A novel Code transformation technique to guide test input generator
...These additional statements along with original program supplied into test executor to improve test data. It ensures that each atomic conditions have been invoked at least once true and once false. It is done to achieve higher MC/DC, because according to the definition of MC/DC it is required to achieve 100% condition coverage, which was not possible due to short-circuit evaluation by the compiler, due to which MC/DC was low and inadequate. This code transformation technique resolves the problem. It has applied Quince-McCluskey simplification technique to resolve complexness of predicate and then applying the method of inserting empty nested if-else conditional statements.
Java-HCT: An approach to increase MC/DC using Hybrid Concolic Testing
In our proposed work, we combine feedback-directed test cases generation with concolic testing to form Java-Hybrid Concolic Testing (Java-HCT). Java-HCT generates test cases combine so that, it create more number of test cases. Hence, through Java-HCT we achieve high MC/DC. Combinations of approaches represent different tradeoffs of completeness and scalability. We developed Java-HCT using RANDOOP, jCUTE, and COPECA. Combination of RANDOOP and jCUTE creates more test cases. COPECA is used to measure MC/DC\% using these generated test cases. Experimental study shows that Java-HCT produce better MC/DC\% through individual testing techniques(feedback-directed random testing and concolic testing).
CodeCover is a free glass box testing tool that measures statement, branch, loop, MC/DC, ?-operator, and sync- coverage. CodeCover supports coverage reports per each test case. Available languages: Java and COBOL.