FlowFusion: Pseudocode to Python Code with Flowchart Precision

Abstract

This paper introduces \"FlowFusion,\" an innovative tool designed to automate the conversion of pseudocode into flowcharts and subsequently translatethese flowcharts into Python co The citation FlowFusion refers to an AI-enabled system developed by this paper which performs pseudocode generation automation and conversion into flow charts and executable Python code. By using pretrained machine learning models, trained data structures, and regular expressions, FlowFusion promotes automation in software development that effectivelyreducesmanualeffortandimprovesprecision. FlowFusion makes use of binary trees to construct flowcharts that visually represent algorithmic logic. The system uses regular expressions for proper pseudocode snippet delineation so that it can be easily converted into enhanced Python code. Furthermore, various pseudocode formats are processed using natural language processing (NLP) to improve adaptability. The tool enforces best practices of designing program in structures, readable and maintainable codes with the application of abstract syntax tree.

Introduction

The text discusses FlowFusion, an automated tool designed to streamline the software development process by converting high-level pseudocode into detailed flowcharts and then into executable Python code. Traditionally, transforming pseudocode into code is manual, time-consuming, and error-prone. FlowFusion addresses these issues by using natural language processing (NLP) to interpret various pseudocode styles, automatically generating accurate flowcharts that visually represent algorithm logic, and then converting these flowcharts into clean, well-structured Python code with annotations.

The tool’s key benefits include reducing manual effort, minimizing errors, improving communication through consistent visualizations, and supporting maintainability of the generated code. The system architecture involves parsing pseudocode with predefined syntax rules, representing the logic internally using data structures (like binary trees), generating flowcharts with graphics libraries, and finally producing Python code.

FlowFusion distinguishes itself by relying on fundamental data structures and a rule-based approach rather than complex AI/NLP-heavy methods used in other systems, balancing simplicity with effectiveness. The implementation uses Python and libraries such as Regex, Graphviz, and Scikit-learn, with a command-line interface to input pseudocode following strict syntax guidelines. The output includes flowcharts in PNG format and Python code files.

Conclusion

Thispaperpresentsatooldesignedtoconvertpseudocodeinto flowchartsand Python code, leveraging simple data structures andalgorithms.Thetoolefficientlytranslatespseudocodeinto visual and executable formats, demonstrating a clear and educational approach to codeconversion. By employingbasic data structures, such as binary trees and regex, and avoiding the complexities of generative AI, the tool maintains transparency and ease of use. The implementation shows effectiveness in handling standard pseudocode styles, producing accurate flowcharts and corresponding Pythoncode.

References

[1] E. Knuth, The Art of Computer Programming, vol. 1,Fundamental Algorithms, 3rd ed. Boston, MA, USA: Addison-Wesley,1997. [2] P.Ganeand C.Sarson,Structured SystemsAnalysis:ToolsandTechniques.New York, NY, USA: Wiley, 1979. [3] J. Myers and C. Rosson, \"Flowchart-based Design Tools,\"JournalofSoftwareEngineering,vol.14,no.3,pp.223-235,Mar.2005. [4] A. Demetrescu, I. Finzi, and G. F. Italiano, \"AutomaticFlowchart- to- Code Conversion: A C++ Approach,\" ACMTransactions onProgrammingLanguages and Systems, vol. 19,no. 4, pp. 652-672,Nov. 1997. [5] B. Ormsby and M. McMillan, \"Flowcharting and CodeGeneration: An Evaluation,\" IEEE Transactions on SoftwareEngineering, vol. 28, no. 11,pp.1094-1105,Nov.2002. [6] E.W.Dijkstra,\"ADisciplineofProgramming,\"Prentice-Hall,1976. [7] P. Johnson and M. Wang, \"Challenges in AlgorithmTranslation and Visualization,\" International Journal of SoftwareEngineering,vol. 22, no. 2, pp. 125-140, Feb. 2008. [8] Visualgo,\"InteractiveVisualizationsofAlgorithms,\"[Online].Available: https://visualgo.net. [Accessed: Aug. 11, 2024]. [9] AlgoViz,\"AlgorithmVisualizationTool,\"[Online].Available:http://algoviz.org. [Accessed: Aug. 11, 2024]. [10] L.Chen,Y.Zhang,andZ.Liu,\"NaturalLanguageProcessingfor Algorithm Understanding,\" Journal of Artificial IntelligenceResearch,vol. 50,pp. 1-20, Jan. 2021. [11] J. Zhang, X. Wu, and H. Zhang, \"Machine LearningApproachesto Code Generation,\" ACM Computing Surveys,vol. 54, no. 6, pp. 1-34, Dec. 2021. [12] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein,IntroductiontoAlgorithms,3rded.,Cambridge,MA,USA:MITPress,2009. [13] B.Shneiderman,\"Flowchart-based ProgrammingConcepts,\"CommunicationsoftheACM,vol.20,no.6,pp.443-449,June1977. [14] N.E.FentonandS.L.Pfleeger,SoftwareMetrics:ARigorousandPractical Approach, 2nd ed., Boston, MA, USA:PWSPublishing,1997. [15] R.SedgewickandK.Wayne,Algorithms,4thed.,Boston,MA,USA: Addison-Wesley, 2011. [16] H.Abelson,G.J.Sussman,andJ.Sussman,StructureandInterpretation of Computer Programs, 2nd ed., MITPress,1996. [17] S.Diehl,SoftwareVisualization:VisualizingtheStructure,Behaviour,andEvolution of Software,Springer,2007. [18] A.Turing,\"OnComputableNumbers,withanApplicationtotheEntscheidungs problem,\" Proceedings of the LondonMathematicalSociety, vol. 2, no. 42, pp. 230-265, 1936. [19] P.Jalote,AnIntegratedApproachtoSoftwareEngineering,Springer, 3rd ed., 2005. [20] J.F.Allen,\"MaintainingKnowledgeAboutTemporalIntervals,\"CommunicationsoftheACM,vol.26,no.11,pp.832-843,Nov.1983. [21] S. Krishnamurthi and K. Fisler, \"Programming withDiagrams:Toward Software Visualization and FlowchartFormalism,\"SoftwareVisualizationSymposium,IEEE,2004.

Copyright

Copyright © 2025 Keerti Kahartmol, Sanket Parulekar, Nawazish Patel, Amaan Siddiqui, Raj Tiwari. 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.