Paper Info
Title
Understanding the effect of time-constraint bounded novel technique for regression test selection and prioritization.
Abstract
It is the demand of our ever-advancing IT industry that software be updated in order to continue its use. Such a modification should not introduce any unwanted new faults in the system. For this, the existing test suite needs to be rerun, often called as regression testing. The main challenge during the regression testing process is not to exceed the desired time and budge deadlines. As a consequence various techniques such as test case selection, minimization and prioritization are used. This paper proposes and analyzes the effect of time constraint on an ant colony optimization based technique for Regression test selection and prioritization. It has been found that with an increase in the applied time constraint, there are more chances to get an optimum selected and prioritized test suite. Also it was found that the complexity of our algorithm depends on the size of the test suite and the applied time constraint and is independent of the number of faults being mutated or any other input variable.
Year
DOI
Venue
2015
10.1007/s13198-014-0244-3
Int. J. Systems Assurance Engineering and Management
Keywords
Field
DocType
Regression test selection, Test case prioritization, Ant colony optimization (ACO), Time-constraint, Analysis
Ant colony optimization algorithms,Test suite,Data mining,Mathematical optimization,Not-To-Exceed,Regression testing,Minification,Software,Engineering,Time constraint,Bounded function
Journal
Volume
Issue
ISSN
6
1
0976-4348
Citations 
PageRank 
References 
0
0.34
16
Authors
2
Name
Order
Citations
PageRank
Bharti Suri1638.02
Shweta Singhal2201.30