Software Testing is one of the most important parts of the software development lifecycle. Testing effectiveness can be achieved by the State Transition Testing (STT) and path testing which is commonly used for carrying out functional and structural testing of software systems. The tester is required to test all possible transitions and paths in the system under built. Aim of the current paper is to present an algorithm for generation of test sequences for state transitions of the system as well as path generation for CFG of the software code using the basic property and behavior of the ants. This novel approach tries to find out all the effective (or can say optimal) paths and test sequences by applying ant colony optimization (ACO) principle using some set of rules. This algorithm tries to give maximum software coverage with minimal redundancy. © 2011 Springer-Verlag.
CITATION STYLE
Panigrahi, B. K., Das, S., Suganthan, P. N., & Nanda, P. K. (Eds.). (2012). Swarm, Evolutionary, and Memetic Computing (Vol. 7677). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-35380-2
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