2022-11-102022-11-102022-10-13FERREIRA, Willian de Jesus. Localização evolucionária de defeitos em software baseada na singularidade de escores de suspeita. 2022. 79 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2022.http://repositorio.bc.ufg.br/tede/handle/tede/12436Context. Software is subject to the presence of faults, which impacts its quality as well as production and maintenance costs. Evolutionary fault localization has used data from the test activity (test spectra) as a source of information about defects, and its automation aims to obtain better accuracy and lower software repair cost. Motivation. Our analysis identified that test spectra commonly used in the research field have a high ratio of sample repetition, which impairs the training and evolution of models (heuristics). Problem. We investigate whether the uniqueness of suspiciousness scores can boost the ability to find software faults, aiming to deal with samples repetition, that is, if an exploration based on how distinguishable program elements are about being defective can generate competitive models. Methodology. The investigation formalized hypotheses, introduced three training strategies to guide the proposal and carried out an experimental evaluation, aiming to reach conclusions regarding the assessment of research questions and hypotheses. Analysis. The results have shown the competitiveness of all the proposed training strategies through evaluation metrics commonly used in the research field. Conclusion. Statistical analyses confirmed that the uniqueness of suspiciousness scores guides the generation of superior heuristics for fault localization.Attribution-NonCommercial-NoDerivatives 4.0 InternationalLocalização de defeitosSBSEDepuração de softwareProgramação genéticaFault LocalizationSoftware debugGenetic programingCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAODissertação