![](/images/graphics-bg.png)
A Hybrid Intelligent Search Algorithm for Automatic Test Data Generation
Joint Authors
Wang, Ya-Wen
Zhang, Xu-Zhou
Gong, Yun-Zhan
Xing, Ying
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-10
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The increasing complexity of large-scale real-world programs necessitates the automation of software testing.
As a basic problem in software testing, the automation of path-wise test data generation is especially important, which is in essence a constraint optimization problem solved by search strategies.
Therefore, the constraint processing efficiency of the selected search algorithm is a key factor.
Aiming at the increase of search efficiency, a hybrid intelligent algorithm is proposed to efficiently search the solution space of potential test data by making full use of both global and local search methods.
Branch and bound is adopted for global search, which gives definite results with relatively less cost.
In the search procedure for each variable, hill climbing is adopted for local search, which is enhanced with the initial values selected heuristically based on the monotonicity analysis of branching conditions.
They are highly integrated by an efficient ordering method and the backtracking operation.
In order to facilitate the search methods, the solution space is represented as state space.
Experimental results show that the proposed method outperformed some other methods used in test data generation.
The heuristic initial value selection strategy improves the search efficiency greatly and makes the search basically backtrack-free.
The results also demonstrate that the proposed method is applicable in engineering.
American Psychological Association (APA)
Xing, Ying& Gong, Yun-Zhan& Wang, Ya-Wen& Zhang, Xu-Zhou. 2015. A Hybrid Intelligent Search Algorithm for Automatic Test Data Generation. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1074296
Modern Language Association (MLA)
Xing, Ying…[et al.]. A Hybrid Intelligent Search Algorithm for Automatic Test Data Generation. Mathematical Problems in Engineering No. 2015 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1074296
American Medical Association (AMA)
Xing, Ying& Gong, Yun-Zhan& Wang, Ya-Wen& Zhang, Xu-Zhou. A Hybrid Intelligent Search Algorithm for Automatic Test Data Generation. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1074296
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074296