments to these timings however has the potential to pose usability issues given the fact that the typing would not perfectly align with the display of typed content. The paper proposes 3 different password masking schemes and undertakes a usability evaluation on them. Our early results suggest that user receptiveness to two of the schemes is not much worse than that seen with the conventional (insecure) scheme.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {244},
numpages = {6},
keywords = {password usability, shoulder surfing, keystroke timing attacks, Password security},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

@inproceedings{10.1145/3411763.3451655,
author = {Kronester, Michael Julian and Riener, Andreas and Babic, Teo},
title = {Potential of Wrist-Worn Vibrotactile Feedback to Enhance the Perception of Virtual Objects during Mid-Air Gestures},
year = {2021},
isbn = {9781450380959},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411763.3451655},
doi = {10.1145/3411763.3451655},
abstract = {Numerous systems based on mid-air gestures have recently been proposed as a digital variant of object manipulation with hands. Simultaneously, however, direct haptic feedback is lost, eliminating an important aspect that we are familiar with from real-life interaction. We believe that smartwatches, as widely used personal devices, could provide a platform for accessible, flexible, and unobtrusive integration of haptic feedback into mid-air gesture interaction. We prototyped a vibrotactile wrist band with four vibration actuators aiming at communicating invisible, undetectable virtual object properties such as electricity, weight, and tension into 3D haptic experiences. In this paper, we present findings from a user study (n=18) that examined the suitability of different vibration patterns (variation in intensity, temporal profile, rhythm, and location). Results show that all feedback variants have a positive impact on user experience (UX) when interacting with virtual objects. Constant, continuous patterns outweigh the other variants examined.},
booktitle = {Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {256},
numpages = {7},
keywords = {Haptic perception, Vibrotactile feedback, Usability/UX studies, Multimodal interaction.},
location = {Yokohama, Japan},
series = {CHI EA '21}
}

repository: HighTemplar-wjiang/Crawlers

path: /ACM-Crawler/download/acm (53).bib

repo_name: HighTemplar-wjiang/Crawlers

filename: acm (53).bib


text:
package lru

import (
	"fmt"
	"time"

	"stathat.com/c/consistent"
)

// ShardedLRU is a LRU with keys split across shards for better performance
type ShardedLRU struct {
	shards map[string]*LRU
	ch     *consistent.Consistent
}

// New returns a new ShardedLRU with a up to a max of one Gigabyte of memory usage
func New() *ShardedLRU {
	return NewSharded(3<<30, Gigabyte, 256)
}

// NewSharded returns a new sharded LRU cache with a maximum in-memory size of maxSize,
// and total maxEntries spread over shardCt
func NewSharded(maxSize uint64, maxEntries uint64, shardCt uint64) *ShardedLRU {

	l := int(shardCt)
	shardSize := maxSize / shardCt
	shardEntries := maxEntries / shardCt

	var k string
	c := ShardedLRU{make(map[string]*LRU), consistent.New()}
	for i := 0; i < l; i++ {
		k = fmt.Sprintf("shard-%2d", i)
		c.ch.Add(k)
		c.shards[k] = NewBasic(shardSize, int(shardEntries))
	}

	return &c
}

func (c *ShardedLRU) find(key string) *LRU {
	nm, _ := c.ch.Get(key)
	return c.shards[nm]
}

// CompareAndSwap writes the given item that was previously returned by Get,
// if the value was neither modified or evicted between the Get and the
// CompareAndSwap calls. The item's Key should not change between calls but
// all other item fields may differ. ErrCASConflict is returned if the value
//  was modified in between the calls. ErrNotStored is returned if the value
// was evicted in between the calls.
func (c *ShardedLRU) CompareAndSwap(key string, value interface{}, exp time.Duration, cas uint64) (err error) {
	return c.find(key).CompareAndSwap(key, value, exp, cas)
}

// SetItem sets the item with the given parameters. Use it if you need to specifiy the cas id
// for future CompareAndSwap actions. Otherwise it's easier to just use Set() instead.
func (c *ShardedLRU) SetItem(key string, value interface{}, exp time.Duration, cas uint64) (err error) {
	return c.find(key).SetItem(key, value, exp, cas)
}

// Set sets the key/value pair
func (c *ShardedLRU) Set(key string, value interface{}, exp time.Duration) (err error) {
	return c.find(key).Set(key, value, exp)
}

// GetItem is similar to Get() only it returns the items unique CAS identifier
func (c *ShardedLRU) GetItem(key string, dstVal interface{}) (cas uint64, err error) {
	return c.find(key).GetItem(key, dstVal)
}

// Get fetches the key into the dstVal. It returns an error if the value doesn't exist.
func (c *ShardedLRU) Get(key string, dstVal interface{}) (err error) {
	return c.find(key).Get(key, dstVal)
}

// Del removes the key from the cache
func (c *ShardedLRU) Del(key string) (err error) {
	return c.find(key).Del(key)
}

// Exists returns true if the given key exists
func (c *ShardedLRU) Exists(key string) bool {
	return c.find(key).Exists(key)
}

// Touch updates the expiry for the given key
func (c *ShardedLRU) Touch(key string, exp time.Duration) (err error) {
	return c.find(key).Touch(key, exp)
}

// Add adds the value to cache, but only if the key doesn't already exist.
func (c *ShardedLRU) Add(key string, value interface{}, exp time.Duration) (err error) {
	return c.find(key).Add(key, value, exp)
}

// Replace replaces the current value for the key with the new value, but only
// if the key already exists. The expiration remains the same.
func (c *ShardedLRU) Replace(key string, value interface{}) (err error) {
	return c.find(key).Replace(key, value)
}

// Increment increases the key's value by delta. The exipration remains the same.
// The existing value must be a uint64 or a pointer to a uint64
func (c *ShardedLRU) Increment(key string, delta uint64) (uint64, error) {
	return c.find(key).Increment(key, delta)
}

// Decrement decreases the key's value by delta. The expiration remains the same.
// The underlying value to increment must be a uint64 or pointer to a uint64.
func (c *ShardedLRU) Decrement(key string, delta uint64) (uint64, error) {
	return c.find(key).Decrement(key, delta)
}

// Append appends the value to the current key value. The value to append
// must be a string, []byte or pointer to one of those types.
func (c *ShardedLRU) Append(key string, value interface{}) (err error) {
	return c.find(key).Append(key, value)
}

// Prepend prepends the value to the current key value. The value to prepend
// must be a string, []byte or pointer to one of those types.
func (c *ShardedLRU) Prepend(key string, value interface{}) (err error) {
	return c.find(key).Prepend(key, value)
}

repository: bradberger/gocache

license_type: permissive

repo_name: bradberger/gocache

branch_name: refs/heads/master

extension: go


text:
// Copyright 2016-2021, Pulumi Corporation.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

/*
This file implements a system for collecting data on how many HCL examples were
attempted to be converted to Pulumi, and what percentage of such conversions
succeeded. Additionally, it allows these diagnostics to be exported in JSON
format for uploading and further processing.

The tracker records the results of individual translation attempts: a provider
with 100 examples would have 400 attempts (four languages for each example).
How many of these attempts succeeded is what the percentages reference. These
400 attempts can either be exported as a whole, or be grouped by language into
four categories of 100 attempts, with each corresponding to one example.
*/

package tfgen

import (
	"fmt"
	"strings"

	"github.com/hashicorp/hcl/v2"
)

/*
Main overarching structure for storing coverage data on how many examples were processed,
how many failed, and for what reason. At different stages, the code translator notifies
the tracker of what is going on. Notifications are treated as an ordered sequence of events.

NOTIFICATION INTERFACE:

foundExample(pageName, hcl)

languageConversionSuccess(targetLanguage)

languageConversionWarning(targetLanguage, warningDiagnostics)

languageConversionFailure(targetLanguage, failureDiagnostics)

languageConversionPanic(targetLanguage, panicInfo)
*/
type CoverageTracker struct {
	ProviderName     string                        // Name of the provider
	ProviderVersion  string                        // Version of the provider
	currentPageName  string                        // Name of current page that is being processed
	EncounteredPages map[string]*DocumentationPage // Map linking page IDs to their data
}

// A structure encompassing a single page, which contains one or more examples.
// This closely resembles the web pages seen in Pulumi/Terraform documentation.
type DocumentationPage struct {
	Name     string    // The unique ID of this documentation page
	Examples []Example // This page's examples, stored in the order they were found
}

// Contains information about a single example, consisting of a block of HCL and
// one or more language conversion results.
type Example struct {
	OriginalHCL       string                               // Original HCL code that the example was found with
	ConversionResults map[string]*LanguageConversionResult // Mapping language names to their conversion results
}

// Individual language information concerning how successfully an example was converted to Pulumi
type LanguageConversionResult struct {
	FailureSeverity int    // This conversion's outcome: [Success, Warning, Failure, Fatal]
	FailureInfo     string // Additional in-depth information
	Program         string // Converted program

	// How many times this example has been converted to this language.
	// It is expected that this will be equal to 1.
	TranslationCount int
}

// Conversion outcome severity values
const (
	Success = 0
	Warning = 1
	Failure = 2
	Fatal   = 3
)

func newCoverageTracker(ProviderName string, ProviderVersion string) *CoverageTracker {
	return &CoverageTracker{ProviderName, ProviderVersion, "",
		make(map[string]*DocumentationPage)}
}

// Used when: generator has found a brand new example, with a convertible block
// of HCL that hasn't been encountered before.
func (ct *CoverageTracker) foundExample(pageName string, hcl string) {
	if ct == nil {
		return
	}
	ct.currentPageName = pageName

	if existingPage, ok := ct.EncounteredPages[pageName]; ok {
		// This example's page already exists. Appending example to it.
		existingPage.Examples = append(existingPage.Examples, Example{hcl, make(map[string]*LanguageConversionResult)})
	} else {
		// Initializing a page for this example.
		ct.EncounteredPages[pageName] = &DocumentationPage{
			pageName,
			[]Example{{hcl, make(map[string]*LanguageConversionResult)}},
		}
	}
}

// Used when: current example has been successfully converted to a certain language
func (ct *CoverageTracker) languageConversionSuccess(languageName string, program string) {
	if ct == nil {
		return
	}
	ct.insertLanguageConversionResult(languageName, LanguageConversionResult{
		FailureSeverity:  Success,
		FailureInfo:      "",
		TranslationCount: 1,
		Program:          program,
	})
}

// Used when: generator has successfully converted current example, but threw out some warnings
//
//nolint:unused
func (ct *CoverageTracker) languageConversionWarning(languageName string, warningDiagnostics hcl.Diagnostics) {
	if ct == nil {
		return
	}
	ct.insertLanguageConversionResult(languageName, LanguageConversionResult{
		FailureSeverity:  Warning,
		FailureInfo:      formatDiagnostics(warningDiagnostics),
		TranslationCount: 1,
	})
}

// Used when: generator has failed to convert the current example to a certain language
func (ct *CoverageTracker) languageConversionFailure(languageName string, failureDiagnostics hcl.Diagnostics) {
	if ct == nil {
		return
	}
	ct.insertLanguageConversionResult(languageName, LanguageConversionResult{
		FailureSeverity:  Failure,
		FailureInfo:      formatDiagnostics(failureDiagnostics),
		TranslationCount: 1,
	})
}

// Used when: generator encountered a fatal internal error when trying to convert the
// current example to a certain language
func (ct *CoverageTracker) languageConversionPanic(languageName string, panicInfo string) {
	if ct == nil {
		return
	}
	ct.insertLanguageConversionResult(languageName, LanguageConversionResult{
		FailureSeverity:  Fatal,
		FailureInfo:      panicInfo,
		TranslationCount: 1,
	})
}

// Adding a language conversion result to the current example. If a conversion result with the same
// target language already exists, keep the lowest severity one and mark the example as possibly duplicated
func (ct *CoverageTracker) insertLanguageConversionResult(languageName string,
	newConversionResult LanguageConversionResult) {
	if currentPage, ok := ct.EncounteredPages[ct.currentPageName]; ok {
		lastExample := currentPage.lastExample()

		if existingConversionResult, ok := lastExample.ConversionResults[languageName]; ok {
			// Example already has this language conversion attempt. Replace if new one has a lower severity
			if newConversionResult.FailureSeverity < existingConversionResult.FailureSeverity {
				lastExample.ConversionResults[languageName] = &newConversionResult
			}
			existingConversionResult.TranslationCount++
		} else {
			// The new language conversion result is added for this example
			lastExample.ConversionResults[languageName] = &newConversionResult
		}
	} else {
		// Check that foundExample() is called before all other Coverage Tracker interface methods
		fmt.Println("Error: attempted to log an example language conversion result without first finding its page")
		fmt.Println(newConversionResult)
		panic("")
	}
}

// Turning the hcl.Diagnostics provided during warnings or failures into a brief explanation of
// why the converter didn't succeed. If the diagnostics have details available, they are included.
func formatDiagnostics(diagnostics hcl.Diagnostics) string {
	results := []string{}

	// Helper method to check if results already have one of this diagnostic
	contains := func(result []string, target string) bool {
		for _, diag := range result {
			if diag == target {
				return true
			}
		}
		return false
	}

	for i := 0; i < len(diagnostics); i++ {
		formattedDiagnostic := diagnostics[i].Summary

		// Include diagnostic details if suitable
		if diagnostics[i].Detail != "" && diagnostics[i].Detail != formattedDiagnostic {
			formattedDiagnostic += ": " + diagnostics[i].Detail
		}

		// Append formatted diagnostic if results don't have it
		if !contains(results, formattedDiagnostic) {
			results = append(results, formattedDiagnostic)
		}
	}

	// Returning all the formatted diagnostics as a single string
	return strings.Join(results[:], "; ")
}

// Returning the page's last example, to which conversion results will be added.
func (Page *DocumentationPage) lastExample() *Example {
	return &Page.Examples[len(Page.Examples)-1]
}

// Exporting the coverage results
func (ct *CoverageTracker) exportResults(outputDirectory string) error {
	coverageExportUtil := newCoverageExportUtil(ct)
	return coverageExportUtil.tryExport(outputDirectory)
}

repository: pulumi/pulumi-terraform-bridge

repo_name: pulumi/pulumi-terraform-bridge

gha_language: Go


text:
SUMMARY = "Screen grabber for Dreambox Set-Top-Boxes"
LICENSE = "GPLv2"
LIC_FILES_CHKSUM = "file://LICENSE;md5=94d55d512a9ba36caa9b7df079bae19f"
DEPENDS = "jpeg libpng"
SRCREV = "${@opendreambox_srcrev('bc00c80ac3b84509df19a9be03887ffefcaeef2d', d)}"

inherit autotools opendreambox-git pkgconfig

license: MIT

repository: opendreambox/opendreambox

repo_name: opendreambox/opendreambox

branch_name: refs/heads/pyro

gha_license_id: NOASSERTION

gha_language: BitBake

extension: bb