Comparação entre ferramentas para geração de dados de teste utilizando inteligência artificial e aleatoriedade

• Main Author: Campos, Jober Guifor de
• Publication Date: 2018
• Format: Bachelor thesis
• Language: por
• Source: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Download full: http://repositorio.utfpr.edu.br/jspui/handle/1/10783
• topic: Software - Desenvolvimento; Algorítmos genéticos; Software - Testes; Computer software - Development; Genetic algorithms; Software - Testing; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::ENGENHARIA DE SOFTWARE

Within the software development processes, the Verification, Validation and Test (VV & T) activities configure the most reliable sources for a system to have the compliance of its requirements ascertained. One of the most important features within automated testing is the automatic generation of test data. In this context, test data (valid/invalid values of the input domain of developing systems are automatically generated by some resource.) The main features for the automatic generation of test data are Genetic Algorithms (GAs), which simulate situations of evolutionary biology (mutation, heredity, natural selection, etc.) for approximate optimization solutions. However, there are tools for this purpose that use AGs for data generation (EvoSuite), there is also another tool that uses the same-directed randomness (Randoop). The present study aims at the planning and execution of a set of empirical evaluations about the comparison between the EvoSuite and Randoop tools for functional test requirements. From the completion of case studies, it will be shown that an AGs use tool can be applied in the selected domains.