Software testing techniques (2nd ed.)
Software testing techniques (2nd ed.)
Dominators, super blocks, and program coverage
POPL '94 Proceedings of the 21st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Introduction to algorithms
Using genetic algorithms for test case generation in path testing
ATS '00 Proceedings of the 9th Asian Test Symposium
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
Software Testing Research: Achievements, Challenges, Dreams
FOSE '07 2007 Future of Software Engineering
Test Data Generation from UML State Machine Diagrams using GAs
ICSEA '07 Proceedings of the International Conference on Software Engineering Advances
Comparison of Two Fitness Functions for GA-Based Path-Oriented Test Data Generation
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 04
Foundations of Software Testing
Foundations of Software Testing
Automated Software Testing Using Metahurestic Technique Based on an Ant Colony Optimization
ISED '10 Proceedings of the 2010 International Symposium on Electronic System Design
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Software testing is one of the most challenging and arduous phase of software development life cycle (SDLC) which helps in determining the software quality. Code coverage is a widely used testing paradigm, which describes the degree to which the code has been tested. Aim of the current paper is to propose an optimised code coverage algorithm with the help of an emerging technique, i.e., intelligent water drop (IWD). This approach uses dynamic parameters for finding all the optimal paths using basic properties of natural water drops. It proposes how test cases can be considered as an IWD moving on the edges of the control dependency graph for finding the optimal paths. The algorithm guarantees complete code coverage by generating automated test sequences.