Architectural Antipatterns Research on Open Source Projects - Summer 2022

• Open Source Research Group, 2022-06-12
• Jie Wang, Hanggang Zhu and Yitao Cai @ ZJU
• Advisor: Prof. Zhiyuan Wan

A research project investigating architectural antipatterns and technical debt in software engineering, conducted at Zhejiang University (ZJU) in Summer 2022.

Overview

This research focuses on analyzing and detecting architectural antipatterns and technical debt in software systems. The project explores various detection techniques, tools, and methodologies for identifying and measuring architectural issues in software projects.

Key Research Areas

• Architectural smell detection and classification
• Technical debt measurement and analysis
• Software maintenance metrics
• Automated architecture analysis techniques
• Design Structure Matrix (DSM) analysis

Project Structure

• /ASE - Analysis of automated architecture analysis techniques and DV8 tool
• /BENCHMARK - Comparative analysis of different tools for detecting technical debt
• /JSS - Literature review and analysis of architectural smell detection techniques
• /notebook - Research notes and mind maps

Key Findings

The research explores several important aspects of software architecture:

1. Different approaches to detecting architectural smells:

   • Rules-based analysis
   • Graph-based analysis
   • Design Structure Matrix (DSM)
   • Model-driven approaches
   • Code smell analysis
   • History-based analysis

2. Various types of architectural smells:

   • Interface-based issues
   • Dependency-based problems
   • Change-based patterns
   • Concern-based issues

3. Evaluation of different tools and their effectiveness in detecting maintenance issues

Final Report

• Final Report in Chinese
• Poster in English

Honors:

• Best Poster Award of ZJUI 2022 Summer Research Competition

License

This project is licensed under the MIT License - see the LICENSE file for details.

Institution

Zhejiang University (ZJU) Open Source Research Group June 2022