Novel Approach to Automated Test Data Generation for AOP

Abstract

Aspect oriented programming is a new programming paradigm. AOP is based on object oriented programming. Most of the researchers target this new paradigm towards the programming not for testing. Testing of aspect oriented programs is an emerging field of research as a very few research work is going on currently on ASP.In this paper, we investigate a new way of testing aspect oriented programs.Here we propose a framework of automated test data generation for evolutionary testing on AOP. On the basis of generated data we will compare evolutionary testing with random testing in terms of effort reduction and improvement of test effectiveness. We will justify our comparison with the help of empirical study on AspectJ programs.

GASE -an input domain reduction and branch coverage system based on Genetic Algorithm and Symbolic Execution

“…The search space was the input domain of the test object, with every character / possible result, individual an encoded place of inputs to that test object. Anuranjan Misra et al [7] have proposed a novel approach to automated test data generation for AOP. The approach was based on evolutionary testing, which had used search based optimization to target hard to cover branches.…”

Automated Software Test Data Generation Using Improved Search Procedure

“…It should also depend on assignment statements since as soon as a variable is assigned a value or another variable, its mutability trait may vanish and hence its risk factor since it is always going to attain the assigned value despite of what user gives it initially. This means that variable dependencies [10] hold important place in determining risk factor.…”

An Automated Sequence Model Testing (ASMT) for Reducing Test Suit Size

“…Among these issues, the test generation problem is deemed to be an important issue in software testing research [7]. Various approaches are developed to solve the above mentioned issues, few of them are PSO (Particle Swarm Optimization) [8], ACO (Ant Colony Optimization) [9], genetic algorithm [10] etc.…”