conference-paper Open access

Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants

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Abstract

AI-based code assistants are promising tools that can facilitate and speed up code development. They exploit machine learning algorithms and natural language processing to interact with developers, suggesting code snippets (e.g., method implementations) that can be incorporated into projects. Recent studies empirically investigated the effectiveness of code assistants using simple exemplary problems (e.g., the re-implementation of well-known algorithms), which fail to capture the spectrum and nature of the tasks actually faced by developers.

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Publication details

DOI
10.1145/3643916.3644402
OpenAlex
W4391835304
Document type
conference-paper
Language
EN
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