This paper presents PyResBugs, a curated dataset of residual bugs, i.e., defects that persist undetected during traditional testing but later surface in production - collected from major Python frameworks. Each bug in the dataset is paired with its corresponding fault-free (fixed) version and annotated with multi-level natural language (NL) descriptions. These NL descriptions enable natural language-driven fault injection, offering a novel approach to simulating real-world faults in software systems. By bridging the gap between Software Fault Injection techniques and real-world representativeness, PyResBugs provides researchers with a high-quality resource for advancing AI-driven automated testing in Python systems.
PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection / Cotroneo, Domenico; De Rosa, Giuseppe; Liguori, Pietro. - (2025), pp. 146-150. ( 2nd IEEE/ACM International Conference on AI Foundation Models and Software Engineering, FORGE 2025 can 2025) [10.1109/forge66646.2025.00024].
PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection
Cotroneo, Domenico;Liguori, Pietro
2025
Abstract
This paper presents PyResBugs, a curated dataset of residual bugs, i.e., defects that persist undetected during traditional testing but later surface in production - collected from major Python frameworks. Each bug in the dataset is paired with its corresponding fault-free (fixed) version and annotated with multi-level natural language (NL) descriptions. These NL descriptions enable natural language-driven fault injection, offering a novel approach to simulating real-world faults in software systems. By bridging the gap between Software Fault Injection techniques and real-world representativeness, PyResBugs provides researchers with a high-quality resource for advancing AI-driven automated testing in Python systems.| File | Dimensione | Formato | |
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