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Documents authored by Treude, Christoph

Document
Emerging Results, Vision & Reflection Track Paper
DOI: 10.4230/LIPIcs.ESEM.2026.54
An Exploratory Study of Agent Plans for Agentic AI Coding Tools in Open-Source Software

Authors: Muhammad Auwal Abubakar, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Jie M. Zhang, Christoph Treude, Sebastian Baltes, and Matthias Galster

Published in: LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)

Abstract
Repository-level configuration artifacts allow developers to provide guidance for agentic AI coding tools, e.g., Claude Code, Gemini. Although prior research has examined repository-shared context files that capture project-level instructions and conventions (e.g., AGENTS.md files), little is known about more task-oriented artifacts such as Agent Plans. We present an exploratory study of Agent Plans in open-source software repositories, examining how plan files are preserved, which development activities they support, and what information they provide to guide agent execution. We screened 36,710 GitHub repositories belonging to engineered software projects and identified 85 Markdown plan files from 10 repositories. Within this concentrated corpus, Agent Plans supported several kinds of software engineering work, including maintenance, design, construction, quality-related work, and process support. They also provided task-oriented execution guidance, most commonly through implementation steps, concrete files and locations, and testing and validation information. Overall, repository-preserved Agent Plans in these tool-specific directories appear to be a narrow but informative artifact for studying task intent and execution guidance in human-agent workflows.
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Muhammad Auwal Abubakar, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Jie M. Zhang, Christoph Treude, Sebastian Baltes, and Matthias Galster. An Exploratory Study of Agent Plans for Agentic AI Coding Tools in Open-Source Software. In 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 394, pp. 54:1-54:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{abubakar_et_al:LIPIcs.ESEM.2026.54,
  author =	{Abubakar, Muhammad Auwal and Mohsenimofidi, Seyedmoein and Lulla, Jai Lal and Zhang, Jie M. and Treude, Christoph and Baltes, Sebastian and Galster, Matthias},
  title =	{{An Exploratory Study of Agent Plans for Agentic AI Coding Tools in Open-Source Software}},
  booktitle =	{20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)},
  pages =	{54:1--54:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-450-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{394},
  editor =	{Feldt, Robert and Paasivaara, Maria and Mendez, Daniel and Wagner, Stefan and Bar\'{o}n, Marvin Mu\~{n}oz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.54},
  URN =		{urn:nbn:de:0030-drops-280222},
  doi =		{10.4230/LIPIcs.ESEM.2026.54},
  annote =	{Keywords: Agentic AI Coding Tools, Configuration Mechanisms, Plans}
}
Document
Software Engineering in Practice Track Paper
DOI: 10.4230/LIPIcs.ESEM.2026.82
Can LLMs Identify Missing Elements in Requirements Elicitation? An Empirical Evaluation Using Production-Derived User Stories in an Industry Setting

Authors: Vinay Kabadi, Abhiram Wuntakal, Naresh Gutha, Lahiri Bellarykar, Xuan Bach D. Le, Patanamon Thongtanunam, and Christoph Treude

Published in: LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)

Abstract
Business Requirements often fail to fully capture the complete set of system requirements they intend to describe, resulting in under-specification and measurable gaps between documented requirements and production-ready implementations. While experienced business analysts attempt to mitigate these gaps using domain expertise, the resulting artifacts often remain incomplete. This study uses Cross-Pollination, a domain-agnostic methodology for transforming incomplete natural language Business Requirements into comprehensive, production-grade functional user stories. To evaluate the completeness of LLM-generated user stories, the study systematically benchmarks them against realistic production artifacts. It further investigates the capability of Large Language Models (LLMs) to bridge the coverage gap between human-authored backlogs and production systems. It identifies the requirements that are overlooked during human-driven elicitation but are recovered through an LLM-assisted approach. The cross-pollination technique is a structured multi-phase methodology supported by a gap analysis taxonomy and a domain complexity calibration mechanism to establish a minimum baseline for production readiness. The methodology is applied across real-world domains, and a comparative evaluation of analyst-authored, LLM-generated, and production-derived user stories is conducted. Empirical results demonstrate that a substantial proportion of requirement gaps can be systematically identified and addressed through this approach. The findings indicate that Cross-Pollination provides a reproducible and scalable methodology for translating natural-language requirements into more complete and production-aligned user stories. The results demonstrate that while analysts produce precise requirements, LLM-generated user stories achieve higher recall across all evaluated domains and are effective in uncovering implicit and non-obvious requirements. These findings indicate that an integrated approach, with LLM-assisted elicitation functioning as a complementary mechanism to human expertise, produces more comprehensive and reliable requirement backlogs than either method independently.
Cite as

Vinay Kabadi, Abhiram Wuntakal, Naresh Gutha, Lahiri Bellarykar, Xuan Bach D. Le, Patanamon Thongtanunam, and Christoph Treude. Can LLMs Identify Missing Elements in Requirements Elicitation? An Empirical Evaluation Using Production-Derived User Stories in an Industry Setting. In 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 394, pp. 82:1-82:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{kabadi_et_al:LIPIcs.ESEM.2026.82,
  author =	{Kabadi, Vinay and Wuntakal, Abhiram and Gutha, Naresh and Bellarykar, Lahiri and Bach D. Le, Xuan and Thongtanunam, Patanamon and Treude, Christoph},
  title =	{{Can LLMs Identify Missing Elements in Requirements Elicitation? An Empirical Evaluation Using Production-Derived User Stories in an Industry Setting}},
  booktitle =	{20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)},
  pages =	{82:1--82:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-450-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{394},
  editor =	{Feldt, Robert and Paasivaara, Maria and Mendez, Daniel and Wagner, Stefan and Bar\'{o}n, Marvin Mu\~{n}oz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.82},
  URN =		{urn:nbn:de:0030-drops-280500},
  doi =		{10.4230/LIPIcs.ESEM.2026.82},
  annote =	{Keywords: Software Engineering, Requirement Elicitation, Large Language Model (LLM), User Stories}
}

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