Test Data Generation Based on Test Path Discovery Using Intelligent Water Drop

Test Data Generation Based on Test Path Discovery Using Intelligent Water Drop

Praveen Ranjan Srivastava (Birla Institute of Technology and Science, Pilani, India), Amitkumar Patel (Birla Institute of Technology and Science, Pilani, India), Kunal Patel (Birla Institute of Technology and Science, Pilani, India) and Prateek Vijaywargiya (Birla Institute of Technology and Science, Pilani, India)
Copyright: © 2012 |Pages: 19
DOI: 10.4018/jamc.2012040105
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Abstract

Automatic test data generation is required to generate test cases dynamically for a specific software program. Manual generation of test data is too tedious and a time consuming task. This paper proposes a technique using Intelligent Water Drop (IWD) for automatic generation of test data. Correctly generated test data helps in reducing the effort while testing the software. This paper discusses different algorithms based on IWD to generate test data and path coverage over Control Flow Graph. Test data is generated keeping in mind all of the programming constraints like “if,” “while,” “do while,” etc., available in the program.
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Background

Various techniques (Korel, 1990; Pedrycz & Peters, 1998; Briand, 2002; McMinn, 2004; Harman, 2007; Kewen et al., 2009; Srivastava et al., 2009; Srivastava & Baby, 2010) have been proposed for automated testing to reduce efforts to a remarkable extent. Swarm optimization techniques are widely used for test data generation. Ant Colony Optimization (ACO) is one of them (Li & Lam, 2005; Kewen et al., 2009; Srivastava et al., 2009). Automatic test data generation based on ACO (Kewen et al., 2009) has introduced a model to generate test data using the branch function technique. It has solved the problem of local optimization, but this approach is applicable only for numeric data types and also the model is not suitable for object oriented programs and other types of input behavior. Software test data generation using ACO (Li & Lam, 2005) has also proposed a solution for state-based software testing but complete coverage is not possible by the proposed approach.

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