Davide Ginelli

Davide Ginelli, Oliviero Riganelli, Daniela Micucci et al.

Automated Program Repair (APR) techniques typically exploit spectrum-based fault localization (SBFL) to identify the program locations that should be patched, making the effectiveness of APR techniques dependent on the effectiveness of fault localization. Indeed, results show that SBFL often does not localize faults accurately, hindering the effectiveness of APR. In this paper, we propose EXCEPT, a technique that addresses the localization problem by focusing on the semantics of failures rather than on the correlation between the executed statements and the failed tests, as SBFL does. We focus on failures due to exceptions and we exploit their type and source to localize and guess the faults. Experiments with 43 exception-raising faults from the Defects4J benchmark show that EXCEPT can perform better than Ochiai and ssFix.

André Silva, Matias Martinez, Benjamin Danglot et al.

Fault localization is an essential step in the debugging process. Spectrum-Based Fault Localization (SBFL) is a popular fault localization family of techniques, utilizing code-coverage to predict suspicious lines of code. In this paper, we present FLACOCO, a new fault localization tool for Java. The key novelty of FLACOCO is that it is built on top of one of the most used and most reliable coverage libraries for Java, JaCoCo. FLACOCO is made available through a well-designed command-line interface and Java API and supports all Java versions. We validate FLACOCO on two use-cases from the automatic program repair domain by reproducing previous scientific experiments. We find it is capable of effectively replacing the state-of-the-art FL library. Overall, we hope that FLACOCO will help research in fault localization as well as industry adoption thanks to being founded on industry-grade code coverage. An introductory video is available at https://youtu.be/RFRyvQuwRYA

Davide Ginelli, Matias Martinez, Leonardo Mariani et al.

Automatic Program Repair (APR) techniques can promisingly help reducing the cost of debugging. Many relevant APR techniques follow the generate-and-validate approach, that is, the faulty program is iteratively modified with different change operators and then validated with a test suite until a plausible patch is generated. In particular, Kali is a generate-and-validate technique developed to investigate the possibility of generating plausible patches by only removing code. Former studies show that indeed Kali successfully addressed several faults. This paper addresses the case of code-removal patches in automated program repair investigating the reasons and the scenarios that make their creation possible, and the relationship with patches implemented by developers. Our study reveals that code-removal patches are often insufficient to fix bugs, and proposes a comprehensive taxonomy of code-removal patches that provides evidence of the problems that may affect test suites, opening new opportunities for researchers in the field of automatic program repair.