Automated Query Generation for Design Pattern Mining in Source Code

TL;DR

This paper presents Model2Mine, an automated approach for generating SPARQL queries from UML diagrams to identify design patterns in source code, reducing manual effort and improving accuracy.

Contribution

Introduction of Model2Mine, a novel method for automatic query generation for design pattern mining from UML diagrams, enhancing efficiency and accuracy.

Findings

Model2Mine can generate queries for creational, behavioral, and structural patterns.

It has a slight performance overhead compared to manual query creation.

Accuracy is comparable or better than existing techniques.

Abstract

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.