Partition testing with usage models

Abstract The fundamental statistical strategy of improving sampling efficiency through partitioning the population is applied to software testing. Usage models make it possible to apply this strategy to improve the efficiency of testing. The testing budget is allocated to the blocks of the partition, and the software is executed on the sample of uses drawn from each block or sub-population of potential uses. Usage models support many strategies for automated partitioning and generating test cases from the partitioned population. Two strategies are shown here with the efficiency gains demonstrated.

[1]  Jesse H. Poore,et al.  Application of statistical science to testing and evaluating software intensive systems , 1999, Proceedings. Science and Engineering for Software Development: A Recognition of Harlin D. Mills Legacy (Cat. No. PR00010).

[2]  Elaine J. Weyuker,et al.  Analyzing Partition Testing Strategies , 1991, IEEE Trans. Software Eng..

[3]  Jesse H. Poore,et al.  Markov analysis of software specifications , 1993, TSEM.

[4]  Vijayan N. Nair,et al.  A statistical assessment of some software testing strategies and application of experimental design techniques , 1998 .

[5]  Jesse H. Poore,et al.  Statistical testing of software based on a usage model , 1995, Softw. Pract. Exp..

[6]  R. Taylor,et al.  Partition testing does not inspire confidence , 1988, [1988] Proceedings. Second Workshop on Software Testing, Verification, and Analysis.

[7]  James A. Whittaker,et al.  A Markov Chain Model for Statistical Software Testing , 1994, IEEE Trans. Software Eng..

[8]  A. Winsor Sampling techniques. , 2000, Nursing times.