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Researchers and practitioners are usually eager to develop, test and experiment with new ideas and techniques to analyze software systems and/or to present results of such analyzes, for instance new kind of visualizations or analysis tools. However, often these novel and certainly promising ideas are never properly and seriously empirically evaluated. Instead their inventors just resort to anecdotal evidence to substantiate their beliefs and claims that their ideas and the realizations thereof are actually useful in theory and practice. The chief reason why proper validation is often neglected is that serious evaluation of any newly realized technique, tool, or concept in reverse engineering is time-consuming, laborious, and often tedious. Furthermore, we assume that there is also a lack of knowledge or experience concerning empirical evaluation in our community. This paper hence sketches some ideas and discusses best practices of how we can still, with moderate expenses, come up with at least some empirical validation of our next project in the field of reverse engineering.

Why and How to Substantiate the Good of our Reverse Engineering Tools?