Duplicated Code Pattern Mining in Visual Programming Languages

TL;DR

This paper introduces a scalable algorithm for detecting duplicated code patterns in Visual Programming Languages, addressing a gap in tools for maintaining code quality in VPL-based systems.

Contribution

It presents a novel pattern mining algorithm that leverages visual structures in VPLs to detect and explain duplicated code patterns, improving maintainability.

Findings

Duplication in OutSystems VPL codebases can reach 39%.

The proposed algorithm effectively detects duplicated code patterns.

Evaluation on real-world applications demonstrates scalability and accuracy.

Abstract

Visual Programming Languages (VPLs), coupled with the high-level abstractions that are commonplace in visual programming environments, enable users with less technical knowledge to become proficient programmers. However, the lower skill floor required by VPLs also entails that programmers are more likely to not adhere to best practices of software development, producing systems with high technical debt, and thus poor maintainability. Duplicated code is one important example of such technical debt. In fact, we observed that the amount of duplication in the OutSystems VPL code bases can reach as high as $39\%$. Duplicated code detection in text-based programming languages is still an active area of research with important implications regarding software maintainability and evolution. However, to the best of our knowledge, the literature on duplicated code detection for VPLs is very limited. We propose a novel and scalable duplicated code pattern mining algorithm that leverages the visual structure of VPLs in order to not only detect duplicated code, but also highlight duplicated code patterns that explain the reported duplication. The performance of the proposed approach is evaluated on a wide range of real-world mobile and web applications developed using OutSystems.