Automated Query Generation for Design Pattern Mining in Source Code
This addresses the tedious manual effort in design pattern mining for maintenance engineers, though it is incremental as it builds on existing techniques.
The paper tackles the problem of manually specifying queries for design pattern mining in source code by introducing Model2Mine, which automatically generates SPARQL queries from UML diagrams, achieving comparable or better accuracy than existing techniques with slight performance overhead.
Identifying which design patterns already exist in source code can help maintenance engineers gain a better understanding of the source code and determine if new requirements can be satisfied. There are current techniques for mining design patterns, but some of these techniques require tedious work of manually labeling training datasets, or manually specifying rules or queries for each pattern. To address this challenge, we introduce Model2Mine, a technique for automatically generating SPARQL queries by parsing UML diagrams, ensuring that all constraints are appropriately addressed. We discuss the underlying architecture of Model2Mine and its functionalities. Our initial results indicate that Model2Mine can automatically generate queries for the three types of design patterns (i.e., creational, behavioral, structural), with a slight performance overhead compared to manually generated queries, and accuracy that is comparable, or perform better than, existing techniques.