Software Testing

Testing is the most important and critical task in software development life cycle. Whenever a Software Testing execution fails its test scripts is analyzed so that the point where the fault occurred can be detected and the expected result can be achieved also called as fault localization. Manually fault localization can be a cumbersome job so providing an automated technique to do the same without human intervention is the target. In this research, a brief overview of all the technique of soft computing is implemented for software fault localization to achieve better results. Specifying the above, it would generate a better result using a machine learning technique for time reduction. The research aims to propose and experimentally show a survey on usage of soft computing technique sorting out the software fault localization issue and also which technique is minimizing the time and space complexities so that accurate and reliable results can be achieved in better usability and effectiveness. This report aims to implement soft computing method to help in software testing and decide their ease of usage and effectiveness.

Autorentext

Manpreet Singh Bajwa trabalha como Professor Assistente no Departamento de Informática na Faculdade de Engenharia, Grupo de Faculdades de Chandigarh. É coordenador do corpo docente do IEEE Student Branch e do Google DSC powered by Google.