Divergence-Driven Debugging: Understanding Behavioral Changes Between Two Program Versions

Daily software changes present an inherent risk of introducing bugs. To understand such bugs, it is crucial to understand why specific changes introduced the bugs. This is difficult and time-consuming. We propose Divergence-Driven Debugging, an approach using a debugger for detecting execution divergences between two versions of the same program. Developers can explore both versions' execution in full and compare them based on the detected divergences. We evaluate our approach on a bug scenario and show that our debugger highlights the live state and behavior required to understand why the changes produce the bug and to identify its root cause.

Authors

Institutions

Publication Details

Published
2025-04-27
DOI
https://doi.org/10.1109/icpc66645.2025.00031
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Divergence-Driven Debugging: Understanding Behavioral Changes Between Two Program Versions

Anne Etien, Steven Costiou, Imen Sayar, Rémi Dufloer
Innovative Teaching and Learning Methods
article

Divergence-Driven Debugging: Understanding Behavioral Changes Between Two Program Versions

Anne Etien, Steven Costiou, Imen Sayar, Rémi Dufloer
article en

Abstract

Daily software changes present an inherent risk of introducing bugs. To understand such bugs, it is crucial to understand why specific changes introduced the bugs. This is difficult and time-consuming. We propose Divergence-Driven Debugging, an approach using a debugger for detecting execution divergences between two versions of the same program. Developers can explore both versions' execution in full and compare them based on the detected divergences. We evaluate our approach on a bug scenario and show that our debugger highlights the live state and behavior required to understand why the changes produce the bug and to identify its root cause.

Centre National de la Recherche Scientifique (FR), Université de Lille (FR), École Centrale de Lille (FR)
Openalex Percentile: Top 86%
Innovative Teaching and Learning Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.