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  1. Proceedings of the Eighth International Workshop on Search-Based Software Testing (SBST '15)
  2. A novelty search approach for automatic test data generation
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Broadening the search in search-based software testing: it need not be evolutionary
Unit testing tool competition: round three
Using dynamic symbolic execution to generate inputs in search-based GUI testing
T3: benchmarking at third unit testing tool contest
An empirical analysis of providing assurance for self-adaptive systems at different levels of abstraction in the face of uncertainty
EvoSuite at the SBST 2015 tool competition
Meta-heuristic generation of robust XPath locators for web testing
GRT at the SBST 2015 tool competition
Hyperheuristic search for SBST
Results for EvoSuite-MOSA at the third unit testing tool competition
A novelty search approach for automatic test data generation
JTExpert at the third unit testing tool competition
Constraints: the future of combinatorial interaction testing

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A novelty search approach for automatic test data generation

Content Provider ACM Digital Library
Author Sunyé, Gerson Boussaa, Mohamed Barais, Olivier Baudry, Benoît
Abstract In search-based structural testing, metaheuristic search techniques have been frequently used to automate the test data generation. In Genetic Algorithms (GAs) for example, test data are rewarded on the basis of an objective function that represents generally the number of statements or branches covered. However, owing to the wide diversity of possible test data values, it is hard to find the set of test data that can satisfy a specific coverage criterion. In this paper, we introduce the use of Novelty Search (NS) algorithm to the test data generation problem based on statement-covered criteria. We believe that such approach to test data generation is attractive because it allows the exploration of the huge space of test data within the input domain. In this approach, we seek to explore the search space without regard to any objectives. In fact, instead of having a fitness-based selection, we select test cases based on a novelty score showing how different they are compared to all other solutions evaluated so far.
Starting Page 40
Ending Page 43
Page Count 4
File Format PDF
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-05-16
Access Restriction Subscribed
Content Type Text
Resource Type Article
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