Jinghui Cheng

Rozhan Hozhabri Nezhad, Jin L. C. Guo, Jinghui Cheng

Open source software (OSS) often prioritizes technical functionality over usability and UX design. This imbalance limits OSS adoption among broader, non-technical users. Key underlying factors contributing to this issue are the shortage of design expertise in OSS and a dominant developer-centric mindset. To address these persistent issues, we explore the potential of speculative design as a catalyst for transforming the OSS community's mindset towards a more designer-inclusive environment. Our design was informed by an analysis of online forums, which revealed designers' motivations and challenges when contributing to OSS. Guided by these insights, we created two speculative societies, Husia (collectivist) and Reetar (individualist), in which designers are valued for different reasons and their work incorporated in different ways. Through a user study with 12 OSS practitioners (seven designers and five developers), we found that our speculative societies provoked participants' rich and critical reflections on OSS values, the root causes of challenges, and proposed actions. Our work provides insights into how speculative design can be used in the practical, sociotechnical context of OSS to stimulate critical reflection, improve awareness, and yield recommendations for fostering an equitable, sustainable, and inclusive OSS environment.

Andrey Sobolevsky, Guillaume-Alexandre Bilodeau, Jinghui Cheng et al.

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.

Boniface Bahati Tadjuidje, Jin L. C. Guo, Jinghui Cheng

Open-source software (OSS) developers often struggle to understand and respond to user context, while existing tools, such as issue trackers (for handling bugs, requests, and feedback), largely focus on technical discussion. Although personas could help, limited resources and UX expertise make them hard to scale. We present PersonaFlow, a tool that generates editable user personas from OSS repository artifacts and integrates them alongside issue reports. In a user study with 13 OSS developers, most reported shifts in how they understood users, and more than half modified their responses by adding empathetic language, tailoring explanations, or raising priority ratings. We found two pathways to this change: some connected emotionally to personas as people, while others used them pragmatically for triaging. Both appeared to lead to more user-centered behavior. We contribute design implications for persona-based tools relevant to OSS and other contexts where efficiency-driven systems or workflows obscure valuable human elements.

Isabella Ferreira, Jinghui Cheng, Bram Adams

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.

Arghavan Sanei, Jinghui Cheng, Bram Adams

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.

Wenting Wang, Jinghui Cheng, Jin L. C. Guo

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.

Jinghui Cheng, Jin L. C. Guo

Contributors to open source software (OSS) communities assume diverse roles to take different responsibilities. One major limitation of the current OSS tools and platforms is that they provide a uniform user interface regardless of the activities performed by the various types of contributors. This paper serves as a non-trivial first step towards resolving this challenge by demonstrating a methodology and establishing knowledge to understand how the contributors' roles and their dynamics, reflected in the activities contributors perform, are exhibited in OSS communities. Based on an analysis of user action data from 29 GitHub projects, we extracted six activities that distinguished four Active roles and five Supporting roles of OSS contributors, as well as patterns in role changes. Through the lens of the Activity Theory, these findings provided rich design guidelines for OSS tools to support diverse contributor roles.

Deeksha Arya, Wenting Wang, Jin L. C. Guo et al.

Most modern Issue Tracking Systems (ITSs) for open source software (OSS) projects allow users to add comments to issues. Over time, these comments accumulate into discussion threads embedded with rich information about the software project, which can potentially satisfy the diverse needs of OSS stakeholders. However, discovering and retrieving relevant information from the discussion threads is a challenging task, especially when the discussions are lengthy and the number of issues in ITSs are vast. In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences. Our investigation of supervised, automated classification techniques indicated that, when prior knowledge about the issue is available, Random Forest can effectively detect most sentence types using conversational features such as the sentence length and its position. When classifying sentences from new issues, Logistic Regression can yield satisfactory performance using textual features for certain information types, while falling short on others. Our work represents a nontrivial first step towards tools and techniques for identifying and obtaining the rich information recorded in the ITSs to support various software engineering activities and to satisfy the diverse needs of OSS stakeholders.

Mohammad Ronagh Nikghalb, Jinghui Cheng

In an era of AI's growing capabilities and influences, recent advancements are reshaping HCI and CSCW's view of AI. Playful interactions emerged as an important way for users to make sense of the ever-changing AI technologies, yet remained underexamined. We target this gap by investigating playful interactions exhibited by users of a popular AI technology, ChatGPT. Through a thematic analysis of 372 user-generated posts on the ChatGPT subreddit, we found that more than half (54\%) of user discourse revolved around playful interactions. The analysis further allowed us to construct a preliminary framework to describe these interactions, categorizing them into six types: reflecting, jesting, imitating, challenging, tricking, and contriving; each included sub-categories. This study contributes to HCI and CSCW by identifying the diverse ways users engage in playful interactions with AI. It examines how these interactions can help users understand AI's agency, shape human-AI relationships, and provide insights for designing AI systems.

Md Saidur Rahman, Foutse Khomh, Alaleh Hamidi et al.

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.

Audrey Labrie, Jinghui Cheng

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.

Jinghui Cheng, Micayla Goodrum, Ronald Metoyer et al.

Safety-critical software systems are those whose failure or malfunction could result in casualty and/or serious financial loss. In such systems, safety assurance cases (SACs) are an emerging approach that adopts a proactive strategy to produce structuralized safety justifications and arguments. While SACs are recommended in many software-intensive safety-critical domains, the lack of knowledge regarding the practitioners' perspectives on using SACs hinders effective adoption of this approach. To gain such knowledge, we interviewed nine practitioners and safety experts who focused on safety-critical software systems. In general, our participants found the SAC approach beneficial for communication of safety arguments and management of safety issues in a multidisciplinary setting. The challenges they faced when using SACs were primarily associated with (1) a lack of tool support, (2) insufficient process integration, and (3) scarcity of experienced personnel. To overcome those challenges, our participants suggested tactics that focused on creating direct safety arguments. Process and organizational adjustments are also needed to streamline SAC analysis and creation. Finally, our participants emphasized the importance of knowledge sharing about SACs across software-intensive safety-critical domains.