ICSE 2026 Preview

Apr 10, 2026 - ⧖ 5 min

The IEEE/ACM International Conference on Software Engineering (ICSE) is one of the top venues for software engineering research. This post provides an overview of papers from our group that will be presented at co-located events and specific tracks of the conference this year:

The Fall-Off of Bots in Software Engineering [BoatSE]

I am honored and excited to provide a keynote address for the International Workshop on Bots and Agents in Software Engineering (BoatSE)! More details are below, and a follow-up post will be shared at a later date.

  • Abstract: Over the past decade, bots have become embedded in modern software development. Yet empirical evidence suggests many bots fail to achieve sustained adoption and trust. Further, these traditional automation systems will continue to become obsolete with the rise in adoption and capabilities of generative AI agents. Drawing on recent research on bots and real-world development workflows, this keynote will explore the "fall off" by characterizing the shortcomings of bots, relating it to the come up of AI agents in software engineering contexts, and discussing implications for the next generation of bots, agents, and research.

Finding RSEs: Challenges in Recruiting Research Software Engineers for Research [SERS]

Minhyuk Ko, Shawal Khalid, Chris Brown

  • 🔍 Problem: Recruiting research software engineers (RSEs) for empirical SE studies is difficult.

  • 💡 Study: We provide an experience report outlining challenges we faced recruiting RSEs for a participatory design workshop, and propose solutions to overcome these challenges.

Designing Tools to Enhance Best Practices in Research Software Engineering [CHASE]

Minhyuk Ko, Chris Brown

  • 🔍 Problem: RSEs develop software to support scientific discovery, however, they often fail to adopt the best practices in software engineering.

  • 🧪 Study: We conducted two participatory design workshops to uncover development challenges researchers face and co-design novel tools to support development practices in research SE contexts.

  • 📊 Findings: RSEs struggle with debugging and understanding codebases, and face unique challenges related to adopting developer mental models. Participants proposed novel tools to support code translation, code understanding, and communication---leveraging the power of large language models (LLMs).

  • 💡 Implications: We discuss future research directions for designing tools to increase awareness and the adoption of beneficial software engineering practices for research SE.

Political and Ideological Pressure in Software Engineering Research: The Case of DEI Backlash [ICSE FOSE]

Sonja M. Hyrynsalmi, Chris Brown, Alexander Serebrenik, Sebastian Baltes, Letizia Jaccheri

  • 🔍 Problem: Recent political and ideological pressures, particularly related to diversity, equity, and inclusion (DEI), have impacted the software industry---and recently the SE research community.

  • 🧪 Study: We analyzed responses from the FOSE developer survey and provide case examples of DEI backlash in SE research contexts

  • 📊 Findings: Survey responses suggest political and ideological backlash exists within the SE research community, and manifests in different ways across micro, meso, and macro levels.

  • 💡 Implication: We provide suggestions for the SE research community to safeguard and mitigate the negative impacts of political pressure in research contexts.

From Papers to Progress: Rethinking Knowledge Accumulation in Software Engineering [ICSE FOSE]

Jason Cusati, Chris Brown

  • 🔍 Problem: SE research has experienced rapid growth recently, yet we lack sufficient infrastructure and techniques to accumulate, integrate, and reuse knowledge to support long-term progress.

  • 🧪 Study: We analyzed responses from the FOSE developer survey, providing motivation for a knowledge accumulation framework.

  • 📊 Findings: Respondents face challenges with research papers as isolated units, lack of provenance and evidence tracking, and lack incentive structures for research replication.

  • 💡 Implication: We discuss principles for knowledge accumulation and provide a roadmap toward community-based infrastucture for tracking research artifacts.

"I Value LeetCode Over My Coursework": CS Students’ Preparation Strategies and Perceptions of Technical Interviews [ICSE SEET]

Daniel Manesh, Teresa Thomas, Chris Brown, Sang Won Lee

  • 🔍 Problem: Technical interviews involve specific skills that are not covered in computing curricula and need to be developed outside of coursework.

  • 🧪 Study: We interviewd Computer Science students to explore how they prepare for technical interviews and how they perceive technical interviews in relation to their coursework and expected future job activities.

  • 📊 Findings: Participants primarily use LeetCode to prepare in addition to practicing with others. They also find technical interviews irrelevant to their courses and future job tasks, yet prioritize interview preparation over coursework.

  • 💡 Implication: We discuss how educators and industry can better align curricula and hiring practices to support students and their career development.

Exploring the Community of Inquiry in Online Computing Education: Student Perceptions and Opportunities for Generative AI [ICSE SEET]

Tianjia Wang, Chris Brown

  • 🔍 Problem: Online learning provides flexible and accessible learning opportunities for students in computing education, yet introduces challenges such as reduced engagement, lack of real-time support, and limited personal interaction.

  • 🧪 Study: We surveyed computing students with experience taking online classes to understand their perceptions of online learning and opportunities for generative AI in the context of the community of inquiry framework.

  • 📊 Findings: Participants perceive traditional online courses lack social, teaching, and cognitive support for learning, and believe generative AI can enhance community factors through personalized feedback, task decomposition, reduced social pressure, and instructional support.

  • 💡 Implication: We discuss future research directions for using AI to support students’ experiences in online learning environments in computing education contexts.

We are excited to connect with everyone and share these findings at ICSE 2026! These papers reflect ongoing and upcoming themes in our research group, and we hope they provide useful insights and spark meaningful discussions. See you in Rio!

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