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Goals

We are looking for insightful and thought-provoking papers that address the various roles of software engineering in society. We are especially interested in papers addressing issues around connecting different communities such as scientific communities, industry, academia, disciplines across academia, sub-disciplines across software engineering, under-represented communities, and communities across countries and continents at large. We seek contributions that highlight how software engineering can help with the opportunities and challenges posed by the rapidly accelerating pace of technological advances, including data-driven technologies and LLMs, that are impacting the economic, political, environmental, social, and technical aspects of society.

We would also like to discuss emerging trends in the development of software that is part of larger systems and whose development is tackled within the specific areas listed below. The goal is to investigate the reasons for these trends, to analyze possible novel contributions from the software engineering community, and to identify novel research challenges that these areas pose to software engineering methods and practices.

SEIS Welcomes

  • Innovative, inspiring research with a clear impact on software engineering challenges, directions, methods, and tools
  • Engagement with a broad spectrum of areas including, but not limited to:
    • Diversity and Inclusion
      • Diversity and Inclusion (e.g., Intersectional Issues related to gender, race, ethnicity, disability, socioeconomic background, sexual orientation, etc.)., Fostering Inclusion, Allyship, Covering, Privilege, Organizational Culture;
      • Designing, Engineering, and Testing Software for Diverse Users;
      • Communication and collaboration (e.g., code of conduct, hostile or inappropriate behavior, conflict and resolution, successful and unsuccessful communication or collaboration patterns);
      • The impact of data-driven technologies and LLMs on equity, diversity and inclusion;
      • Opinion pieces on why diversity and inclusion are important for software engineering;
      • Experience reports, reviews, visions and roadmaps on diversity and inclusion
    • Software Engineering for Sciences, Design, Arts and Engineering
      • Medicine and public health (e.g., Health Informatics, software technologies for aging);
      • Physical Sciences (e.g., Computational Chemistry, Genomic, Biotechnologies);
      • Environmental Sciences (e.g., Sustainability, Urban Planning, Ecology, Climate Change);
      • Social Sciences (e.g., Organizational Psychology, Software Fairness, Regulatory Compliance);
      • Management (e.g., socio-technical ecosystems, technical debt, social debt);
      • Economics (e.g., Electronic payments, Blockchain technologies);
      • Law (e.g., combating and investigating crime, impact on the legal system);
      • Manufacturing (e.g., Industry 4.0, smart factory);
      • Engineering emerging cyber-physical systems (e.g., autonomous vehicles, smart cities);
      • Arts (e.g., Digital Art, Performing Arts) and Crafts (e.g. DIY electronics);
      • Design (e.g., Value-sensitive Design, history of cultural change, future of cultural changes);
      • Interdisciplinary research (e.g., Cognitive Science, Digital Social Innovation);
      • Computing and Engineering (e.g., HCI, AI, Data Science, Distributed Computing);
    • Society and societal challenges
      • Security and Privacy (e.g., security and privacy preserving software development);
      • Ethics (e.g., Responsible AI, Whistleblowing, Free Speech, Gatekeepers, Politics);
      • Misinformation (e.g., Recognition, Impeding its Spread, Censorship);
      • Work emerging from research partnerships with communities, NGOs, cultural institutions, and the public and private sector;
      • Research reflections on the long-term implications of digital technology interventions on all aspects in society (e.g., economics, social, political, environmental, technical);
      • Sustainability and UN sustainability goals;
  • Research directions towards new development models, tools, and methods for specific application environments;
  • Research findings supported by empirical studies and experimentation.
Dates
Wed 30 Apr 2025
Thu 1 May 2025
Fri 2 May 2025
Tracks
ICSE Demonstrations
ICSE Journal-first Papers
ICSE New Ideas and Emerging Results (NIER)
ICSE Research Track
ICSE SE In Practice (SEIP)
ICSE SE in Society (SEIS)
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Wed 30 Apr

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Gender, Equity and DiversitySE in Society (SEIS) at 206 plus 208
Chair(s): Ronnie de Souza Santos University of Calgary
11:00
15m
Talk
A Socio-Technical Grounded Theory on the Effect of Cognitive Dysfunctions in the Performance of Software Developers with ADHD and Autism
SE in Society (SEIS)
Kiev Gama Universidade Federal de Pernambuco, Grischa Liebel Reykjavik University, Miguel Goulao NOVA-LINCS, FCT/UNL, Aline Lacerda Federal University of Pernambuco (UFPE), Cristiana Lacerda Federal University of Pernambuco (UFPE)
Pre-print
11:15
15m
Talk
Belonging Beyond Code: Queer Software Engineering and Humanities Student Experiences
SE in Society (SEIS)
Emily Vorderwülbeke University of Passau, Isabella Graßl Technical University of Darmstadt
Pre-print
11:30
15m
Talk
Breaking the Silos: An Actionable Framework for Recruiting Diverse Participants in SE
SE in Society (SEIS)
Shandler Mason North Carolina State University, Hank Lenham North Carolina State University, Sandeep Kuttal North Carolina State University
11:45
15m
Talk
Enhancing Women's Experiences in Software Engineering
SE in Society (SEIS)
Júlia Rocha Fortunato University of Brasília, Luana Ribeiro Soares University of Brasília, Gabriela Silva Alves University of Brasília, Edna Dias Canedo University of Brasilia (UnB), Fabiana Freitas Mendes Aalto University
12:00
15m
Talk
Investigating the Developer eXperience of LGBTQIAPN+ People in Agile Teams
SE in Society (SEIS)
Edvaldo R. Wassouf-Jr UFMS, Pedro Fukuda Federal University of Mato Grosso do Sul, Awdren Fontão Federal University of Mato Grosso do Sul (UFMS)
12:15
15m
Talk
There's Nothing to See Here: A Study of Deaf and Hearing Developer Use of Stack Overflow
SE in Society (SEIS)
Steve Counsell Brunel University London, Giuseppe Destefanis Brunel University of London, Rumyana Neykova Brunel University London, Alina Miron Brunel University, Nadine Aburumman Brunel University, Thomas Shippey LogicMonitor
16:00 - 17:45
Human and Social 1SE in Society (SEIS) / SE In Practice (SEIP) at 206 plus 208
Chair(s): Yvonne Dittrich IT University of Copenhagen, Denmark
16:15
15m
Talk
A Collaborative Framework for Cross-Domain Scientific Experiments for Society 5.0Artifact-ReusableArtifact-AvailableResearch MethodsArtifact-Functional
SE in Society (SEIS)
Muhammad Mainul Hossain University of Saskatchewan, Banani Roy University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan
16:30
15m
Talk
A First Look at AI Trends in Value-Aligned Software Engineering Publications: Human-LLM Insights
SE in Society (SEIS)
Ahmad Azarnik Universiti Teknologi Malaysia, Davoud Mougouei , Mahdi Fahmideh University of Southern Queensland, Elahe Mougouei Islamic Azad University Najafabad, Hoa Khanh Dam University of Wollongong, Arif Ali Khan University of Oulu, Saima Rafi Edinburgh Napier University, Javed Ali Khan University of Hertforshire Hertfordshire, UK, Aakash Ahmad School of Computing and Communications, Lancaster University Leipzig, Leipzig, Germany
Link to publication
16:45
15m
Talk
From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?Artifact-ReusableArtifact-AvailableArtifact-Functional
SE in Society (SEIS)
Gianmario Voria University of Salerno, Stefano Lambiase University of Salerno, Maria Concetta Schiavone University of Salerno, Gemma Catolino University of Salerno, Fabio Palomba University of Salerno
Pre-print
17:00
15m
Talk
Not real or too soft? On the challenges of publishing interdisciplinary software engineering researchArtifact-Available
SE in Society (SEIS)
Sonja Hyrynsalmi LUT University, Grischa Liebel Reykjavik University, Ronnie de Souza Santos University of Calgary, Sebastian Baltes University of Bayreuth
Pre-print
17:15
15m
Talk
What is unethical about software? User perceptions in the Netherlands
SE in Society (SEIS)
Yagil Elias Vrije Universiteit Amsterdam, Tom P Humbert Vrije Universiteit Amsterdam, Lauren Olson Vrije Universiteit Amsterdam, Emitzá Guzmán Vrije Universiteit Amsterdam
Pre-print

Thu 1 May

Displayed time zone: Eastern Time (US & Canada) change

13:00 - 13:30
13:00
30m
Talk
Ethical Issues in Video Games: Insights from Reddit Discussions
SE in Society (SEIS)
Yeqian Li Vrije Universiteit Amsterdam, Kousar Aslam Vrije Universiteit Amsterdam
14:00 - 15:30
SE for AI 3Research Track / SE in Society (SEIS) / Journal-first Papers at 215
Chair(s): Lina Marsso École Polytechnique de Montréal
15:00
15m
Talk
A Reference Model for Empirically Comparing LLMs with HumansSE for AI
SE in Society (SEIS)
Kurt Schneider Leibniz Universität Hannover, Software Engineering Group, Farnaz Fotrousi Chalmers University of Technology and University of Gothenburg, Rebekka Wohlrab Chalmers University of Technology
15:30 - 16:00
15:30
30m
Talk
Strategies to Embed Human Values in Mobile Apps: What do End-Users and Practitioners Think?
SE in Society (SEIS)
Rifat Ara Shams CSIRO's Data61, Mojtaba Shahin RMIT University, Gillian Oliver Monash University, Jon Whittle CSIRO's Data61 and Monash University, Waqar Hussain Data61, CSIRO, Harsha Perera CSIRO's Data61, Arif Nurwidyantoro Universitas Gadjah Mada

Fri 2 May

Displayed time zone: Eastern Time (US & Canada) change

10:30 - 11:00
10:30
30m
Talk
Ethical Issues in Video Games: Insights from Reddit Discussions
SE in Society (SEIS)
Yeqian Li Vrije Universiteit Amsterdam, Kousar Aslam Vrije Universiteit Amsterdam
13:00 - 13:30
13:00
30m
Talk
Strategies to Embed Human Values in Mobile Apps: What do End-Users and Practitioners Think?
SE in Society (SEIS)
Rifat Ara Shams CSIRO's Data61, Mojtaba Shahin RMIT University, Gillian Oliver Monash University, Jon Whittle CSIRO's Data61 and Monash University, Waqar Hussain Data61, CSIRO, Harsha Perera CSIRO's Data61, Arif Nurwidyantoro Universitas Gadjah Mada
14:00 - 15:30
Human and Social 4Journal-first Papers / SE in Society (SEIS) / SE In Practice (SEIP) / Research Track at 206 plus 208
Chair(s): Liliana Pasquale University College Dublin & Lero
14:30
15m
Talk
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository StudyArtifact-ReusableArtifact-AvailableArtifact-Functional
SE in Society (SEIS)
Vincenzo De Martino University of Salerno, Silverio Martínez-Fernández UPC-BarcelonaTech, Fabio Palomba University of Salerno
Pre-print
15:00
15m
Talk
A Bot-based Approach to Manage Codes of Conduct in Open-Source Projects
SE in Society (SEIS)
Sergio Cobos IN3 - UOC, Javier Luis Cánovas Izquierdo Universitat Oberta de Catalunya
Pre-print
14:00 - 15:30
User ExperienceJournal-first Papers / Research Track / SE In Practice (SEIP) / SE in Society (SEIS) at 207
Chair(s): Ramiro Liscano Ontario Tech University
14:45
15m
Talk
Designing a Tool for Evacuation Plan Validation: Multi-Agent Simulations with Persona-Based UI
SE in Society (SEIS)
Gennaro Zanfardino University of L'Aquila, Antinisca Di Marco University of L'Aquila, Michele Tucci University of L'Aquila
16:00 - 17:30
Human and Social for AIResearch Track / SE in Society (SEIS) / SE In Practice (SEIP) at 206 plus 208
Chair(s): Ramiro Liscano Ontario Tech University
16:45
15m
Talk
Curious, Critical Thinker, Empathetic, and Ethically Responsible: Essential Soft Skills for Data Scientists in Software Engineering
SE in Society (SEIS)
Matheus de Morais Leça University of Calgary, Ronnie de Souza Santos University of Calgary
17:00
15m
Talk
Multi-Modal LLM-based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education
SE in Society (SEIS)
Minjoo Kim Sookmyung Women's University, Tae-Hyun Kim Sookmyung Women's University, Jaehyun Chung Korea University, Hyunseok Choi Korea University, Seokhyeon Min Korea University, Joon-Ho Lim Tutorus Labs, Soohyun Park Sookmyung Women's University
17:15
15m
Talk
What Does a Software Engineer Look Like? Exploring Societal Stereotypes in LLMs
SE in Society (SEIS)
Muneera Bano CSIRO's Data61, Hashini Gunatilake Monash University, Rashina Hoda Monash University

Accepted Papers

Title
A Bot-based Approach to Manage Codes of Conduct in Open-Source Projects
SE in Society (SEIS)
Pre-print
A Collaborative Framework for Cross-Domain Scientific Experiments for Society 5.0Artifact-ReusableArtifact-AvailableResearch MethodsArtifact-Functional
SE in Society (SEIS)
A First Look at AI Trends in Value-Aligned Software Engineering Publications: Human-LLM Insights
SE in Society (SEIS)
Link to publication
A Reference Model for Empirically Comparing LLMs with HumansSE for AI
SE in Society (SEIS)
A Socio-Technical Grounded Theory on the Effect of Cognitive Dysfunctions in the Performance of Software Developers with ADHD and Autism
SE in Society (SEIS)
Pre-print
Belonging Beyond Code: Queer Software Engineering and Humanities Student Experiences
SE in Society (SEIS)
Pre-print
Breaking the Silos: An Actionable Framework for Recruiting Diverse Participants in SE
SE in Society (SEIS)
Curious, Critical Thinker, Empathetic, and Ethically Responsible: Essential Soft Skills for Data Scientists in Software Engineering
SE in Society (SEIS)
Designing a Tool for Evacuation Plan Validation: Multi-Agent Simulations with Persona-Based UI
SE in Society (SEIS)
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository StudyArtifact-ReusableArtifact-AvailableArtifact-Functional
SE in Society (SEIS)
Pre-print
Enhancing Women's Experiences in Software Engineering
SE in Society (SEIS)
Ethical Issues in Video Games: Insights from Reddit Discussions
SE in Society (SEIS)
From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?Artifact-ReusableArtifact-AvailableArtifact-Functional
SE in Society (SEIS)
Pre-print
Investigating the Developer eXperience of LGBTQIAPN+ People in Agile Teams
SE in Society (SEIS)
Multi-Modal LLM-based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education
SE in Society (SEIS)
Not real or too soft? On the challenges of publishing interdisciplinary software engineering researchArtifact-Available
SE in Society (SEIS)
Pre-print
Strategies to Embed Human Values in Mobile Apps: What do End-Users and Practitioners Think?
SE in Society (SEIS)
There's Nothing to See Here: A Study of Deaf and Hearing Developer Use of Stack Overflow
SE in Society (SEIS)
What Does a Software Engineer Look Like? Exploring Societal Stereotypes in LLMs
SE in Society (SEIS)
What is unethical about software? User perceptions in the Netherlands
SE in Society (SEIS)
Pre-print

Call for Papers

Scope

We are interested in social, technical, and/or socio-technical research approaches that have been applied to investigate and explain societal problems in depth and/or to address or to support solutions to societal problems. We especially welcome papers studying diversity, inclusion, belonging, and representation. Equally, we are interested in sharing case studies, success stories, failures and lessons learned from working in highly complex problem spaces such as climate change, public health, cyber-security and democracy. We are interested in software engineering tools, processes, architectures, methods, frameworks, and theories that are relevant in these settings. SEIS authors are encouraged to contribute soundly motivated and novel research, both mature and emerging. SEIS welcomes multi- and inter-disciplinary research showcasing how software engineering can contribute to the many dimensions of software embedded in and influencing society.

We encourage all submissions to discuss the broader impacts of their work. What impact will this work have, or has already had, on the world and on diversity, inclusion, belonging, and representation? How does the work engage with underrepresented groups to bring new perspectives on research? These impacts should be directly related to the research focus of the paper.

Submission Types

  • Full research paper, up to 10 pages documenting results and findings, where the research presented has followed established research methods;
  • Short research paper, up to 4 pages, reporting novel approaches that have not been fully evaluated, which will be presented as a poster;
  • Experience report, up to 10 pages, reporting on real-world problems and innovative solutions, or tools;
  • Opinion, vision, method, meta-research paper, up to 4 pages, reporting on well-founded arguments to support diversity and inclusion.

For all papers, references may use 2 extra pages beyond the page limits stated above.

Evaluation

The primary criteria for acceptance of a paper submitted to SEIS are the scientific quality of the paper and the extent to which the paper meets the SEIS track goals and scope. The SEIS program committee will undertake the assessment with regard to the following criteria:

  • relevance to the Software Engineering community,
  • impact to society,
  • soundness of the technical contribution,
  • originality of the paper,
  • appropriate consideration of relevant literature,
  • acknowledgment of broader impacts, and
  • clarity of presentation.

Each submission will be reviewed by at least three members of the program committee.

For full research papers, all the above criteria are expected to be met as much as possible and to a high degree. Evaluation of short papers may focus on one of the criteria more to make up for some weaknesses in another. For example, evaluating the “soundness of the contribution” may be limited for papers presenting approaches that have not been fully evaluated, and greater attention may be paid to the “originality” criterion in such cases. For experience reports, “appropriate consideration of relevant literature” will be interpreted as at a level appropriate for an experience report, i.e. not a full or systematic review but due consideration of closely related research and practitioner works. For opinion, vision, method, and meta-research papers, “soundness of the contribution” will be evaluated by considering the soundness of the arguments presented and the feasibility of the new ideas for real-world application, whether in software practice or research.

Submission instructions and policies

  • Submissions must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options).
  • By submitting to this track, authors acknowledge that they are aware of and agree to be bound by the ACM Policy and Procedures on Plagiarism (https://www.acm.org/publications/policies/plagiarism) and the IEEE Plagiarism FAQ (https://www.ieee.org/publications/rights/plagiarism/plagiarism-faq.html). In particular, papers submitted to ICSE 2025 SEIS must not have been published elsewhere and must not be under review or submitted for review elsewhere whilst under consideration for ICSE 2025. Contravention of this concurrent submission policy will be deemed a serious breach of scientific ethics, and appropriate action will be taken in all such cases. To check for double submission and plagiarism issues, the chairs reserve the right to (1) share the list of submissions with the PC Chairs of other conferences with overlapping review periods and (2) use external plagiarism detection software, under contract to the ACM or IEEE, to detect violations of these policies.
  • By submitting to this track, authors acknowledge that they conform to the authorship policy of the ACMhttps://www.acm.org/publications/policies/new-acm-policy-on-authorship ), and the authorship policy of the IEEE (https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/ethical-requirements/Ethical Requirements ).
  • By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM’s new Publications Policy on Research Involving Human Participants and Subjects. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.
  • Note, we use double-anonymous reviewing. Be sure to remove the list of authors from the submitted paper. If citing your own prior work, please do so in the third person to obscure the relationship you have with it. For advice, guidance, and explanation about the double-anonymous review process, see ICSE2025 Q&A page (https://conf.researchr.org/info/icse-2025/submitting-to-icse2025%3A-q%26a).
  • Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start and we have recently made a commitment to collect ORCID IDs from all of our published authors. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.
  • All papers must be written in English.
  • All papers should be made accessible to people with disabilities. See some guidelines from the folks at SIGACCESS here: https://assets21.sigaccess.org/creating_accessible_pdfs.html.

Submissions that meet the above requirements can be made via the SEIS submission site. Any submission that does not comply with these requirements may be desk rejected without further review.

SEIS Submission site: https://icse2025-seis.hotcrp.com/

Conference Attendance Expectation

If a submission is accepted, at least one author of the paper is required to register for and attend the full 3-day technical conference and present the paper. We are assuming that the conference will be in-person, and if it is virtual or hybrid, virtual presentations may be possible. These matters will be discussed with the authors closer to the date of the conference.

Important Dates

  • Submissions Deadline: October 10th, 2024 - Submissions close at 23:59 AoE (Anywhere on Earth, UTC-12)
  • Acceptance notification: December 15th, 2024
  • Camera ready: January 10th, 2025

Contact

If there are queries regarding the CFP, please contact the SEIS Co-Chairs.

The following papers have been accepted in the ICSE 2025 SEIS Track. The papers are will be published by the IEEE and appear in the IEEE and ACM digital libraries, subject to an author submitting their camera-ready and copyright forms, and registering to attend the conference. (Authors are required to present the papers at the conference, otherwise they will be withdrawn).

Júlia Rocha Fortunato, Luana Ribeiro Soares, Gabriela Silva Alves, Edna dias Canedo, Fabiana Mendes, "Enhancing Women's Experiences in Software Engineering"

Abstract: Context: Women face many challenges in their lives, including harassment, lack of acceptance, and excessive workloads. These challenges affect their daily experiences and influence major life decisions, such as pursuing a career in IT. These issues further diminish the already low participation of women in the industry, making the field less appealing to potential newcomers. The challenges often begin before women even enroll in bachelor's programs, setting a difficult path for those aspiring to enter the software development industry. Goal: To investigate challenges women face in IT at different stages of their lives—specifically, during their last year of high school, while they are at University pursuing their bachelor's degree, and as practitioners. Furthermore, we aim to explore solutions to address these identified challenges. Research Method: To achieve this goal, we conducted a literature review using the snowballing technique to identify challenges and solutions already reported in the literature. The literature review results were used as input for workshops, in which we sought to understand the perspectives of high school women, undergraduates, and practitioners regarding the same set of challenges and solutions identified in the literature. Results: Our studies revealed that, regardless of the life stage, women feel discouraged in a toxic environment often characterized by a lack of inclusion, harassment, and the exhausting need to prove themselves. We also discovered that some challenges are specific to certain life stages; for example, issues related to maternity were mentioned only by practitioners. Conclusions: Women encounter gender-related challenges even before deciding to enter the software development field when the proportion of men and women is still similar. While issues such as feeling the need to prove themselves are mentioned at all three stages, high school women's challenges are more often directed toward convincing their parents that they are mature enough to handle their own responsibilities. As women move to the other stages, the challenge shifts to proving their competence in managing responsibilities for which they have received training. Increasing the inclusion of women in the field should, therefore, start earlier, and profound societal changes may be necessary to boost women's participation in the field.

 Tags: "Human/Social", "Gender, equity and diversity"  
 
Vincenzo De Martino, Silverio Martínez-Fernández, Fabio Palomba, "Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study"

Abstract: As machine learning (ML) and artificial intelligence (AI) technologies become increasingly prevalent in society, concerns about their environmental sustainability have grown. Developing and deploying ML-enabled systems, especially during training and inference, are resource-intensive, raising sustainability issues. Green AI has emerged as a response, advocating for reducing the computational demands of AI while maintaining accuracy. While recent research has identified various green tactics for developing sustainable ML-enabled systems, there is a gap in understanding the extent to which these tactics are adopted in real-world projects and whether additional, undocumented practices exist. This paper addresses these gaps by presenting a mining software repository study that evaluates the adoption of green tactics in 168 open-source ML projects on GitHub. In doing so, we introduce a novel mining mechanism based on large language models to identify and analyze green tactics within software repositories. Our results provide insights into the adoption of green tactics found in the literature and expand previous catalogs by providing 12 new tactics, with code examples to support wider implementation. This study contributes to the development of more sustainable ML systems by identifying adopted green tactics that offer substantial environmental benefits with minimal implementation effort. It provides practical insights for developers to green their systems and offers a path for future research to automate the integration of these tactics.

 Tags: "Human/Social", "Green / Environmental SE", "SE for AI", "AI for SE"  
 
Gianmario Voria, Stefano Lambiase, Maria Concetta Schiavone, Gemma Catolino, Fabio Palomba, "From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?"

Abstract: As the adoption of machine learning (ML) systems continues to grow across industries, concerns about fairness and bias in these systems have taken center stage. Fairness toolkits—designed to mitigate bias in ML models—serve as critical tools for addressing these ethical concerns. However, their adoption in the context of software development remains underexplored, especially regarding the cognitive and behavioral factors driving their usage. As a deeper understanding of these factors could be pivotal in refining tool designs and promoting broader adoption, this study investigates the factors influencing the adoption of fairness toolkits from an individual perspective. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT2), we examined the factors shaping the intention to adopt and actual use of fairness toolkits. Specifically, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data from a survey study involving practitioners in the software industry. Our findings reveal that performance expectancy and habit are the primary drivers of fairness toolkit adoption. These insights suggest that by emphasizing the effectiveness of these tools in mitigating bias and fostering habitual use, organizations can encourage wider adoption. Practical recommendations include improving toolkit usability, integrating bias mitigation processes into routine development workflows, and providing ongoing support to ensure professionals see clear benefits from regular use.

 Tags: "Human/Social", "Resp SE and Ethics", "Process", "SE for AI"  
 
Steve Counsell, Giuseppe Destefanis, Rumyana Neykova, Alina Miron, Nadine Aburumman, Thomas Shippey, "There's Nothing to See Here: A Study of Deaf and Hearing Developer Use of Stack Overflow"

Abstract: In this paper, we analyse the 2022 Stack Overflow developer survey data that, for the only time, included questions on accessibility. We extracted data from both deaf and hearing developers to determine any differences in the way each used Stack Overflow; nine of the original survey questions were explored relating to frequency, nature and extent of Stack Overflow use. Our over-arching aim was to show that there were differences between the two. Based on a randomly selected sample of hearing developers however, we found no evidence of any difference between the two groups across the nine questions. When we ran the same analysis matching the two groups identically on years of coding experience, we found (counter-intuitively) marginally more difference. In fact, from eighteen tests in total, only one was statistically significant. Understanding developer accessibility issues is important, but if our results are common across software development practice, then we question the ethos of collecting accessibility data. Developers (deaf or hearing) act in the same way with respect to Stack Overflow use, irrespective of any barriers they may face.

 Tags: "Human/Social", "Gender, equity and diversity", "Open Source"  
 
Kurt Schneider, Farnaz Fotrousi, Rebekka Wohlrab, "A Reference Model for Empirically Comparing LLMs with Humans"

Abstract: Large Language Models (LLM) have shown stunning abilities to carry out tasks that were previously conducted by humans. The future role of humans and the responsibilities assigned to non-human LLMs affects society fundamentally. In that context, LLMs have often been compared to humans. However, it is surprisingly difficult to make a fair empirical comparison between humans and LLMs. To address those difficulties, we aim at establishing a systematic approach to guide researchers in comparing LLMs with humans across various linguistic and cognitive tasks. We developed a reference model of the information flow in an exploratory research study. Through a literature review, we examined key differences and similarities among several existing studies. We propose a framework to support researchers in designing and executing studies, and in assessing LLMs with respect to humans. Future studies can use the reference model as guidance for designing and reporting their own unique study design by mapping key decisions to the decision points of that reference model. We want to support researchers and the society to take a maturation step in this emerging and constantly growing field.

 Tags: "Human/Social", "SE for AI", "Research Methods"  
 
Matheus de Morais Leça, Ronnie de Souza Santos, "Curious, Critical Thinker, Empathetic, and Ethically Responsible: Essential Soft Skills for Data Scientists in Software Engineering"

Abstract: Background. As artificial intelligence and AI-powered systems continue to grow, the role of data scientists has become essential in software development environments. Data scientists face challenges related to managing large volumes of data and addressing the societal impacts of AI algorithms, which require a broad range of soft skills. Goal. This study aims to identify the key soft skills that data scientists need when working on AI-powered projects, with a particular focus on addressing biases that affect society. Method. We conducted a thematic analysis of 87 job postings on LinkedIn and 11 interviews with industry practitioners. The job postings came from companies in 12 countries and covered various experience levels. The interviews featured professionals from diverse backgrounds, including different genders, ethnicities, and sexual orientations, who worked with clients from South America, North America, and Europe. Results. While data scientists share many skills with other software practitioners—such as those related to coordination, engineering, and management—there is a growing emphasis on innovation and social responsibility. These include soft skills like curiosity, critical thinking, empathy, and ethical awareness, which are essential for addressing the ethical and societal implications of AI. Conclusion. Our findings indicate that data scientists working on AI-powered projects require not only technical expertise but also a solid foundation in soft skills that enable them to build AI systems responsibly, with fairness and inclusivity. These insights have important implications for recruitment and training within software companies and for ensuring the long-term success of AI-powered systems and their broader societal impact.

 Tags: "Human/Social", "SE for AI", "Gender, equity and diversity"  
 
Sergio Cobos, Javier Luis Cánovas Izquierdo, "A Bot-based Approach to Manage Codes of Conduct in Open-Source Projects"

Abstract: The development of Open-Source Software (OSS) projects relies on the collaborative work of contributors, generally scattered around the world. To enable this collaboration, OSS projects are hosted on social-coding platforms like GitHub, which provide the infrastructure to host the code as well as the support for enabling the participation of the community. The potentially rich and diverse mixture of contributors in OSS projects makes their management not only a technical challenge, where automation tools and bots are usually deployed, but also a social one. To this aim, OSS projects have been increasingly deploying a declaration of their code of conduct, which defines rules to ensure a respectful and inclusive participatory environment in the community, being the Contributor Covenant the main model to follow. However, the broad adoption and enforcement of codes of conduct in OSS projects is still limited. In particular, the definition, deployment, and enforcement of codes of conduct is a very challenging task. In this paper, we propose an approach to effectively manage codes of conduct in OSS projects based on the Contributor Covenant proposal. Our solution has been implemented as a bot-based solution where bots help in the definition of codes of conduct, the monitoring of OSS projects, and the enforcement of ethical rules.

 Tags: "Human/Social", "Resp SE and Ethics", "Open Source"  
 
Muneera Bano, Hashini Gunatilake, Rashina Hoda, "What Does a Software Engineer Look Like? Exploring Societal Stereotypes in LLMs"

Abstract: Large language models (LLMs) have rapidly gained popularity and are being embedded into professional applications due to their capabilities in generating human-like content. However, unquestioned reliance on their outputs and recommendations can be problematic as LLMs can reinforce societal biases and stereotypes. This study investigates how LLMs, specifically OpenAI's GPT-4 and Microsoft Copilot, can reinforce gender and racial stereotypes within the software engineering (SE) profession through both textual and graphical outputs. We used each LLM to generate 300 profiles, consisting of 100 gender-based and 50 gender-neutral profiles, for a recruitment scenario in SE roles. Recommendations were generated for each profile and evaluated against the job requirements for four distinct SE positions. Each LLM was asked to select the top 5 candidates and subsequently the best candidate for each role. Each LLM was also asked to generate images for the top 5 candidates, providing a dataset for analysing potential biases in both text-based selections and visual representations. Our analysis reveals that both models preferred male and Caucasian profiles, particularly for senior roles, and favoured images featuring traits such as lighter skin tones, slimmer body types, and younger appearances. These findings highlight underlying societal biases influence the outputs of LLMs, contributing to narrow, exclusionary stereotypes that can further limit diversity and perpetuate inequities in the SE field. As LLMs are increasingly adopted within SE research and professional practices, awareness of these biases is crucial to prevent the reinforcement of discriminatory norms and to ensure that AI tools are leveraged to promote an inclusive and equitable engineering culture rather than hinder it.

 Tags: "Human/Social", "SE for AI", "Gender, equity and diversity"  
 
Minjoo Kim, Tae-Hyun Kim, Jaehyun Chung, Hyunseok Choi, Seokhyeon Min, Joon-Ho Lim, Soohyun Park, "Multi-Modal LLM-based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education"

Abstract: Due to the academic and commercial successes in large-language model (LLM) software research and development, there are a lot of activities to utilize this technology. Accordingly, many successful software have been released and developed for various social applications. Among them, mathematics education is one of emerging social applications which is obviously helpful for social welfare. Aligned with the development directions of LLM technologies, the use of direct preference optimization (DPO) is considered. However, one of the biggest hurdles is the lack of training dataset. Therefore, this research introduces fully-automated training dataset generation using the advanced form of LLM, i.e., multi-modal LLM. Based on various generation results based on our multi-modal LLM, various discussions and analysis results are provided. Lastly, it has to be noted that our proposed platform can contribute to providing fair education opportunities for diverse human beings without discrimination, which is definitely beneficial for social welfare.

 Tags: "Human/Social", "SE for AI", "Education"  
 
Muhammad Mainul Hossain, Banani Roy, Chanchal Roy, Kevin Schneider, "A Collaborative Framework for Cross-Domain Scientific Experiments for Society 5.0"

Abstract: The convergence of technology and human creativity in Society 5.0 demands innovative approaches to address complex scientific challenges across diverse domains, making cohesive experiments essential. The increasing complexity, diversity, and scale of data, along with the need for interdisciplinary exploration and knowledge discovery, present significant challenges. Computational scientific experiments leverage methods such as data acquisition, preprocessing, analysis, and visualization to simulate and understand intricate phenomena. However, existing interactive environments (e.g., Jupyter Notebook, Google Colab), collaborative groupware systems (e.g., Co-Taverna, iPlant Collaborative), and scientific workflow management systems (e.g., Galaxy, Kepler) often fall short in providing the automation, scalability, and reproducibility required for scientific experimentation. Additionally, they lack the usability and flexibility necessary for accommodating varying skill levels among researchers and supporting effective collaboration across domains. This paper introduces a collaborative framework designed to support cross-domain computational scientific experiments, fostering automation of complex operations, intuitive workflow composition, easy collaboration among researchers, comprehensive data and process lineage management, and seamless integration of data, tools, and experiments, allowing domain experts to focus on scientific discovery rather than the technical complexities involved. This study outlines the architecture and key features of the framework and discusses the challenges it addresses for Society 5.0. As a proof of concept, we developed prototype workflow management systems for code clone analysis, bioinformatics, image processing, and machine learning by integrating tools and services from the respective domains. We conducted case studies illustrating the creation of numerous cross-domain workflows and evaluated the framework's flexibility through tool integration via a user study. The results demonstrate its effectiveness in facilitating cross-domain scientific experimentation, aligning with the principles of Society 5.0, and fostering innovation and knowledge discovery across diverse scientific domains. Two anonymous virtual machines of the prototype are hosted at http://143.110.214.145 and http://165.22.229.234 for experimentation.

 Tags: "Research Methods", "Human/Social", "Design/Architecture"  
 
Yagil Elias, Tom P. Humbert, Lauren Olson, Emitzá Guzmán, "What is unethical about software? User perceptions in the Netherlands"

Abstract: Software has the potential to improve lives. Yet, unethical and uninformed software practices are at the root of an increasing number of ethical concerns. Despite its pervasiveness, few research has analyzed end-users perspectives on the ethical issues of the software they use. We address this gap, and investigate end-user's ethical concerns in software through 19 semi-structured interviews with residents of the Netherlands. We ask a diverse group of users about their ethical concerns when using everyday software applications. We investigate the underlying reasons for their concerns and what solutions they propose to eliminate them. We find that our participants actively worry about privacy, transparency, manipulation, safety and inappropriate content; with privacy and manipulation often being at the center of their worries. Our participants demand software solutions to improve information clarity in applications and provide more control over the user experience. They further expect larger systematic changes within software practices and government regulation.

 Tags: "Human/Social", "Resp SE and Ethics"  
 
Emily Vorderwülbeke, Isabella Graßl, "Belonging Beyond Code: Queer Software Engineering and Humanities Student Experiences"

Abstract: Queer students often encounter discrimination and a lack of belonging in their academic environments, contributing to higher dropout rates. This may be especially true in heteronormative male-dominated fields like software engineering, which already faces a \emph{diversity crisis}. In contrast, disciplines like humanities have a higher proportion of queer students, suggesting a more diverse academic culture. While prior research has explored queer students' challenges in STEM fields, limited attention has been given to how experiences differ between the sociotechnical, yet highly heteronormative, field of software engineering and the socioculturally inclusive humanities. This study addresses that gap by comparing 165 queer software engineering and 119 queer humanities students regarding outness, campus climate, sense of belonging, and dropout intentions. Our findings reveal that queer students in software engineering are less likely to be open about their sexuality, report a significantly lower sense of belonging, and encounter more academic challenges compared to their peers in the humanities. Despite these challenges, queer software engineering students show greater determination to continue their studies. These insights suggest that software engineering could enhance inclusivity by adopting practices commonly seen in the humanities, such as fostering acceptance and integrating inclusive policies in classrooms, to create a more welcoming academic environment where queer students can thrive.

 Tags: "Human/Social", "Gender, equity and diversity", "Education"  
 
Kiev Gama, Grischa Liebel, Miguel Goulao, Aline Lacerda, Cristiana Lacerda, "A Socio-Technical Grounded Theory on the Effect of Cognitive Dysfunctions in the Performance of Software Developers with ADHD and Autism"

Abstract: The concept of neurodiversity, encompassing conditions such as Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD), dyslexia, and dyspraxia, challenges traditional views of these neurodevelopmental variations as disorders and instead frames them as natural cognitive differences that contribute to unique ways of thinking and problem-solving. Within the software development industry, known for its emphasis on innovation, there is growing recognition of the value neurodivergent individuals bring to technical teams. Despite this, research on the contributions of neurodivergent individuals in Software Engineering (SE) remains limited. This interdisciplinary Socio-Technical Grounded Theory study addresses this gap by exploring the experiences of neurodivergent software engineers with ASD and ADHD, examining the cognitive and emotional challenges they face in software teams. Based on interviews and a survey with 25 neurodivergent and 5 neurotypical individuals, our theory describes how neurodivergent cognitive dysfunctions affect SE performance, and how the individuals’ individual journey and various accommodations can regulate this effect. We conclude our paper with a list of inclusive Agile practices, allowing organizations to better support neurodivergent employees and fully leverage their capabilities.

 Tags: "Human/Social", "Gender, equity and diversity", "Process"  
 
Edvaldo Wassouf-Jr, Pedro Fukuda, Awdren Fontão, "Investigating the Developer eXperience of LGBTQIAPN+ People in Agile Teams"

Abstract: Diversity in the software industry is increasingly recognized for its significant advantages, despite the potential for conflicts and challenges. This study investigates the implications of diversity within agile software development teams, particularly focusing on the experiences of LGBTQIAPN+ professionals. Through an opinion survey of 40 participants, we identify critical factors affecting developer satisfaction and retention, revealing that trust, communication, and adequate support are vital for effective collaboration. Our findings indicate that less structured teams often face issues such as discrimination and inadequate inclusion policies, leading to frustration and diminished sprint performance. Moreover, participants reported higher dissatisfaction with in-person work environments, citing psychological discomfort and reduced productivity compared to remote work. This research underscores the need for targeted practices to improve visibility and support for LGBTQIAPN+ professionals, contributing to a deeper understanding of how diversity impacts agile methodologies and developer experience in the software industry.

 Tags: "Human/Social", "Gender, equity and diversity"  
 
Shandler A. Mason, Hank Lenham, Sandeep Kaur Kuttal, "Breaking the Silos: An Actionable Framework for Recruiting Diverse Participants in SE"

Abstract: Inclusive Human-Centric Software Engineering (HCSE) research faces significant challenges in recruiting participants from underrepresented backgrounds, including gender, race, culture, socioeconomic status, disability, religion, sexual orientation, and age. Our study explores the recruitment barriers encountered by HCSE researchers through in-depth, semi-structured interviews with 20 professionals from academia and industry across four continents. Using an inductive approach and open coding of transcribed interview data, we identified 25 key barriers and 20 strategies, categorized into five thematic areas: participant skepticism, study design limitations, logistical and financial constraints, gatekeepers, and researcher well-being. Notably, researchers highlighted barriers such as deteriorating mental health, external criticism of their research focus, and participant reluctance rooted in historical exploitation and perceived risks. To address these challenges, we offer a set of 20 evidence-based, actionable strategies aimed at improving participant outreach and enhancing recruitment practices. Our research culminates in a comprehensive framework to support both novice and experienced researchers in overcoming recruitment barriers, fostering greater inclusion and equity in HCSE studies.

 Tags: "Human/Social", "Gender, equity and diversity"  
 
Rifat Ara Shams, Mojtaba Shahin, Gillian Oliver, Jon Whittle, Waqar Hussain, Harsha Perera, Arif Nurwidyantoro, "Strategies to Embed Human Values in Mobile Apps: What do End-Users and Practitioners Think?"

Abstract: Given the ubiquity of mobile applications (apps) in daily lives, understanding and reflecting end-users' human values (e.g., transparency) in apps has become increasingly important. Violations of end users' values by software applications have been reported in the media and have resulted in a wide range of difficulties for end users. Value violations may bring more and lasting problems for marginalized and vulnerable groups of end-users. This research aims to understand the extent to which the values of Bangladeshi female farmers, marginalized and vulnerable end-users, who are less studied by the software engineering community, are reflected in agriculture apps in Bangladesh. Further to this, we aim to identify possible strategies to embed their values in those apps. To this end, we conducted a mixed-methods empirical study consisting of 13 interviews with app practitioners and four focus groups with 20 Bangladeshi female farmers. The accumulated results from the interviews and focus groups identified 22 values of Bangladeshi female farmers, which the participants expect to be reflected in the agriculture apps. Among these 22 values, 15 values (e.g., accuracy) are already reflected and 7 values (e.g., accessibility) are ignored/violated in the existing agriculture apps. We also identified 14 strategies (e.g., "applying human-centered approaches to elicit values") to address Bangladeshi female farmers' values in agriculture apps.

 Tags: "Human/Social", "User experience", "Mobile SW"  
 
Ahmad Azarnik, Davoud Mougouei, Mahdi Fahmideh, Elahe Mougouei, Hoa Khanh Dam, Arif Ali Khan, Saima Rafi, Javed Khan, Aakash Ahmad, "A First Look at AI Trends in Value-Aligned Software Engineering Publications: Human-LLM Insights"

Abstract: Recent criticism of major social media platforms by the U.S. Senate Judiciary Committee for neglecting child safety and privacy lawsuits against Google over ambiguous location tracking exemplify how software can undermine human values with societal, reputational, and financial impacts. The integration of AI into modern software has further complicated this through inherent challenges like biases and lack of transparency. But AI can also offer opportunities to embed values in software, for instance, by employing natural language processing (NLP) for privacy regulation compliance checks. To explore these opportunities, we have utilized the automated reasoning abilities of ChatGPT, as a large language model (LLM), in combination with human expertise, to study the use of AI in software engineering (SE) publications that address human values (Value-Aligned publications) across some of the leading SE venues from 2022 to 2023. The findings underwent a comprehensive human evaluation, confirming that AI was used in 27% of the value-aligned publications, primarily addressing pragmatic aspects of software, such as Achievement and Security. In contrast, socially focused altruistic values like Equality, Peace, and Social Justice remain underrepresented.

 Tags: "Human/Social", "AI for SE", "Gender, equity and diversity", "Security"  
 
Gennaro Zanfardino, Antinisca Di Marco, Michele Tucci, "Designing a Tool for Evacuation Plan Validation: Multi-Agent Simulations with Persona-Based UI"

Abstract: Natural disasters (such as earthquakes) are unpredictable events that cannot be foreseen, so the unique strategy we have to reduce their impact and the risks for the citizens is to do prevention. In this context, we propose a methodology we followed to develop a highly customizable tool aimed at validating urban evacuation plans. Built with a focus on persona-based user interface (UI) design, the tool leverages software engineering methodologies to ensure scalability, dynamicity (e.g., simulating unpredictable events during the disaster), and adaptive UI for diverse user groups, including urban planners, civil protection agencies, and safety plan managers. By integrating agent-based models with Geographic Information Systems, the tool provides data-driven simulations that can be used to validate evacuation strategies. The tool was evaluated through two case studies conducted considering various urban environments, enabling iterative development through ongoing requirements elicitation and refinement in collaboration with the user groups.

 Tags: "User experience", "Human/Social", "Design/Architecture"  
 
Yeqian Li, Kousar Aslam, "Ethical Issues in Video Games: Insights from Reddit Discussions"

Abstract: Over the past few decades, the video game industry has seen exponential growth, evolving from basic entertainment into a sophisticated medium featuring immersive graphics, intricate storytelling, and highly interactive experiences. This rapid expansion has brought a host of ethical concerns to the forefront, including issues related to violence, gender representation, race, addictive game mechanics, and monetization fairness. These concerns have sparked ongoing debates on social media, yet public discussions on these matters remain largely unresearched. To address this gap, we conducted an exploratory study of ethical issues in video games by analyzing Reddit discussions through both manual analysis and machine learning techniques. We collected and examined 19,843 posts from a diverse set of stakeholders, including game designers, developers, players, and the people related to the players. Our findings offer researchers a foundation for further studies on the impact of specific ethical issues, aids practitioners in the development of more ethically grounded practices and facilitates regulatory bodies for shaping future policies. We also found that machine learning techniques are effective for extracting information about ethical issues in video games from large volumes of Reddit posts.

 Tags: "Human/Social", "Games", "Resp SE and Ethics", "AI for SE"  
 
Sonja M. Hyrynsalmi, Grischa Liebel, Ronnie de Souza Santos, Sebastian Baltes, "Not real or too soft? On the challenges of publishing interdisciplinary software engineering research"

Abstract: The discipline of software engineering (SE) combines social and technological dimensions. It is an interdisciplinary research field. However, interdisciplinary research submitted to software engineering venues may not receive the same level of recognition as more technical and traditional SE subjects, such as software testing. In this study, we conducted a survey of 73 SE researchers and used a mixed-method data analysis approach to investigate their challenges and recommendations in publishing interdisciplinary research in SE. Our results revealed that marginalized groups are more likely to receive negative feedback, and experienced researchers are less likely to change their research direction because of the feedback they receive. We also identified that the challenges of publishing interdisciplinary research in SE can be divided into topic-related and review-related challenges. As a solution to these challenges, our respondents emphasized the importance of highlighting the impact and value of interdisciplinary work for SE, collaborating with experienced researchers, and establishing clearer submission guidelines and new interdisciplinary SE publication venues. Our findings contribute to the understanding of the SE research community of how to better support interdisciplinary research in our field.

 Tags: "Human/Social", "Research Methods", "Gender, equity and diversity"  
 
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