arXiv subjects

Jinghui Cheng

Publications and source records attributed to Jinghui Cheng.

At least 37 records · Page 2Linked to original sources

arXiv2023

Characterizing Usability Issue Discussions in Open Source Software Projects

Usability is a crucial factor but one of the most neglected concerns in open source software (OSS). While far from an ideal approach, a common practice that OSS communities adopt to collaboratively address usability is through discussions on issue tracking systems (ITSs). However, there is little knowledge about the extent to which OSS community members engage in usability issue discussions, the aspects of usability they frequently target, and the characteristics of their collaboration around usability issue discussions. This knowledge is important for providing practical recommendations and research directions to better support OSS communities in addressing this important topic and improve OSS usability in general. To help achieve this goal, we performed an extensive empirical study on issues discussed in five popular OSS applications: three data science notebook projects (Jupyter Lab, Google Colab, and CoCalc) and two code editor projects (VSCode and Atom). Our results indicated that while usability issues are extensively discussed in the OSS projects, their scope tended to be limited to efficiency and aesthetics. Additionally, these issues are more frequently posted by experienced community members and display distinguishable characteristics, such as involving more visual communication and more participants. Our results provide important implications that can inform the OSS practitioners to better engage the community in usability issue discussion and shed light on future research efforts toward collaboration techniques and tools for discussing niche topics in diverse communities, such as the usability issues in the OSS context.

cs.HC↗

arXiv2023

SUMMIT: Scaffolding OSS Issue Discussion Through Summarization

For Open Source Software (OSS) projects, discussions in Issue Tracking Systems (ITS) serve as a crucial collaboration mechanism for diverse stakeholders. However, these discussions can become lengthy and entangled, making it hard to find relevant information and make further contributions. In this work, we study the use of summarization to aid users in collaboratively making sense of OSS issue discussion threads. We reveal a complex picture of how summarization is used by issue users in practice as a strategy to help develop and manage their discussions. Grounded on the different objectives served by the summaries and the outcome of our formative study with OSS stakeholders, we identified a set of guidelines to inform the design of collaborative summarization tools for OSS issue discussions. We then developed SUMMIT, a tool that allows issue users to collectively construct summaries of different types of information discussed, as well as a set of comments representing continuous conversations within the thread. To alleviate the manual effort involved, SUMMIT uses techniques that automatically detect information types and summarize texts to facilitate the generation of these summaries. A lab user study indicates that, as the users of SUMMIT, OSS stakeholders adopted different strategies to acquire information on issue threads. Furthermore, different features of SUMMIT effectively lowered the perceived difficulty of locating information from issue threads and enabled the users to prioritize their effort. Overall, our findings demonstrated the potential of SUMMIT, and the corresponding design guidelines, in supporting users to acquire information from lengthy discussions in ITSs. Our work sheds light on key design considerations and features when exploring crowd-based and machine-learning-enabled instruments for asynchronous collaboration on complex tasks such as OSS development.

cs.HC↗

arXiv2023

GUILGET: GUI Layout GEneration with Transformer

Sketching out Graphical User Interface (GUI) layout is part of the pipeline of designing a GUI and a crucial task for the success of a software application. Arranging all components inside a GUI layout manually is a time-consuming task. In order to assist designers, we developed a method named GUILGET to automatically generate GUI layouts from positional constraints represented as GUI arrangement graphs (GUI-AGs). The goal is to support the initial step of GUI design by producing realistic and diverse GUI layouts. The existing image layout generation techniques often cannot incorporate GUI design constraints. Thus, GUILGET needs to adapt existing techniques to generate GUI layouts that obey to constraints specific to GUI designs. GUILGET is based on transformers in order to capture the semantic in relationships between elements from GUI-AG. Moreover, the model learns constraints through the minimization of losses responsible for placing each component inside its parent layout, for not letting components overlap if they are inside the same parent, and for component alignment. Our experiments, which are conducted on the CLAY dataset, reveal that our model has the best understanding of relationships from GUI-AG and has the best performances in most of evaluation metrics. Therefore, our work contributes to improved GUI layout generation by proposing a novel method that effectively accounts for the constraints on GUI elements and paves the road for a more efficient GUI design pipeline.

cs.CV↗

arXiv2023

"Finding the Magic Sauce": Exploring Perspectives of Recruiters and Job Seekers on Recruitment Bias and Automated Tools

Automated recruitment tools are proliferating. While having the promise of improving efficiency, various risks, including bias, challenges the potential of these tools. An in-depth understanding of the perceived risk factors and needs from the perspective of both recruiters and job seekers is needed. We address this through an interview study in the high-tech industry to compare and contrast the concerns of these two roles. We found that the importance of clarifying position requirements and assessing candidates as "whole individuals" are commonly discussed by both recruiters and job seekers. In contrast, while recruiters tended to be more aware of cognitive bias and desired more tool support during interviews, job seekers voiced more desire towards a healthy candidate-company relationship. Additionally, both roles considered the uncertainty of the current technology capability and reduced human contact as concerns for using automated tools. Based on these results, we provided design implications for automated recruitment tools and related decision-support technologies.

cs.HC↗

arXiv2022

"Inconsistent Performance": Understanding Concerns of Real-World Users on Smart Mobile Health Applications Through Analyzing App Reviews

While smart mobile health apps that adapt to users' progressive individual needs are proliferating, many of them struggle to fulfill their promises due to an inferior user experience. Understanding the concerns of real-world users related to those apps, and their smart components in particular, could help advance the app design to attract and retain users. In this paper, we target this issue through a preliminary thematic analysis of 120 user reviews of six smart health apps. We found that accuracy, customizability, and convenience of data input are primary concerns raised in real-world user reviews. Many concerns on the smart components are related to the trust issue of the users towards the apps. However, several important aspects such as privacy and fairness were rarely discussed in the reviews. Overall, our study provides insights that can inspire further investigations to support the design of smart mobile health apps.

cs.HC↗

arXiv2022

Understanding and Supporting the Design Systems Practice

Design systems represent a user interaction design and development approach that is currently of avid interest in the industry. However, little research work has been done to synthesize knowledge related to design systems in order to inform the design of tools to support their creation, maintenance, and usage practices. This paper represents an important step in which we explored the issues that design system projects usually deal with and the perceptions and values of design system project leaders. Through this exploration, we aim to investigate the needs for tools that support the design system approach. We found that the open source communities around design systems focused on discussing issues related to behaviors of user interface components of design systems. At the same time, leaders of design system projects faced considerable challenges when evolving their design systems to make them both capable of capturing stable design knowledge and flexible to the needs of the various concrete products. They valued a bottom-up approach for design system creation and maintenance, in which components are elevated and merged from the evolving products. Our findings synthesize the knowledge and lay foundations for designing techniques and tools aimed at supporting the design system practice and related modern user interaction design and development approaches.

cs.SE↗

arXiv2022

Understanding the Characteristics of Visual Contents in Open Source Issue Discussions: A Case Study of Jupyter Notebook

Most issue tracking systems for open source software (OSS) development include features for community members to embed visual contents, such as images and videos, to enhance the discussion. Although playing an important role, there is little knowledge on the characteristics of the visual contents to support their use. To address this gap, we conducted an empirical study on the Jupyter Notebook project. We found that more than a quarter of the issues in the Jupyter Notebook project included visual contents. Additionally, issues that had visual contents in the comments but not in the issue posts tended to have a longer discussion and to involve a larger number of discussants. In our qualitative analysis, we identified eight types of visual contents in our sample, with about 60% including screenshots or mockups of the main product. We also found that visual contents served diverse purposes, touching both problem and solution spaces of the issues. Our effort serves as an important step towards a comprehensive understanding of the characteristics of visual contents in OSS issue discussions. Our results provided several design implications for issue tracking systems to better facilitate the use of visual contents.

cs.SE↗

arXiv2022

Characterizing User Behaviors in Open-Source Software User Forums: An Empirical Study

User forums of Open Source Software (OSS) enable end-users to collaboratively discuss problems concerning the OSS applications. Despite decades of research on OSS, we know very little about how end-users engage with OSS communities on these forums, in particular, the challenges that hinder their continuous and meaningful participation in the OSS community. Many previous works are developer-centric and overlook the importance of end-user forums. As a result, end-users' expectations are seldom reflected in OSS development. To better understand user behaviors in OSS user forums, we carried out an empirical study analyzing about 1.3 million posts from user forums of four popular OSS applications: Zotero, Audacity, VLC, and RStudio. Through analyzing the contribution patterns of three common user types (end-users, developers, and organizers), we observed that end-users not only initiated most of the threads (above 96% of threads in three projects, 86% in the other), but also acted as the significant contributors for responding to other users' posts, even though they tended to lack confidence in their activities as indicated by psycho-linguistic analyses. Moreover, we found end-users more open, reflecting a more positive emotion in communication than organizers and developers in the forums. Our work contributes new knowledge about end-users' activities and behaviors in OSS user forums that the vital OSS stakeholders can leverage to improve end-user engagement in the OSS development process.

cs.SE↗

arXiv2022

How heated is it? Understanding GitHub locked issues

Although issues of open source software are created to discuss and solve technical problems, conversations can become heated, with discussants getting angry and/or agitated for a variety of reasons, such as poor suggestions or violation of community conventions. To prevent and mitigate discussions from getting heated, tools like GitHub have introduced the ability to lock issue discussions that violate the code of conduct or other community guidelines. Despite some early research on locked issues, there is a lack of understanding of how communities use this feature and of potential threats to validity for researchers relying on a dataset of locked issues as an oracle for heated discussions. To address this gap, we (i) quantitatively analyzed 79 GitHub projects that have at least one issue locked as too heated, and (ii) qualitatively analyzed all issues locked as too heated of the 79 projects, a total of 205 issues comprising 5,511 comments. We found that projects have different behaviors when locking issues: while 54 locked less than 10% of their closed issues, 14 projects locked more than 90% of their closed issues. Additionally, locked issues tend to have a similar number of comments, participants, and emoji reactions to non-locked issues. For the 205 issues locked as too heated, we found that one-third do not contain any uncivil discourse, and only 8.82% of the analyzed comments are actually uncivil. Finally, we found that the locking justifications provided by maintainers do not always match the label used to lock the issue. Based on our results, we identified three pitfalls to avoid when using the GitHub locked issues data and we provide recommendations for researchers and practitioners.

cs.SE↗

arXiv2022

GANSpiration: Balancing Targeted and Serendipitous Inspiration in User Interface Design with Style-Based Generative Adversarial Network

Inspiration from design examples plays a crucial role in the creative process of user interface design. However, current tools and techniques that support inspiration usually only focus on example browsing with limited user control or similarity-based example retrieval, leading to undesirable design outcomes such as focus drift and design fixation. To address these issues, we propose the GANSpiration approach that suggests design examples for both targeted and serendipitous inspiration, leveraging a style-based Generative Adversarial Network. A quantitative evaluation revealed that the outputs of GANSpiration-based example suggestion approaches are relevant to the input design, and at the same time include diverse instances. A user study with professional UI/UX practitioners showed that the examples suggested by our approach serve as viable sources of inspiration for overall design concepts and specific design elements. Overall, our work paves the road of using advanced generative machine learning techniques in supporting the creative design practice.

cs.HC↗

arXiv2021

Machine Learning Application Development: Practitioners' Insights

Nowadays, intelligent systems and services are getting increasingly popular as they provide data-driven solutions to diverse real-world problems, thanks to recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML). However, machine learning meets software engineering not only with promising potentials but also with some inherent challenges. Despite some recent research efforts, we still do not have a clear understanding of the challenges of developing ML-based applications and the current industry practices. Moreover, it is unclear where software engineering researchers should focus their efforts to better support ML application developers. In this paper, we report about a survey that aimed to understand the challenges and best practices of ML application development. We synthesize the results obtained from 80 practitioners (with diverse skills, experience, and application domains) into 17 findings; outlining challenges and best practices for ML application development. Practitioners involved in the development of ML-based software systems can leverage the summarized best practices to improve the quality of their system. We hope that the reported challenges will inform the research community about topics that need to be investigated to improve the engineering process and the quality of ML-based applications.

cs.SE↗

arXiv2021

The "Shut the f**k up" Phenomenon: Characterizing Incivility in Open Source Code Review Discussions

Code review is an important quality assurance activity for software development. Code review discussions among developers and maintainers can be heated and sometimes involve personal attacks and unnecessary disrespectful comments, demonstrating, therefore, incivility. Although incivility in public discussions has received increasing attention from researchers in different domains, the knowledge about the characteristics, causes, and consequences of uncivil communication is still very limited in the context of software development, and more specifically, code review. To address this gap in the literature, we leverage the mature social construct of incivility as a lens to understand confrontational conflicts in open source code review discussions. For that, we conducted a qualitative analysis on 1,545 emails from the Linux Kernel Mailing List (LKML) that were associated with rejected changes. We found that more than half 66.66% of the non-technical emails included uncivil features. Particularly, frustration, name calling, and impatience are the most frequent features in uncivil emails. We also found that there are civil alternatives to address arguments, while uncivil comments can potentially be made by any people when discussing any topic. Finally, we identified various causes and consequences of such uncivil communication. Our work serves as the first study about the phenomenon of in(civility) in open source software development, paving the road for a new field of research about collaboration and communication in the context of software engineering activities.

cs.SE↗

arXiv2021

The Impacts of Sentiments and Tones in Community-Generated Issue Discussions

The diverse community members who contribute to the discussions on issue tracking systems of open-source software projects often exhibit complex affective states such as sentiments and tones. These affective states can significantly influence the effectiveness of the issue discussions in elaborating the initial ideas into actionable tasks that the development teams need to address. In this paper, we present an extended empirical study to investigate the impacts of sentiments and tones in community-generated issue discussions. We created and validated a large dataset of sentiments and tones in the issues posts and comments created by diverse community members in three popular open source projects. Our analysis results drew a complex picture of the relationships between, on the one hand, the sentiments and tones in the issue discussions, and on the other hand, various discussion and development-related measures such as the discussion length and the issue resolution time. We also found that when factors such as the issue poster roles and the issue types were controlled, sentiments and tones had varied associations with the measures. Insights gained from these findings can support open source community members in making and moderating effective issue discussions and guide the design of tools to better support community engagement.

cs.SE↗

arXiv2021

Facilitating Asynchronous Participatory Design of Open Source Software: Bringing End Users into the Loop

As open source software (OSS) becomes increasingly mature and popular, there are significant challenges with properly accounting for usability concerns for the diverse end users. Participatory design, where multiple stakeholders collaborate on iterating the design, can be an efficient way to address the usability concerns for OSS projects. However, barriers such as a code-centric mindset and insufficient tool support often prevent OSS teams from effectively including end users in participatory design methods. This paper proposes preliminary contributions to this problem through the user-centered exploration of (1) a set of design guidelines that capture the needs of OSS participatory design tools, (2) two personas that represent the characteristics of OSS designers and end users, and (3) a low-fidelity prototype tool for end user involvement in OSS projects. This work paves the road for future studies about tool design that would eventually help improve OSS usability.

cs.HC↗

arXiv2020

Adapting Nielsen's Usability Heuristics to the Context of Mobile Augmented Reality

Augmented reality (AR) is an emerging technology in mobile app design during recent years. However, usability challenges in these apps are prominent. There are currently no established guidelines for designing and evaluating interactions in AR as there are in traditional user interfaces. In this work, we aimed to examine the usability of current mobile AR applications and interpreting classic usability heuristics in the context of mobile AR. Particularly, we focused on AR home design apps because of their popularity and ability to incorporate important mobile AR interaction schemas. Our findings indicated that it is important for the designers to consider the unfamiliarity of AR technology to the vast users and to take technological limitations into consideration when designing mobile AR apps. Our work serves as a first step for establishing more general heuristics and guidelines for mobile AR.

cs.HC↗

arXiv2020

How Do Open Source Software Contributors Perceive and Address Usability? Valued Factors, Practices, and Challenges

Usability is an increasing concern in open source software (OSS). Given the recent changes in the OSS landscape, it is imperative to examine the OSS contributors' current valued factors, practices, and challenges concerning usability. We accumulated this knowledge through a survey with a wide range of contributors to OSS applications. Through analyzing 84 survey responses, we found that many participants recognized the importance of usability. While most relied on issue tracking systems to collect user feedback, a few participants also adopted typical user-centered design methods. However, most participants demonstrated a system-centric rather than a user-centric view. Understanding the diverse needs and consolidating various feedback of end-users posed unique challenges for the OSS contributors when addressing usability in the most recent development context. Our work provided important insights for OSS practitioners and tool designers in exploring ways for promoting a user-centric mindset and improving usability practice in the current OSS communities.

cs.SE↗

arXiv2020

Capturing the Practices, Challenges, and Needs of Transportation Decision-Makers

Transportation decision-makers from government agencies play an important role in addressing the traffic network conditions, which in turn, have a major impact on the well-being of citizens. The practices, challenges, and needs of this group of practitioners are less represented in the HCI literature. We address this gap through an interview study with 19 practitioners from Transports Québec, a government agency responsible for transportation infrastructures in Québec, Canada. We found that this group of decision-makers can most benefit from research about data analysis tools and platforms that (1) provide information to support data quality awareness, (2) are interoperable with other tools in the complex workflow of the practitioners, and (3) support intuitive and customizable visual analytics. These implications can also be informative to the design of tools supporting other decision-making tasks and domains.

cs.HC↗

arXiv2020

ArguLens: Anatomy of Community Opinions On Usability Issues Using Argumentation Models

In open-source software (OSS), the design of usability is often influenced by the discussions among community members on platforms such as issue tracking systems (ITSs). However, digesting the rich information embedded in issue discussions can be a major challenge due to the vast number and diversity of the comments. We propose and evaluate ArguLens, a conceptual framework and automated technique leveraging an argumentation model to support effective understanding and consolidation of community opinions in ITSs. Through content analysis, we anatomized highly discussed usability issues from a large, active OSS project, into their argumentation components and standpoints. We then experimented with supervised machine learning techniques for automated argument extraction. Finally, through a study with experienced ITS users, we show that the information provided by ArguLens supported the digestion of usability-related opinions and facilitated the review of lengthy issues. ArguLens provides the direction of designing valuable tools for high-level reasoning and effective discussion about usability.

cs.HC↗