Artificial intelligence as an effective tool in the development of systems for automatic generation and optimization
Keywords:
artificial intelligence, software development, automatic code generation, code optimization, machine learning, programming assistance, software engineering, large language modelsAbstract
Artificial intelligence (AI) has become one of the most influential technologies of the 21st century, transforming various sectors thanks to its ability to process vast amounts of information, identify patterns, and automate complex tasks. In the field of software development, advances in language models, deep learning, and intelligent systems have enabled the creation of tools capable of automatically generating, analyzing, and optimizing code, offering new opportunities to improve the efficiency of programming processes. Currently, both students and professionals face challenges related to the increasing complexity of computer systems, reducing development times, detecting errors, and optimizing application performance. In response to this situation, this research aimed to propose the development of an AI-based system for the automatic generation, analysis, and optimization of code, in order to support programming activities and strengthen the technical skills of its users. To this end, a mixed-methods approach with a descriptive scope was employed, integrating quantitative and qualitative techniques to analyze the impact of AI in the context of software development. The study included a review of specialized scientific literature, the conceptual design of the proposed system, and the application of surveys to 87 participants, including students, teachers, and software developers from the city of Cúcuta. The results revealed a generally positive perception of the use of artificial intelligence tools in programming: 78% of respondents expressed familiarity with at least one intelligent assistance tool, and more than 70% considered that these technologies significantly improve productivity, reduce development time, and facilitate error detection. Furthermore, automatic code generation was identified as the most used and valued functionality, followed by error correction and support for learning programming.
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