Geração evolucionária de heurísticas para localização de defeitos de software

• Ano de defesa: 2018
• Autor(a) principal: Freitas, Diogo Machado de
• Orientador(a): Leitão Júnior, Plínio de Sá
• Banca de defesa: Soares, Anderson da Silva, Vergilio, Silvia Regina
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Goiás
• Programa de Pós-Graduação: Programa de Pós-graduação em Ciência da Computação (INF)
• Departamento: Instituto de Informática - INF (RG)
• País: Brasil
• Palavras-chave em Português: Localização de defeitos baseada em espectro; Localização de defeitos baseada em busca; Engenharia de software baseada em busca; Programação genética; Meta-heurísticas evolucionárias
• Palavras-chave em Inglês: Spectrum-based fault localization; Search-based fault localization; Search-based software engineering; Genetic programming; Evolutionary metaheuristics
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tede/9010

Fault Localization is one stage of the software life cycle, which demands important resources such as time and effort spent on a project. There are several initiatives towards the automation of the fault localization process and the reduction of the associated resources. Many techniques are based on heuristics that use information obtained (spectrum) from the execution of test cases, in order to measure the suspiciousness of each program element to be defective. Spectrum data generally refers to code coverage and test results (positive or negative). The present work presents two approaches based on the Genetic Programming algorithm for the problem of Fault Localization: a method to compose a new heuristic from a set of existing ones; and a method for constructing heuristics based on data from program mutation analysis. The innovative aspects of both methods refer to the joint investigation of: (i) specialization of heuristics for certain programs; (ii) application of an evolutionary approach to the generation of heuristics with non-linear equations; (iii) creation of heuristics based on the combination of traditional heuristics; (iv) use of coverage and mutation spectra extracted from the test activity; (v) analyzing and comparing the efficacy of methods that use coverage and mutation spectra for fault localization; and (vi) quality analysis of the mutation spectra as a data source for fault localization. The results have pointed to the competitiveness of both approaches in their contexts.