Open AccessAutomatic Generation and Optimization of Combinatorial Test Cases from UML Activity Diagram Using Particle Swarm Optimization
Author(s) -
Subhash Tatale,
V. Chandra Prakash
Publication year - 2022
Publication title -
ingénierie des systèmes d'information/ingénierie des systèmes d'information
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.161
H-Index - 8
eISSN - 2116-7125
pISSN - 1633-1311
DOI - 10.18280/isi.270106
Subject(s) - activity diagram , test case , particle swarm optimization , computer science , model based testing , unified modeling language , process (computing) , automation , test management approach , combinatorial explosion , test (biology) , software , algorithm , data mining , software system , programming language , machine learning , mathematics , engineering , regression analysis , combinatorics , biology , mechanical engineering , paleontology , software construction
Generation of test cases is one of the essential activities of the software testing process. The process of executing a programme to identify defects to improve the system's quality is known as software testing. Manually writing test cases takes time, effort, and money. On the other hand, generating test cases automatically is the solution to this problem. For this automation process, a model-based test case generation technique would be acceptable. A model is usually required to generate test cases in the model-based testing technique. Nowadays, researchers have relied on the activity diagram to generate test cases. Test cases for combinatorial logic systems are required. Combinatorial testing is essential for producing a small number of test cases and identifying errors occurred by interactions between system input parameters. Information about constraints, parameters and its values are required for generation of test cases. It is difficult to extract information regarding constraints, parameters, its values, and interactions between parameters from an Activity Diagram. A novel approach is proposed to extract this information from an Activity Diagram. The authors created a tool that automatically generates combinatorial test cases using UML Activity Diagrams. The proposed tool has two main parts. First, the combinatorial test design model is developed for extraction of input parameters. Second part is generation of optimized number of combinatorial test cases using Particle Swarm Optimization algorithm. Finally, the authors experimented on a real-world case study namely viz. Railway Reservation using the proposed tool, and it is shown that the proposed tool generated optimum number of combinatorial test cases.