The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Bio-Inspired Computational Intelligence and Its Application to Software Testing
Abstract
Bio inspired algorithms are computational procedure inspired by the evolutionary process of nature and swarm intelligence to solve complex engineering problems. In the recent times it has gained much popularity in terms of applications to diverse engineering disciplines. Now a days bio inspired algorithms are also applied to optimize the software testing process. In this chapter authors will discuss some of the popular bio inspired algorithms and also gives the framework of application of these algorithms for software testing problems such as test case generation, test case selection, test case prioritization, test case minimization. Bio inspired computational algorithms includes genetic algorithm (GA), genetic programming (GP), evolutionary strategies (ES), evolutionary programming (EP) and differential evolution(DE) in the evolutionary algorithms category and Ant colony optimization(ACO), Particle swarm optimization(PSO), Artificial Bee Colony(ABC), Firefly algorithm(FA), Cuckoo search(CS), Bat algorithm(BA) etc. in the Swarm Intelligence category(SI).
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.
|
|
|