AN ANALYTICAL STUDY ON CHALLENGES IN SOFTWARE FAULT  LOCALISATION

Ajeet Kumar,Dr. I B Lal

AN ANALYTICAL STUDY ON CHALLENGES IN SOFTWARE FAULT LOCALISATION

Authors

Ajeet Kumar,Dr. I B Lal

Keywords:

Software Fault Localisation, Automated Debugging, Spectrum-Based Fault Localisation, Machine Learning, Large Language Models, Software Testing, Software Maintenance, Empirical Software Engineering.

Abstract

Software Fault Localisation (SFL) is a critical, yet notoriously challenging, phase in the softwaredebugging process, aimed at identifying the exact code locations responsible for failures. Despitedecades of research and the development of numerous automated techniques—from spectrum based and statistical debugging to modern learning-based approaches

References

Haghighatkhah, A.; Oivo, M.; Banijamali, A.; Kuvaja, P. Improving the state of automotive software engineering. IEEE Softw. 2017, 34, 82–86. [Google Scholar] [CrossRef]

Downloads

Published

2024-10-03

How to Cite

Ajeet Kumar,Dr. I B Lal. (2024). AN ANALYTICAL STUDY ON CHALLENGES IN SOFTWARE FAULT LOCALISATION. Journal of Computational Analysis and Applications (JoCAAA), 33(07), 3276–2389. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4717