OpenAi's GPT4 as coding assistant
Lefteris Moussiades, George Zografos

TL;DR
This paper evaluates GPT-4's effectiveness as a coding assistant, demonstrating its superior performance in answering development questions, generating reliable code, and aiding debugging, which could transform software development practices.
Contribution
It provides a comprehensive assessment of GPT-4's capabilities in coding tasks, highlighting its potential to enhance programmer productivity and reshape development workflows.
Findings
GPT-4 outperforms GPT-3.5 in coding tasks
GPT-4 produces reliable and accurate code
GPT-4 significantly improves debugging assistance
Abstract
Lately, Large Language Models have been widely used in code generation. GPT4 is considered the most potent Large Language Model from Openai. In this paper, we examine GPT3.5 and GPT4 as coding assistants. More specifically, we have constructed appropriate tests to check whether the two systems can a) answer typical questions that can arise during the code development, b) produce reliable code, and c) contribute to code debugging. The test results are impressive. The performance of GPT4 is outstanding and signals an increase in the productivity of programmers and the reorganization of software development procedures based on these new tools.
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Taxonomy
TopicsSoftware Engineering Research · Topic Modeling · Scientific Computing and Data Management
