Development of An Automated Pseudocode to Python Translator Application with Three Stage Compilation Visualization For Learning Compilation Techniques

Abstract

Advances in information technology have increased the demand for more effective programming learning approaches, particularly for vocational high school students and early-stage university students who often experience difficulties in understanding algorithmic logic and programming language structures. One of the main challenges lies in the transition from pseudocode, which is conceptual in nature, to actual program code such as Python, where misunderstandings of control structures, data types, and logical flow frequently lead to syntactic and logical errors. This study aims to develop an automatic translator application from pseudocode to Python integrated with a three-stage compilation visualization, namely tokenization, parsing, and code generation. The research adopts a Research and Development (R&D) approach using a prototyping model. The web-based application is developed using the Flask framework and provides features for pseudocode input, interactive visualization of compilation stages, direct execution of generated Python code, and downloading of the conversion results. The system is designed to recognize common pseudocode structures, including IF–ELSE, FOR, WHILE, FUNCTION, INPUT, PRINT, SET, and RETURN, and to automatically handle input data types based on contextual usage. Evaluation is conducted through testing various dynamic pseudocode scenarios with different levels of complexity and input simulations. The expected outcome is a system that enhances learners’ understanding of fundamental programming concepts and compilation processes, reduces syntactic errors, and supports interactive self-directed learning. This research contributes to the development of web-based programming learning tools through the integration of automatic translation and compilation process visualization.