Automatic Dependency Conflict Detection Tool for Software Projects

Abstract

Software projects today depend on numerous external libraries and packages to provide additional functionality and improve development efficiency. However, managing these dependencies in large software systems can become complex and often leads to dependency conflicts, especially when different components require incompatible versions of the same library. These conflicts may cause system failures, security vulnerabilities, and maintenance difficulties. Therefore, detecting and resolving dependency conflicts early in the development process is an important challenge in modern software engineering. This paper presents an Automatic Dependency Conflict Detection Tool for Large Software Projects that analyzes dependency files and identifies potential conflicts in software environments. The system uses a dependency parsing mechanism to extract dependency information from project files and applies rule-based analysis to detect direct and transitive dependency conflicts. Additionally, the system provides suggestions for resolving detected conflicts and predicts potential risk levels associated with them. A web-based interface is also developed to visualize the analysis results and provide developers with an easy way to understand dependency relationships. The proposed system improves dependency management by providing automated detection, conflict analysis, and visualization of dependency structures. Experimental results demonstrate that the tool effectively identifies dependency conflicts and assists developers in resolving them quickly. This approach enhances software stability and reduces development time in large-scale software projects. Future enhancements may include integrating machine learning techniques for more intelligent conflict prediction and automated dependency optimization.

Introduction

Modern software development relies on numerous third-party libraries, which accelerates development but often causes dependency conflicts when multiple modules require incompatible versions of the same library. These conflicts can lead to build failures, runtime errors, and security vulnerabilities, and manually managing them in large projects is difficult.

To address this, an Automatic Dependency Conflict Detection Tool is proposed. The system parses dependency files (e.g., requirements.txt, package.json) to extract library versions, analyses both direct and transitive dependencies, detects conflicts, predicts their risk levels, and suggests resolutions such as upgrading or replacing conflicting packages. A web-based visualization dashboard displays dependency structures, conflicts, risk scores, and recommended solutions, helping developers manage large-scale projects efficiently.

The tool was implemented using Python with the Flask framework and visualized using Chart.js, and testing demonstrated effective conflict detection, accurate risk assessment, and clear presentation of dependency relationships, significantly reducing manual debugging effort and improving software stability.

Conclusion

In this paper, an Automatic Dependency Conflict Detection Tool for Large Software Projects has been proposed to address the challenges associated with managing dependencies in modern software development. Large software systems often rely on multiple external libraries, which may lead to compatibility issues when different modules require conflicting versions of the same dependency. The proposed system analyses dependency files, extracts library information through a dependency parsing mechanism, and automatically detects both direct and transitive dependency conflicts. The implemented tool provides developers with a clear understanding of dependency relationships and highlights potential conflicts that may affect software stability. In addition, the system offers suggested solutions for resolving conflicts and includes a risk prediction mechanism that evaluates the severity of detected conflicts. The visualization dashboard presents the analysis results in an easy-to-understand format, helping developers quickly identify and address dependency issues. The results demonstrate that the proposed system can effectively detect dependency conflicts and assist developers in improving dependency management in large software projects. By automating the conflict detection process and providing meaningful insights, the system helps reduce debugging time and improves overall software reliability.

References

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Copyright

Copyright © 2026 Ms. Savitha R, Ms. Udhayarani K S, Mrs. R Sindhiya. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.