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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

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