Abstract
dc:description.abstractDebugging is a challenging and time-consuming process in software life-cycle. The focus of the thesis is to improve the accuracy of existing fault localization (FL) techniques. We experimented with several source code line level features such as line commit size, line recency, and line length to arrive at a new fault localization technique. Based on our experiments, we propose a novel enhanced cost-aware fault localization (ECFL) technique by combining line length with the existing selected baseline fault localization techniques. ECFL improves the accuracy of DStar (Baseline 1), CombineFastestFL (Baseline 2), and CombineFL (Baseline 3) by locating 81%, 58%, and 30% more real faults respectively in Top-1 evaluation metric. In comparison with the baseline techniques, ECFL requires a marginal additional time (on an average, 5 seconds per bug) and data while providing a significant improvement in accuracy. The source code line features also improve the baseline fault localization techniques when ''learning to rank'' SVM machine learning approach is used to combine the features. We also provide an infrastructure to facilitate future research on combining new source code line features with other fault localization techniques.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Computer Science and Applications
- Department dc:contributor.department
- Computer Science
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Nachimuthu Nallasamy, Kanagaraj
- Chair dc:contributor.committeechair
-
- Servant Cortes, Francisco Javier
- Committee members dc:contributor.committeemember
-
- Prakash, B. Aditya
- Meng, Na
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:21387
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/90575