Depuração: Localização Automática de Falhas

• Autor(a) principal: Sampaio, Carla Manuela Ferreira
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/18263
• topic: Automated Debugging; Spectrum-based Fault Localization; Fault Localization; Debugging; Bug

Developing a bug free software its impossible without the task of debugging. Due to the increasing complexity and size of software, it gets harder to find and fix these errors which lead to higher development costs. Therefore, software engineers try to either prevent the errors or debug them as fast as possible. Debugging is not only inevitable, but so difficult that it often consumes more time than creating the bogus piece of software. For this reason, researchers invested a considerable amount of effort in developing fault localization techniques and tools for supporting various debugging tasks. Fault localization has been an active area of research, leading to the creation of several tools, such as Aletheia. Spectrum-based Fault Localization (SFL), the technique behind the outlined tool, is a statistical debugging technique that relies on code coverage information. However, there is always a way to improve the effectiveness of this tool. This thesis, proposes an approach to overcome some challenges presented in the fault localization tool Aletheia and its integration with the similarity coefficient. This approach, tries to overcome the null symmetry when comparing the statements covered in the passed tests to the uncovered statements in the failed tests.