Software Engineering Techniques and Practices

Latest papers

• SWE-MILE: Asynchronous Potential-Induced Milestone Credit Assignment for Long-Horizon Software Engineering Agents

  Chaoqun Cui, Hao Zhou, Meiqi Chen, Fandong Meng, Wenji Mao · 29 September 2026

  Long-horizon software engineering (SWE) agents trained with reinforcement learning with verifiable rewards (RLVR) typically receive only terminal outcome supervision, making it difficult to distinguish productive actions from redundant exploration or functional regressions. We propose SWE-MILE, an a…

• Developing a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development

  Viktor Kjellberg, Srijita Basu, Simin Sun, Farnaz Fotrousi, Miroslaw Staron · 28 September 2026

  The emergence of AI agents is expected to reshape software engineering by moving beyond AI as assistants towards systems capable of planning, executing, and evaluating development tasks with increasing autonomy. This transition is particularly significant for embedded software organizations, where s…

• What Will Remain Human in Software Architecture? A Focus Group Report

  Uwe van Heesch, Olaf Zimmermann, Christian Kohls · 28 September 2026

  AI development agents are increasingly used to support and partially automate software architecture tasks. To explore how practitioners perceive this shift, specifically what changes, what remains, and what new responsibilities emerge, we conducted a focus group at the 31st European Conference on Pa…

• Judgment-Centred Software Engineering Education: A Post-Hype Review and Framework for AI-Augmented Learning

  Qusay H. Mahmoud · 25 September 2026

  Generative artificial intelligence has moved from a disruptive novelty to a recurring part of software-development and computing-education workflows, while software agents are beginning to act across repositories, command lines, browsers, tests, and other tools. The educational problem is no longer …

• Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education

  Anamaria Mojica-Hanke, David Nader Palacio, Denys Poshyvanyk, Mario Linares-V\'asquez, Steffen Herbold · 18 September 2026

  Context: Machine Learning (ML) significantly impacts Software Engineering (SE), but studies mainly focus on practitioners, neglecting researchers. This overlooks practices and challenges in teaching, researching, or reviewing ML applications in SE. Objective: This study aims to contribute to the k…

• Beyond the Personal Assistant: How Expectations for Enterprise AI in Teamwork Diverged as Generative AI Took Shape, 2023-2025

  Qing Xiao, Xinlan Emily Hu, Mark E. Whiting, Arvind Karunakaran, Hong Shen, Hancheng Cao · 15 September 2026

  HCI often draws on users' articulated needs and expectations to explore design opportunities for emerging technologies. Yet, these accounts are shaped by how technologies take form over time. We examine this dynamic through a two-phase interview study of enterprise AI in a project-based software dev…

• When Digitalization Transforms Itself: AI, Software, and the Next Technical Order

  Ina K. Schieferdecker · 15 September 2026

  Agentic artificial intelligence (AI) marks a new phase of digitalization: digitalization is beginning to act back upon its own technical production base. Whereas earlier phases aimed at digitizing analog information, automating processes, and building digital value networks, AI is increasingly takin…

• Beyond Code Generation: Reliability, Verification, and Cost Economics in the Agentic Software Development Lifecycle

  Happy Bhati · 7 September 2026

  AI coding systems are moving from autocomplete and chat toward agents that can inspect repositories, edit multiple files, run tools, write tests, open pull requests, and work for long periods with limited supervision. This capability changes the bottleneck in software delivery. Recent field studies …

• An Empirical Study on Learning Paths and Gender Dynamics in Scrum Master Roles

  Manuela Petrescu, Paul Razvan Petrescu · 7 September 2026

  Context: Agile development methodology has been widely adopted by industry and the demand for experienced professionals in Agile-related roles is persistently high. Objectives: We focus on the learning path for a Scrum Master role in multicultural software companies and investigate the role in relat…

• The Psychological Costs of Artificial Intelligence Adoption in Software Engineering

  Adam Alami, Elda Paja, Abhishek Tiwari · 4 September 2026

  Artificial intelligence (AI) is increasingly used to augment software engineering (SE) workflows. While code generation remains the main use case, organizations are actively seeking AI integration in other practices such as test cases generation and code reviews. Organizational AI adoption strategie…

• Antipatterns in AI-assisted Qualitative Data Analysis: A Catalog of Temptations and Pitfalls for Software Engineering Researchers

  Rashina Hoda, Carolyn Seaman, Victoria Gomes, Rodrigo Spinola · 31 August 2026

  AI-assisted qualitative data analysis (QDA) offers unprecedented opportunities to streamline software engineering (SE) research, yet uncritical use risks compromising analytical rigor and flooding the field with accelerated production of low-quality research. While tactical best practices will natur…

• Detecting Soft Skills in ML Engineering Roles CVs

  Aidin Azamnouri, Nouran Ayad, Justus Bogner, Stefan Wagner · 12 August 2026

  Soft skills shape collaboration among ML engineers, data scientists, and software engineers building ML-enabled systems, yet what we know about them comes almost entirely from the demand side. Job advertisements, surveys, and hiring manager interviews capture what employers ask for. How candidates t…

• AI-assisted Script Management for Requirements Elicitation Interviews

  Anmol Singhal, Paulo Carvalho, Travis Breaux · 4 August 2026

  Requirements elicitation interviews require interviewers to balance topic coverage, active listening, and adaptive probing while responding to stakeholders in real time. Although prior work has explored AI support for isolated interviewing tasks, such as script generation and follow-up question gene…

• Where Is the Cost of Third-Party API Routers in Agentic Software Development?

  Donghao Fu, Jingxin Li, Xue Jiang, Yihong Dong · 30 July 2026

  Third-party API routers have become a common layer that unifies access across increasingly diverse LLM providers. In coding-agent workflows, high-autonomy operation is widely adopted because it reduces interaction overhead. As a result, a third-party API router, which sits between the agent and the …

• Preliminary Guidelines for Using and Evaluating GenAI Tools to Support Systematic Literature Reviews

  Barbara Kitchenham, Sebasti\'an Pizard, Lech Madeyski, Ronnie de Souza Santos, Martin Shepperd, David Budgen · 29 July 2026

  Context: Generative AI (GenAI) and Large Language Models (LLMs) are increasingly used for academic tasks in software engineering and beyond, including systematic literature reviews (SLRs). However, while capable of summarizing text, there is no guarantee they can meet the rigour, reliability, and tr…

• How Do Practitioners Build SE Agents? Insights from a Mixed-Methods Study

  Yunbo Lyu, David Williams, Jieke Shi, Zhensu Sun, Chao Peng, Zhou Yang, Federica Sarro, David Lo · 14 July 2026

  The rise of Software Engineering (SE) agents, i.e., LLM-based agents that can understand large codebases and carry out engineering tasks with limited human intervention, has been marked by rapid advances and adoption, but little is known about how developers build these systems in practice: existing…

• Inside the Skill Market: From Software Engineering Activities to Reusable Agent Skills

  Jialun Cao, Xinru Yan, Songqiang Chen, Yaojie Lu, Zhongxin Liu, Shing-Chi Cheung · 13 July 2026

  Software engineering (abbrev. SE) has continuously evolved through increasingly powerful forms of reuse, from source code and libraries to components and services. Recent advances in AI agents have introduced a potentially new reusable artifact: skills. Emerging agent skill repositories and marketpl…

• A Retrieval-Augmented Framework for Detecting and Resolving Pragmatic Ambiguities in Natural Language Requirements

  Pavithra PM Nair, Preethu Rose Anish · 7 July 2026

  Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the inherent ambiguity in NLRs can pose significant challenges. In particular, some requirements may be misinterpreted due to varying contextual knowledge a…

• Reasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study

  Achint Mehta · 3 July 2026

  Agentic coding assistants are increasingly given extra capabilities, such as browser based testing tools and design oriented system prompts, on the assumption that more capability yields better software. This study tested that assumption directly. Ninety independent agent runs built the same applica…

• Risk Architecture for AI-Native Engineering Teams: An Organizational Framework for Agentic System Governance

  Laxmipriya Ganesh Iyer · 3 July 2026

  Engineering management research has produced mature frameworks for software risk: ownership by feature, escalation by severity, and assurance by test coverage. These frameworks implicitly assume deterministic behavior, discrete and auditable change events, and clear component-to-owner mappings. Team…

• UA-ChatDev: Uncertainty-Aware Multi-Agent Collaboration for Reliable Software Development

  Temitayo Olamilekan Ogunsusi, Lijun Qian, Xishuang Dong · 3 July 2026

  Software development is a complex task that demands cooperation among agents with diverse roles. Large language models (LLMs) have enabled autonomous multi-agent software development frameworks that leverage role-based collaboration to automate requirements analysis, coding, testing, and refinement.…

• Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study

  Mirko Perkusich, Danyllo Albuquerque, Jo\~ao Paiva, Robson Vilar, Emanuel Dantas, Ademar Fran\c{c}a de Sousa Neto, Rohit Gheyi, Kyller Gorg\^onio, Angelo Perkusich · 2 July 2026

  Large Language Models (LLMs) are increasingly used in Agile Software Development for documentation, coaching, and training. As practitioners adopt these tools to prepare for certifications such as Professional Scrum Master (PSM), a key question is whether LLMs can reliably reason about Scrum, a fram…

• Comparing Large Language Models on Scrum Certification-Style Questions: Accuracy, Stability, and Error Patterns

  Robson Alves Vilar, Emanuel Dantas Filho, Ademar Fran\c{c}a de Sousa Neto, Mirko Perkusich, Danyllo Wagner Albuquerque, Jo\~ao Paiva, Kyller Gorg\^onio, Angelo Perkusich · 2 July 2026

  Large Language Models (LLMs) are increasingly used in exam- and certification-style question answering tasks, where their ability to retrieve, interpret, and apply domain-specific knowledge can be systematically assessed. In Software Engineering, such settings are particularly relevant when question…

• Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment

  Ali Pourghasemi Fatideh, Wilder Baldwin, Maria Dhakal, Collin McMillan, Sepideh Ghanavati · 24 June 2026

  LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional correctness. This leaves a critical gap in assessing the quality and accuracy of these conversations when handling Non-Functional Requirements (NFRs),…

• Skills for the future software profession: beyond agentic AI!

  Sungmin Kang, Baishakhi Ray, Abhik Roychoudhury · 23 June 2026

  As coding agents are rapidly changing software engineering, a natural question is: what are the core skills needed by future software engineers? To identify where software engineering is headed and thus what skills will be needed, we summarize the results of two round-tables with researchers and ind…