Software coverage: a testing approach through ant colony optimization

Authors:
Bhuvnesh Sharma;Isha Girdhar;Monika Taneja;Pooja Basia;Sangeetha Vadla;Praveen Ranjan Srivastava
Affiliations:
Birla Institute of Technology and Science, India;Birla Institute of Technology and Science, India;Birla Institute of Technology and Science, India;Birla Institute of Technology and Science, India;Birla Institute of Technology and Science, India;Birla Institute of Technology and Science, India
Venue:
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Year:
2011

Citing 7
Cited 0

Computational Intelligence in Software Engineering

Computational Intelligence in Software Engineering
On the many ways software engineering can benefit from knowledge engineering

SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
The Art of Software Testing

The Art of Software Testing
An Ant Colony Optimization Approach to Test Sequence Generation for Statebased Software Testin

QSIC '05 Proceedings of the Fifth International Conference on Quality Software
Extracting test sequences from a Markov software usage model by ACO

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
The state problem for evolutionary testing

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Foundations of Software Testing

Foundations of Software Testing

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.