FlowFusion: Pseudocode to Python Code with Flowchart Precision

This paper introduces "FlowFusion," an innovative tool designed to automate the conversion of pseudocode into flowcharts and subsequently translate these 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 effectively reduces manual effort and improves precision. 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.