Generating combinatorial test suite for interaction relationship
Fourth international workshop on Software quality assurance: in conjunction with the 6th ESEC/FSE joint meeting
A survey of combinatorial testing
ACM Computing Surveys (CSUR)
Application of quotient space theory in input-output relationship based combinatorial testing
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Information Sciences: an International Journal
An automated framework for software test oracle
Information and Software Technology
Neural networks based automated test oracle for software testing
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Attribute reduction based expected outputs generation for statistical software testing
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Artificial neural networks as multi-networks automated test oracle
Automated Software Engineering
Hi-index | 0.01 |
In this paper we describe a technique for generating expected results for automated black-box testing. Generating expected results allows larger automated test suites to be created, moving us toward continuous product testing. Our technique uses a program's Input-Output (IO) relationships to identify unique combinations of program inputs that influence program outputs. With this information, a small set of test cases is executed and checked for correctness. Given the correctness of this set, the expected results for the larger combinatorial test set can be generated automatically. Included in the paper is an experimental study in which checking the results of 384 test cases allows us to generate expected results and fully automate nearly 600,000 test cases.