Year: 2025
Type: preprint
Abstract: Large language models have become a popular tool in software development, providing coding assistance. The proper measurement of the accuracy and reliability of the code produced by such tools is a challenge due to natural language prompts. We propose a simple pipeline that uses state-of-the-art implementation of classic and universal genres of algorithms and data structures. We focus on measuring the quality of TabbyML code assistant due to its open licence and the flexibility in the choice of the language model. Our results presented as cyclomatic complexity, Halstead's Bugs \& Effort and four text-based similarity matrices depict the usability of TabbyML in coding assistance tasks.
Source: arXiv (Cornell University)
Authors: Borek, Marta, Nowak, Robert
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4414829265
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