Analysis of the constraint solver in UNA based test data generation
Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering
Improved method to generate path-wise test data
Journal of Computer Science and Technology
Automatic Test Data Generation for Programs with Integer and Float Variables
Proceedings of the 16th IEEE international conference on Automated software engineering
Program Execution-Based Module Cohesion Measurement
Proceedings of the 16th IEEE international conference on Automated software engineering
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A number of approaches have been proposed to automatically generate test data to traverse a given path in a program. In this paper, we present a program execution based approach to generate test data for a given path. The technique derives a desired input for a test path by iteratively refining an arbitrarily chosen input. A set of linear constraints on the increments to the input are derived to refine the input. We solve this constraint set using a Unified Numerical Approach (UNA) developed in this paper. Our technique can generate both integer and floating point inputs as well as handle arrays and loops. We determine a basis set of paths for a program and use our technique to generate test data for this set. We implemented and experimentally evaluated our technique. We present results of generating input for scientific programs. The experimental results show that the technique is effective in that it generates input for most of the paths in the basis sets and also efficiently detects linear infeasible paths. Our experiments also show that our technique is efficient in the number of iterations required to generate test data. The time performance shows that it provides a practical method to automatically generate test data for scientific programs.