Approach for automated test data generation for path testing in aspect-oriented programs using genetic algorithm

Abstract

Aspect-Oriented Programming (AOP) is an emerging programming paradigm that supports implementation of cross-cutting requirements into named program units called aspects. However, these Aspects are hard to deal in many stages of Software Development Life Cycle (SDLC) especially in Aspect-Oriented software testing. Main aim of testing is to find the errors during execution of the program. Error can prevail in any part of the program so this study use Control Flow Graph (CFG) to depicts all path of the program during its execution. Some path of the program executes rarely, so with the help of automated test data generation tester can execute those path because generation of test data for these path is not manually possible. Test data generation process can be automated with the help of various techniques and framework. This work provides review of some of the recent work that has been done in the area of AOP test data generation. Based on those work, this work proposes a approach for generating test data for AOP using Genetic Algorithm (GA).