The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Automatic Test Data Generation Using Bio-Inspired Algorithms: A Travelogue
Abstract
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.
Related Content
|
G. Sowmya, R. Sridevi, K. S. Sadasiva Rao, Sri Ganesh Shiramshetty.
© 2025.
36 pages.
|
|
Srinidhi Vasan.
© 2025.
20 pages.
|
|
Arul Kumar Natarajan, Yash Desai, Pravin R. Kshirsagar, Kamal Upreti, Tan Kuan Tak.
© 2025.
26 pages.
|
|
R. Leisha, Katelyn Jade Medows, Michael Moses Thiruthuvanathan, S. Ravindra Babu, Prakash Divakaran, Vandana Mishra Chaturvedi.
© 2025.
40 pages.
|
|
Rituraj Jain, Kumar J. Parmar, Kushal Gaddamwar, Damodharan Palaniappan, T. Premavathi, Yatharth Srivastava.
© 2025.
32 pages.
|
|
Anya Behera, A. Vedashree, M. Rupesh Kumar, Kamal Upreti.
© 2025.
30 pages.
|
|
Neha Bagga, Sheetal Kalra, Parminder Kaur.
© 2025.
30 pages.
|
|
|