Year: 2026
Type: article
Abstract: Design smells are structural flaws that, if not detected early, can impair software quality and increase maintenance costs. Traditional detection approaches are language-specific and rely on low-level metrics, making them ineffective for heterogeneous, multilingual systems. This paper presents Ontology-Driven Design Detector (OD3), a language-agnostic framework for detecting design smells at the design stage. OD3 reverse-engineers source code from Java, C++, C#, Ruby, and Python into a unified semantic ontology and applies rule-based reasoning to identify violations of Object-Oriented (OO) design principles. Its key contributions are: (i) detecting design smells in multilingual software projects, (ii) defining semantic representations of smells to improve interpretability, (iii) reducing incorrect detections through context-aware reasoning, (iv) introducing a catalog of cross-language design smells, and (v) validating the approach on 10 multilingual systems, achieving a precision and recall of 0.91 and 0.92, respectively. These results support scalable, early-stage detection of design flaws across heterogeneous software systems while maintaining high semantic accuracy. The proposed framework is designed to operate efficiently within High-Performance Computing (HPC) environments, where parallel ontology reasoning and distributed semantic processing facilitate the analysis of large multilingual software repositories. Consequently, the framework contributes to Sustainable Development Goal (SDG) 9 by supporting intelligent, scalable software engineering infrastructure.
Source: Discover Computing
Authors: Sabiyyah Sabir, Ghulam Rasool, Tariq Umer, Harun Elkiran, Jawad Rasheed
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,520
OpenAlex ID: W7212378752