Maestro: a platform for benchmarking automatic program repair tools on software vulnerabilities

• Type: Article in International Conference Proceedings Book
• Date: 2022

Authors

Pinconschi, E (Author) Other; Bui, QC (Author) Other; Rui Abreu (Author) FEUP; Adão, P (Author) Other; Scandariato, R (Author) Other

Conference proceedings International

Title: ISSTA 2022 - Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis

Pages: 789-792

Indexing

Scopus

Other information

Authenticus ID: P-00X-21G

DOI: 10.1145/3533767.3543291

Abstract (EN): Automating the repair of vulnerabilities is emerging in the field of software security. Previous efforts have leveraged Automated Program Repair (APR) for the task. Reproducible pipelines of repair tools on vulnerability benchmarks can promote advances in the field, such as new repair techniques. We propose Maestro, a decentralized platform with RESTful APIs for performing automated software vulnerability repair. Our platform connects benchmarks of vulnerabilities with APR tools for performing controlled experiments. It also promotes fair comparisons among different APR tools. We compare the performance of Maestro with previous studies on four APR tools in finding repairs for ten projects. Our execution time results indicate an overhead of 23 seconds for projects in C and a reduction of 14 seconds for Java projects. We introduce an agnostic platform for vulnerability repair with preliminary tools/datasets for both C and Java. Maestro is modular and can accommodate tools, benchmarks, and repair workflows with dedicated plugins. © 2022 ACM.

Language: English

Type (Professor's evaluation): Scientific