Improving random test sets using the diversity oriented test data generation

Authors:
Paulo M. S. Bueno;W. Eric Wong;Mario Jino
Affiliations:
Renato Archer Research Center, Campinas, São Paulo, Brazil;University of Texas at Dallas, Richardson, TX;State University of Campinas, Campinas, São Paulo, Brazil
Venue:
Proceedings of the 2nd international workshop on Random testing: co-located with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007)
Year:
2007

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Abstract

We present a measure that characterizes the diversity of a test set from the perspective of the input domain of the program under test. By using a metaheuristic algorithm, randomly generated test sets (RTS) are evolved towards Diversity Oriented Test Sets (DOTS), which thoroughly cover the input domain. DOTS are evaluated using a Monte Carlo simulation to assess how testing factors influence their effectiveness and also by the values of data flow coverage and mutation scores attained on simple programs. Results provide understanding on possible gains of using DOTS and on circumstances where RTS can be more effective.