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.
2025
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].
File in questo prodotto:
File Dimensione Formato  
PyResBugs_A_Dataset_of_Residual_Python_Bugs_for_Natural_Language-Driven_Fault_Injection.pdf

solo utenti autorizzati

Tipologia: Versione Editoriale (PDF)
Licenza: Copyright dell'editore
Dimensione 418.53 kB
Formato Adobe PDF
418.53 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1008379
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact