Best Test Cases Selection Approach Using Genetic Algorithm


  •  Nidal Yousef    
  •  Hassan Altarwaneh    
  •  Aysh Alhroob    

Abstract

This paper proposes an approach for selecting best testing scenarios using Genetic Algorithm.  Test cases generation approach uses UML sequence diagrams, class diagrams and Object Constraint Language (OCL) as software specifications sources. There are three main concepts: Edges Relation Table (ERT), test scenarios generation and test cases generation used in this work. The ERT is used to detect edges in sequence diagrams, identifies their relationships based on the information available in sequence diagrams and OCL information. ERT is also used to generate the Testing Scenarios Graph (TSG). The test scenarios generation technique concerns the generation of scenarios from the testable model of the sequence diagram. Path coverage technique is proposed to solve the problem of test scenario generation that controls explosion of paths which arise due to loops and concurrencies. Furthermore, GA used to generates test cases that covers most of message paths and most of combined fragments (loop, par, alt, opt and break), in addition to some structural specifications.

 



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

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