Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices

Shehroz Khan; Gaadha Sudheerbabu; Bianca Elena Staicu; Tanwir Ahmad; Dragos Truscan

doi:10.1109/ICSTW64639.2025.10962473

Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices

Informaatioteknologia

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

13 Lataukset (Pure)

Abstrakti

We present an automated fault localization technique that can assist developers to localize effectively faults in Python programs. The proposed method uses spectrum-based fault localization techniques, program slicing, and graph-based visualization to formulate an efficient method for reducing the effort needed in fault localization. The approach takes the source code of a program, a set of passed and failed tests and collects the program spectra information by executing the tests. A tool, FaultLocalizer, facilitates the generation of a call graph for inter-procedural dependency analysis and annotated control flow graphs for different modules with spectra information and suspiciousness scores. The focus of the approach is on the visual analysis of the source code, and it is intended to complement existing fault localization approaches. The effectiveness of the proposed approach is evaluated on a set of buggy Python programs. The results show that the approach reduces debugging efforts and can be applied to programs with conditional branching.

Alkuperäiskieli	Englanti
Otsikko	2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025
Toimittajat	Anna Rita Fasolino, Sebastiano Panichella, Aldeida Aleti, Ali Mesbah
Kustantaja	IEEE
Sivut	217-225
ISBN (elektroninen)	979-8-3315-3467-7
ISBN (painettu)	979-8-3315-3468-4
DOI - pysyväislinkit	https://doi.org/10.1109/ICSTW64639.2025.10962473
Tila	Julkaistu - 16 huhtik. 2025
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) - Kesto: 31 maalisk. 2025 → …

Julkaisusarja

Nimi	2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025

Konferenssi

Konferenssi	IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
Ajanjakso	31/03/25 → …

Rahoitus

This work was partially funded by the the European Union's Horizon 2020 research and innovation programme, under grant agreement No. 957212 (VeriDevOps) and by Business Finland via the Virtual Sea Trial project (VST), under grant 7187/31/2023.

YK:n kestävän kehityksen tavoitteet

Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:

SDG 9 – Teollisuus, innovaatiot ja infrastruktuuri

Pääsy asiakirjaan

10.1109/ICSTW64639.2025.10962473

VST: Virtual Sea Trial
Truscan, D. (Vastuullinen tutkija), Hellström, M. (Vastuullinen tutkija), Porres Paltor, I. (CoPI), Ahmad, T. (CoI), Chariyarupadannayil Sudheerbabu, G. (Projektityöntekijä), Yaseen, A. (Projektityöntekijä), Khan, S. (Projektityöntekijä), Mughees, A. (Projektityöntekijä) & Kulshreshtha, A. (Projektityöntekijä)
Business Finland
01/01/24 → 31/12/26
Projekti: Industry/Business Finland

Viittausmuodot

Khan, S., Sudheerbabu, G., Elena Staicu, B., Ahmad, T., & Truscan, D. (2025). Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices. teoksessa A. R. Fasolino, S. Panichella, A. Aleti, & A. Mesbah (Toimittajat), 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025 (Sivut 217-225). (2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025). IEEE. https://doi.org/10.1109/ICSTW64639.2025.10962473

Khan, Shehroz ; Sudheerbabu, Gaadha ; Elena Staicu, Bianca et al. / Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices. 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025. Toimittaja / Anna Rita Fasolino ; Sebastiano Panichella ; Aldeida Aleti ; Ali Mesbah. IEEE, 2025. Sivut 217-225 (2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025).

@inproceedings{aab186353eef4b29b81c598fc9b727c0,

title = "Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices",

abstract = "We present an automated fault localization technique that can assist developers to localize effectively faults in Python programs. The proposed method uses spectrum-based fault localization techniques, program slicing, and graph-based visualization to formulate an efficient method for reducing the effort needed in fault localization. The approach takes the source code of a program, a set of passed and failed tests and collects the program spectra information by executing the tests. A tool, FaultLocalizer, facilitates the generation of a call graph for inter-procedural dependency analysis and annotated control flow graphs for different modules with spectra information and suspiciousness scores. The focus of the approach is on the visual analysis of the source code, and it is intended to complement existing fault localization approaches. The effectiveness of the proposed approach is evaluated on a set of buggy Python programs. The results show that the approach reduces debugging efforts and can be applied to programs with conditional branching.",

keywords = "Spectrum-based fault localization, program slicing, program spectra",

author = "Shehroz Khan and Gaadha Sudheerbabu and \{Elena Staicu\}, Bianca and Tanwir Ahmad and Dragos Truscan",

year = "2025",

month = apr,

day = "16",

doi = "10.1109/ICSTW64639.2025.10962473",

language = "English",

isbn = "979-8-3315-3468-4",

series = "2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025",

publisher = "IEEE",

pages = "217--225",

editor = "Fasolino, \{Anna Rita\} and Sebastiano Panichella and Aldeida Aleti and Ali Mesbah",

booktitle = "2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025",

address = "United States",

note = "IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) ; Conference date: 31-03-2025",

}

Khan, S , Sudheerbabu, G, Elena Staicu, B, Ahmad, T & Truscan, D 2025, Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices. julkaisussa AR Fasolino, S Panichella, A Aleti & A Mesbah (toim), 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025. 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025, IEEE, Sivut 217-225, IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 31/03/25. https://doi.org/10.1109/ICSTW64639.2025.10962473

Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices. / Khan, Shehroz ; Sudheerbabu, Gaadha; Elena Staicu, Bianca et al.
2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025. toim. / Anna Rita Fasolino; Sebastiano Panichella; Aldeida Aleti; Ali Mesbah. IEEE, 2025. s. 217-225 (2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025).

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

T1 - Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices

AU - Khan, Shehroz

AU - Sudheerbabu, Gaadha

AU - Elena Staicu, Bianca

AU - Ahmad, Tanwir

AU - Truscan, Dragos

PY - 2025/4/16

Y1 - 2025/4/16

N2 - We present an automated fault localization technique that can assist developers to localize effectively faults in Python programs. The proposed method uses spectrum-based fault localization techniques, program slicing, and graph-based visualization to formulate an efficient method for reducing the effort needed in fault localization. The approach takes the source code of a program, a set of passed and failed tests and collects the program spectra information by executing the tests. A tool, FaultLocalizer, facilitates the generation of a call graph for inter-procedural dependency analysis and annotated control flow graphs for different modules with spectra information and suspiciousness scores. The focus of the approach is on the visual analysis of the source code, and it is intended to complement existing fault localization approaches. The effectiveness of the proposed approach is evaluated on a set of buggy Python programs. The results show that the approach reduces debugging efforts and can be applied to programs with conditional branching.

AB - We present an automated fault localization technique that can assist developers to localize effectively faults in Python programs. The proposed method uses spectrum-based fault localization techniques, program slicing, and graph-based visualization to formulate an efficient method for reducing the effort needed in fault localization. The approach takes the source code of a program, a set of passed and failed tests and collects the program spectra information by executing the tests. A tool, FaultLocalizer, facilitates the generation of a call graph for inter-procedural dependency analysis and annotated control flow graphs for different modules with spectra information and suspiciousness scores. The focus of the approach is on the visual analysis of the source code, and it is intended to complement existing fault localization approaches. The effectiveness of the proposed approach is evaluated on a set of buggy Python programs. The results show that the approach reduces debugging efforts and can be applied to programs with conditional branching.

KW - Spectrum-based fault localization

KW - program slicing

KW - program spectra

U2 - 10.1109/ICSTW64639.2025.10962473

DO - 10.1109/ICSTW64639.2025.10962473

M3 - Published conference proceeding

SN - 979-8-3315-3468-4

T3 - 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025

SP - 217

EP - 225

BT - 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025

A2 - Fasolino, Anna Rita

A2 - Panichella, Sebastiano

A2 - Aleti, Aldeida

A2 - Mesbah, Ali

PB - IEEE

T2 - IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

Y2 - 31 March 2025

ER -

Khan S , Sudheerbabu G, Elena Staicu B, Ahmad T , Truscan D. Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices. julkaisussa Fasolino AR, Panichella S, Aleti A, Mesbah A, toimittajat, 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025. IEEE. 2025. s. 217-225. (2025 IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025). doi: 10.1109/ICSTW64639.2025.10962473

Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices

Abstrakti

Julkaisusarja

Konferenssi

Rahoitus

YK:n kestävän kehityksen tavoitteet

Pääsy asiakirjaan

Sormenjälki

Projektit

VST: Virtual Sea Trial

Viittausmuodot