A New Software Data-Flow Testing Approach via Ant Colony Algorithms

Search-based optimization techniques have been applied to a wide variety of software engineering activities including cost estimation, next release problem, and test generation. Several search based test generation techniques have been developed. These techniques had focused on finding suites of test data to satisfy a number of control-flow or data-flow testing criteria. Genetic algorithms have been the most widely employed search-based optimization technique in software testing issues. Recently, there are many novel search-based optimization techniques have been developed such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Immune System (AIS), and Bees Colony Optimization (BCO).

Provided by: Universal Journal of Applied computer Science and Technology Topic: Big Data Date Added: Oct 2010 Format: PDF

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