Poster: Hybrid Traversal: Efficient Source Code Analysis at Scale

Source code analysis at a large scale is useful for solving many software engineering problems, however, could be very expensive, thus, making its use difficult. This work proposes hybrid traversal, a technique for performing source code analysis over control flow graphs more efficiently. Analysis over a control flow graph requires traversing the graph and it can be done using several traversal strategies. Our observation is that no single traversal strategy is suitable for different analyses and different graphs. Our key insight is that using the characteristics of the analysis and the properties of the graph it is possible to select a most efficient traversal strategy for a pair. Our evaluation using a set of analyses with different characteristics and a large dataset of graphs with different properties shows up to 30% reduction in the analysis time. Further, the overhead of our technique for selecting the most efficient traversal strategy is very low; between 0.01%-0.2%.