A Multi-Objective optimization algorithm for uniformly distributed generation of test cases

摘要: Multi-objective optimization deals with conflicting objectives. A multi-objective problem is determined to find acceptable solution for all objectives based on the concept of Pareto-Optimality. This paper focuses automatic test data generation aspect Multi - Objective. One objective will be uniformly distribution and another maximize code. incorporates decision making. also covers non-dominance property maintain sub-population best fitness value. Generally, has two approaches, one decompose into various single components, evolve Pareto-optimal set solutions. Software Testing a tedious, critical expensive phase software development, thus there need distributed cases over provided range maximum code coverage. system failure incur huge loss, overcome this an efficient testing approach required.