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Be it in debugging, testing, code review or, more recently, pair programmingwith AI assistance: in all these activities, software engineers need tounderstand source code. Accordingly, plenty of research is taking place in thefield to find out, for example, what makes code easy to understand and whichtools can best support developers in their comprehension process. And while anycode comprehension researcher certainly has a rough idea of what they mean whenthey mention a developer having a good understanding of a piece of code, todate, the research community has not managed to define source codecomprehension as a concept. Instead, in primary research on code comprehension,an implicit definition by task prevails, i.e., code comprehension is what theexperimental tasks measure. This approach has two negative consequences. First,it makes it difficult to conduct secondary research. Currently, each codecomprehension primary study uses different comprehension tasks and measures,and thus it is not clear whether different studies intend to measure the sameconstruct. Second, authors of a primary study run into the difficulty ofjustifying their design decisions without a definition of what they attempt tomeasure. An operationalization of an insufficiently described construct occurs,which poses a threat to construct validity.  The task of defining code comprehension considering the theory of the pastfifty years is not an easy one. Nor is it a task that every author of a primarystudy must accomplish on their own. Therefore, this paper constitutes areference work that defines source code comprehension and presents a conceptualframework in which researchers can anchor their empirical code comprehensionresearch.

Source Code Comprehension: A Contemporary Definition and Conceptual Model for Empirical Investigation