Please use this identifier to cite or link to this item:
Title: Investigation of similarity-based test case selection for specification-based regression testing.
???metadata.dc.creator???: OLIVEIRA NETO, Francisco Gomes de.
???metadata.dc.contributor.advisor1???: MACHADO, Patrícia Duarte de Lima.
???metadata.dc.contributor.referee1???: CARTAXO, Emanuela Gadelha.
???metadata.dc.contributor.referee2???: ARANHA, Eduardo Henrique da Silva.
???metadata.dc.contributor.referee3???: MASSONI, Tiago Lima.
???metadata.dc.contributor.referee4???: SIMÃO, Adenildo da Silva.
Keywords: Engenharia de software;Model-Based Testing (MBT);Automatic Model Generation;Specification-Based Regression Testing;SimilarityApproachforRegression Testing;Teste de regressão;Teste de software
Issue Date: 30-Jul-2014
Publisher: Universidade Federal de Campina Grande
Citation: OLIVEIRA NETO, Francisoc Gomes de. Investigation of similarity-based test case selection for specification-based regression testing. 2014. 149f. (Tese de Doutorado), Programa de Pós-graduação em Ciência da Computação, Centro de Engenharia elétrica e Informática, Universidade Federal de Campina Grande - Paraíba - Brasil, 2014. (Tese redigida em língua inglesa).
???metadata.dc.description.resumo???: uring software maintenance, several modifications can be performed in a specification model in order to satisfy new requirements. Perform regression testing on modified software is known to be a costly and laborious task. Test case selection, test case prioritization, test suite minimisation,among other methods,aim to reduce these costs by selecting or prioritizing a subset of test cases so that less time, effort and thus money are involved in performing regression testing. In this doctorate research, we explore the general problem of automatically selecting test cases in a model-based testing (MBT) process where specification models were modified. Our technique, named Similarity Approach for Regression Testing (SART), selects subset of test cases traversing modified regions of a software system’s specification model. That strategy relies on similarity-based test case selection where similarities between test cases from different software versions are analysed to identify modified elements in a model. In addition, we propose an evaluation approach named Search Based Model Generation for Technology Evaluation (SBMTE) that is based on stochastic model generation and search-based techniques to generate large samples of realistic models to allow experiments with model-based techniques. Based on SBMTE,researchers are able to develop model generator tools to create a space of models based on statistics from real industrial models, and eventually generate samples from that space in order to perform experiments. Here we developed a generator to create instances of Annotated Labelled Transitions Systems (ALTS), to be used as input for our MBT process and then perform an experiment with SART.In this experiment, we were able to conclude that SART’s percentage of test suite size reduction is robust and able to select a sub set with an average of 92% less test cases, while ensuring coverage of all model modification and revealing defects linked to model modifications. Both SART and our experiment are executable through the LTS-BT tool, enabling researchers to use our selections trategy andr eproduce our experiment.
Keywords: Engenharia de software
Model-Based Testing (MBT)
Automatic Model Generation
Specification-Based Regression Testing
SimilarityApproachforRegression Testing
Teste de regressão
Teste de software
???metadata.dc.subject.cnpq???: Ciência da Computação.
Appears in Collections:Doutorado em Ciência da Computação.

Files in This Item:
File Description SizeFormat 
FRANCISCO GOMES DE OLIVEIRA NETO - TESE PPGCC 2014..pdfFrancisco Gomes de Oliveira Neto - Tese PPGCC 2014.5.04 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.