Evaluating the Predictive Power of Software Metrics for Fault Localization
Fault localization remains a critical challenge in software engineering, directly impacting debugging efficiency and software quality. This study investigates the predictive power of various software metrics for fault localization by framing the task as a multi-class classification problem and evalu...
Saved in:
| Main Authors: | Issar Arab, Kenneth Magel, Mohammed Akour |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Computers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-431X/14/6/222 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Branch Drift: A Visually Explainable Metric for Consistency Monitoring in Collaborative Software Development
by: Karl Kegel, et al.
Published: (2025-01-01) -
Enhanced Software Testing Model Under Software Warranty Policy Considering Debugger Learning and Time Postponement Factors
by: Wang Li, et al.
Published: (2025-01-01) -
LLMs: A game-changer for software engineers?
by: Md. Asraful Haque
Published: (2025-03-01) -
Mathematical model of work optimisation in the development of automated information systems
by: G.M. Abildinova, et al.
Published: (2025-01-01) -
Value‐oriented quality metrics in software development: Practical relevance from a software engineering perspective
by: Philipp Haindl, et al.
Published: (2022-04-01)