Aspect-Oriented Programming (AOP) provides new modularization of software systems by encapsulating cross-cutting concerns. AspectJ, an AOP language, uses abstractions such as pointcuts, advice, and aspects to achieve AOP’s primary functionality. Faults in pointcuts can cause aspects to fail to satisfy their requirements. Hence, testing pointcuts is necessary in order to ensure correctness of aspects. In mutation testing of pointcuts (a type of fault-based pointcut testing), the number of mutants (i.e., variations) for pointcuts is usually large due to the usage of wildcards. It is tedious to manually identify effective mutants that are of appropriate strength and resemble closely the original pointcut expression, reflecting the kind of mistakes that developers may make. To reduce developers’ effort in this process, we have developed a new framework that automatically identifies the strength of each pointcut and generates pointcut mutants with different strengths. Developers can inspect the pointcut mutants and their join points for pointcut correctness or choose the mutants for conducting mutation testing. We conducted an empirical study on applying our framework on pointcuts from existing AspectJ programs. The results show that our framework can provide valuable assistance in generating effective mutants that are close to the original pointcuts and are of appropriate strength.

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