Generation and Visualization of Static Function Call Graph for Large C Codebases

Author:

Badhya Sourabh S, ,G Shobha,

Abstract

As software systems evolve, there is a growing concern on how to manage and maintain a large codebase and fully understand all the modules present in it. Developers spend a significant amount of time analyzing dependencies before making any changes into codebases. Therefore, there is a growing need for applications which can easily make developers comprehend dependencies in large codebases. These applications must be able to analyze large codebases and must have the ability to identify all the dependencies, so that new developers can easily analyze the codebase and start making changes in short periods of time. Static analysis provides a means of analyzing dependencies in large codebases and is an important part of software development lifecycle. Static analysis has been proven to be extremely useful over the years in their ability to comprehend large codebases. Out of the many static analysis methods, this paper focuses on static function call graph (SFCG) which represents dependencies between functions in the form of a graph. This paper illustrates the feasibility of many tools which generate SFCG and locks in on Doxygen which is extremely reliant for large codebases. The paper also discusses the optimizations, issues and its corresponding solutions for Doxygen. Finally, this paper presents a way of representing SFCG which is easier to comprehend for developers.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Computer Science Applications,History,Education

Reference25 articles.

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2. B. G. Ryder, "Constructing the Call Graph of a Program" in IEEE Transactions on Software Engineering, vol. SE-5, no. 3, May 1979, pp. 216-226.

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4. D. V. Heesch, Doxygen. Available: https://www.doxygen.nl/index.html

5. M. Franz, C. T. Lopes, G. Huck, Y. Dong, O. Sumer, G. D. Bader. 'Cytoscape.js: a graph theory library for visualisation and analysis.' Bioinformatics. Volume 32, Issue 2, 15 January 2016, pp. 309-311.

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