|
Abstract
|
Article Information:
Application of Search Algorithms for Model Based Regression Testing
Sidra Noureen and Sohail Asghar
Corresponding Author: Sidra Noureen
Submitted: October 26, 2013
Accepted: November 12, 2013
Published: April 12, 2014 |
Abstract:
|
UML models have gained their significance as reported in the literature. The use of a model to describe the behavior of a system is a proven and major advantage to test. With the help of Model Based Testing (MBT), it is possible to automatically generate test cases. When MBT is applied on large industrial systems, there is problem to sampling the test cases from the suit of entire test because it is difficult to execute the huge number of test cases being generated. The motivation of this study is to design a multi objective genetic algorithm based test case selection technique which can select the most appropriate subset of test cases. NSGA (Non-dominated Sorting Genetic Algorithm) is used as an optimization algorithm and its fitness function is improved for selecting test cases from the dataset. It is concluded that there is a room to improve the performance of NSGA algorithm by means of tailoring its respective fitness function.
Key words: Metaheuristic, MBT, regression testing, test case selection, , ,
|
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
Sidra Noureen and Sohail Asghar, . Application of Search Algorithms for Model Based Regression Testing. Research Journal of Applied Sciences, Engineering and Technology, (14): 2981-2986.
|
|
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
