Virginia Tech
Strip-Miner: Automatic Bug Detection in Large Software Code with Low False Positive Rate
Abstract
dc:description.abstractThere are a number of techniques for automatic bug detection, most of them have a high false positive rate when used in practice. This work proposes an approach, named Strip-Miner, that combines simple dependency analysis of code with a data mining technique "frequent itemset mining" to reduce the false positive rate. We adopt a two phase approach 1) finding the potential bugs and 2) filtering the false positive ones. In the first phase we extract code elements and dependencies among them using static analysis and frequent itemset mining to find programming patterns where a deviation from these patterns is considered as a potential bug. In the second phase, we use the extracted dependencies to build dependency chains between program elements in a programming pattern and a lack of such a chain potentially makes a bug false positive. Our evaluation on a set of 7 benchmarks consisting of large software code including OpenSSL, PostgreSQL, Git, FFMPEG, SQLite, Binutils and Putty shows that combining simple de- pendency analysis with pattern mining can significantly decrease the number of generated bugs. Using our approach we are able to reduce the number of generated bugs by up to 99.9% with a false positive rate of 65.19% and true positive rate of 34.18% on average as compared to an earlier frequent itemset mining based approach "PR-Miner".
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
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Ibrar, Fahad
- Chair dc:contributor.committeechair
-
- Hicks, Matthew
- Committee members dc:contributor.committeemember
-
- Servant Cortes, Francisco Javier
- Butt, Ali R.
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:25403
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/97934