Performance Comparison of Query-based Techniques for Anti-Pattern Detection

Context: Program queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Abstract Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries.

Objective: Our paper investigates the costs and benefits of using the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by four different general-purpose model query techniques based on native Java code, OCL evaluation and (incremental) graph pattern matching.

Method: We provide in-depth comparison of these techniques on the source code of 28 Java projects using anti-pattern queries taken from refactoring operations in different usage profiles.

Results: Our results show that general purpose model queries can outperform hand-coded queries by 2-3 orders of magnitude, with the trade-off of an increased in memory consumption and model load time of up to an order of magnitude.

Conclusion: The measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.