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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer)
Gusti Ayu Putri Saptawati Soekidjo
Institut Teknologi Bandung
Computer Science & IT

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DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS Bayu Samodra; Vebby Amelya Nora; Fitra Arifiansyah; Gusti Ayu Putri Saptawati Soekidjo; Muhamad Koyimatu
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6177

Abstract

The increasing complexity of programs in software development requires understanding and analysis of code structure, especially in Python, which dominates machine learning and data science applications. Manual static analysis is often time-consuming and prone to errors. Meanwhile, static analysis tools for Python, like PyCG and Code2graph, are still limited to generating call graphs without including dependency and control flow analysis. This research addresses these shortcomings by proposing the development of a web-based tool that integrates the generation of function call graphs, function dependency graphs, and control flow graphs using Abstract Syntax Tree (AST), Graphviz, and Streamlit. With an iterative SDLC methodology, this tool was developed gradually to visualize Python function code as a heterogeneous graph. Evaluation of 11 Python function codes showed a success rate of 95.45% in analyzing and visualizing Python function codes with various levels of complexity. The limitations of Graphviz present an opportunity for future research to focus on improving scalability and Python code analysis.
Co-Authors Bayu Samodra Fitra Arifiansyah Muhamad Koyimatu Vebby Amelya Nora