ESEIW 2026
Sun 4 - Fri 9 October 2026 München, Germany

This program is tentative and subject to change.

Fri 9 Oct 2026 11:00 - 11:15 at Jupiter - Maintenance, Refactoring and Technical Debt

\textbf{Background.} When developers write a TODO or FIXME comment, they are explicitly admitting that the code is suboptimal: a built-in warning that this logic deserves extra scrutiny. Yet it is an open question whether Self-Admitted Technical Debt (SATD) actually receives that scrutiny in the form of software testing. \textbf{Aim.} We aim to characterize the relationship between SATD and testing across three dimensions: the extent to which SATD-affected code is covered by existing tests, whether developers synchronize test additions with debt resolution, and whether such testing affects the long-term observability of resulting defects. \textbf{Method.} For that, we conducted an empirical study on eight open-source Java projects, analyzing test coverage of 784 SATD instances identified in the latest releases and performing a longitudinal examination of 5,175 SATD removal events. \textbf{Results.} Our results show that while 60.7% of SATD-affected code is covered by existing test suites, developers rarely synchronize test modifications with debt resolution; manual inspection confirms that only 3.4% of SATD removal commits include new tests specifically targeting the resolved debt (vs. 12.5% that co-add tests in the same commit). Longitudinal analysis further suggests that SATD resolutions exhibit nearly identical localized bug induction rates within short-to-medium-term windows regardless of test modifications. However, over a longer, unrestricted observation window, a slight divergence emerges where the test-added group reaches a higher cumulative defect alignment probability (6.32% vs. 4.37%), a counterintuitive trend potentially driven by the selective testing of inherently complex components. \textbf{Conclusion.} Developers treat SATD repayment as an ordinary code change rather than as a high-risk maintenance activity: most debt removals proceed without targeted verification, despite the developer’s own prior flag that the code is suboptimal.

This program is tentative and subject to change.

Fri 9 Oct

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

11:00 - 12:30
11:00
15m
Talk
Is Self-Admitted Technical Debt Tested? An Empirical Study of Coverage, Co-change, and Impact
ESEM - Technical Track
Suzuka Yoshimoto NARA Institute of Science and Technology, Kosei Horikawa Nara Institute of Science and Technology, Daniel Feitosa University of Groningen, Yutaro Kashiwa Nara Institute of Science and Technology, Hajimu Iida Nara Institute of Science and Technology
11:15
15m
Talk
Balancing Green and Clean Code: Prompting for LLM-Based Refactoring
ESEM - Technical Track
Feray Gulu-zada University of Tartu, Hina Anwar University of Tartu
11:30
15m
Talk
A Catalog of Transformations to Remove Dockerfile smells
ESEM - Technical Track
Eduardo Barros Federal University of Alagoas, Brazil, Márcio Ribeiro Federal University of Alagoas, Brazil, Luana Martins University of Salerno, Valeria Pontillo Gran Sasso Science Institute, Fabio Palomba University of Salerno, Baldoino Fonseca Federal University of Alagoas (UFAL), Rohit Gheyi Federal University of Campina Grande, Ivan Machado Federal University of Bahia (UFBA)
11:45
15m
Talk
Bigger Is Not Always Better: Performance and Sustainability Trade-offs in LLMs for Python Bug-Fixing Tasks
ESEM - Technical Track
Syed Fakhar Abbas Naqvi University of Tartu, Hina Anwar University of Tartu
12:00
15m
Talk
Does Spec-Driven Development Reduce Defects? An Empirical Test of Industry Claims Across 119 Open-Source Repositories
ESEM - Software Engineering in Practice Track
Brenn Hill Unaffiliated
12:15
15m
Talk
Reducing Labeling Effort in Architecture Technical Debt Detection through Active Learning and Explainable AI
ESEM - Journal First Track
Edi Sutoyo Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Paris Avgeriou Univ. of Gronningen , Andrea Capiluppi University of Groningen