Please use this identifier to cite or link to this item:
|Title:||Batch-optimistic test-cases generation using genetic algorithms||Authors:||Sofokleous, Anastasis A.
Andreou, Andreas S.
|Major Field of Science:||Engineering and Technology||Field Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Issue Date:||Oct-2007||Source:||19th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2007, Patras, Greece, 29 October 2007 through 31 October 2007||Volume:||1||Conference:||International Conference on Tools with Artificial Intelligence||Abstract:||This paper proposes a dynamic software testing framework, which is able to analyse the source code of a program, create the necessary data structures for automatic testing, such as control flow graphs, and generate a near to optimum set of test cases with reference to a test coverage criterion. The framework consists of two sub-systems: The first is a program analysis system that identifies the type of statements and the complexity of conditions, performs analysis of variables, extracts code paths and creates the control flow graph (CFG) of the program under testing. The second is a test system that uses the CFG for automatically generating test data based on evolutionary computing. The latter system utilises a specially designed genetic algorithm to produce the set of test cases satisfying the selected coverage criterion. The efficacy and performance of the proposed testing approach is assessed and validated using a variety of sample programs. © 2007 IEEE.||Description:||Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI Volume 1, 2007, Article number 4410278, Pages 157-164||ISBN:||0-7695-3015-X||ISSN:||1082-3409||DOI:||10.1109/ICTAI.2007.113||Rights:||© 2007 IEEE||Type:||Conference Papers||Affiliation :||Cyprus University of Technology|
|Appears in Collections:||Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation|
checked on Nov 6, 2023
Page view(s) 5212
checked on Dec 6, 2023
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.