Modified Condition / Decision Coverage (MC / DC) is a white box testing criteria aiming to prove that all conditions involved in a predicate can influence the predicate value in the desired way. Though MC/DC is a standard coverage criterion, existing automated test data generation approaches like CONCOLIC testing do not support MC/DC. To address this issue we present an automated approach to generate test data that helps to achieve an increase in MC/DC coverage of a program under test. We use code transformation techniques which consist of the following major steps: Identification of predicates, Simplification of sum of product by QUINEMcMLUSKY method, and generating empty true-false if-else statements. This transformed program is inserted into the CONCOLIC tester (CREST TOOL) to generate test data for increased MC/DC coverage. Our approach helps to achieve an increase in MC/DC coverage as compared to the traditional CONCOLIC testing.

In regulated domains such as aerospace and safety critical domains, software quality assurance is subjected to strict regulations such as the DO-178B standard. MC/DC is a white box software testing criteria aiming to prove all the conditions involved in a predicate that can influence the predicate value in the desired way. Though MC/DC is a coverage criterion, existing automated test data generation approaches like CONCOLIC testing do not support MC/DC. In this paper, we propose an automated technique to generate a test suite that helps in achieving an increase in MC/DC coverage of a program under test. We use code transformation technique which consists of two steps: identification of predicates and generation of empty truefalse if-else statements. The empty conditional statements are based on the concepts of exclusive nor (X-NOR) operations. This transformed program is inserted into the CREST TOOL. It drives CREST TOOL to generate test suite and increase the MC/DC coverage. Our technique helps to achieve a significant increase in MC/DC coverage as compared to traditional CONCOLIC testing.

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SUMMARYDistributed concolic testing (DCT) for complex programs takes a remarkable computational time. Also, the achieved modified condition/decision coverage (MC/DC) for such programs is often inadequate. We propose an improved DCT approach that reduces the computational time and simultaneously enhanced the MC/DC. We have named our approach SMCDCT (scalable MC/DC percentage calculator using DCT). Our experimental study on forty-five C programs indicates 6.62% of average increase in MC/DC coverage.

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