Conceptual interpretation of SQL execution traces for program comprehension

Modern data-intensive software systems manipulate an increasing amount of heterogeneous data usually stored in a database. Maintaining such systems became a crucial and complex task, which is especially true due to the lack of sufficient documentation. In this context, program comprehension became a primary and an important step in this task. Unfortunately, the highly dynamic nature of interactions between a system and its database makes it hard to analyze these interactions with static analysis techniques. To this end, we propose a novel approach that combines dynamic analysis techniques and visualization to ease understanding data-intensive systems, by focusing on their database manipulation behavior. The approach consists of defining the conceptual interpretation of SQL execution traces in terms of a domain-specific, platform-independent model.