Visualizing massively pruned execution traces to facilitate trace exploration

Execution traces provide precise pictures of the inner workings of software systems. They therefore support programmers in performing various maintenance tasks. However, exploring traces is difficult due to their size. They typically consist of thousands of participating functions and millions of control flow events. When exploring traces, it is particularly time-consuming to identify those time ranges within the trace that are relevant for the current maintenance task. In this paper, we propose a technique that supports programmers in exploring traces in that it first prunes less relevant calls from the trace and then provides condensed and repetition-aware visualizations that facilitate fast and accurate navigation even within very large traces. Repetitions in the trace are detected by a novel metrics to measure similarity between function calls in a fuzzy and adjustable way. The metrics helps to identify outlier calls in repetitive call sequences and guides programmers on control paths being likely relevant for their comprehension task. The technique is implemented within a prototypical analysis tool that copes with large C/C++ software systems. We demonstrate the concepts by means of a case study with our industrial partner.