Automatic Test Data Generation Using Bio-Inspired Algorithms: A Travelogue

Automatic Test Data Generation Using Bio-Inspired Algorithms: A Travelogue

Madhumita Panda (North Orissa University, India) and Sujata Dash (North Orissa University, India)
DOI: 10.4018/978-1-5225-2857-9.ch008
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This chapter presents an overview of some widely accepted bio-inspired metaheuristic algorithms which would be helpful in solving the problems of software testing. Testing is an integral part of the software development process. A sizable number of Nature based algorithms coming under the per- view of metaheuristics have been used by researchers to solve practical problems of different disciplines of engineering and computer science, and software engineering. Here an exhaustive review of metaheuristic algorithms which have been employed to optimize the solution of test data generation for past 20 -30 years is presented. In addition to this, authors have reviewed their own work has been developed particularly to generate test data for path coverage based testing using Cuckoo Search and Gravitational Search algorithms. Also, an extensive comparison with the results obtained using Genetic Algorithms, Particle swarm optimization, Differential Evolution and Artificial Bee Colony algorithm are presented to establish the significance of the study.
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Basic Concepts Of Test Data Generation

Software testing mainly includes the detailed verification and validation of the entire process of software development ensuring its correctness and quality. In earlier days people were not technical literate and neither well acquainted with the use of software and its underlying technologies. With the passage of time and advent of modern technology gradually program complexity, as well as common user’s technical knowledge start growing at an explosive rate. Thus it became mandatory to ensure the quality and correct functioning of each and every specification, before successful lunching of any new software, as well as maintenance of existing software.

Key Terms in this Chapter

Search Based Testing: It is a domain of software testing where bio inspired search algorithms are applied to solve the critical problems of software testing.

Bio-Inspired Algorithm: It includes all the metaheuristic algorithms developed mimicking the food and foraging behavior of different organisms as well as the intelligentsia developed by nature for better species selection as well as adaptation to the environment.

Feasible Path: All traceable paths of the program structure where we can traverse from start node to end node of a program structure, are known as the the feasible paths of that program structure.

Test Adequacy Criteria: It is the minimum and sufficient criteria required to perform a particular type of testing.

Coverage: The percent of code tested by a particular set of input data or by adopting a specific testing strategy is known as coverage.

Test Data: The set of inputs carefully calculated or selected to test a software or any specific module of a software.

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