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DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS

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Titel: DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS
Autoren: Samodra, Bayu, Nora, Vebby Amelya, Arifiansyah, Fitra, Putri Saptawati Soekidjo, Gusti Ayu, Koyimatu, Muhamad
Quelle: JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer); Vol. 10 No. 3 (2025): JITK Issue February 2025; 690-697 ; 2527-4864 ; 2685-8223 ; 10.33480/jitk.v10i3
Verlagsinformationen: LPPM Nusa Mandiri
Publikationsjahr: 2025
Bestand: ejournal.nusamandiri.ac.id (STMIK Nusa Mandiri)
Schlagwörter: abstract syntax tree, control flow graph, graphviz, python, SDLC
Beschreibung: 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.
Publikationsart: article in journal/newspaper
Dateibeschreibung: application/pdf
Sprache: English
Relation: https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177/1353; https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177
Verfügbarkeit: https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177
Rights: Copyright (c) 2025 Bayu Samodra, Vebby Amelya Nora, Fitra Arifiansyah, Gusti Ayu Putri Saptawati Soekidjo, Muhamad Koyimatu ; http://creativecommons.org/licenses/by-nc/4.0
Dokumentencode: edsbas.C6A907B8
Datenbank: BASE
Beschreibung
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.