Leveraging Large Language Models for Effective Coding

In the field of research software engineering, Large Language Models (LLMs) have emerged as powerful tools for enhancing coding practices. This presentation, "Leveraging LLMs for Effective Coding," delves into the practical applications of LLMs in automating and improving various aspects of the development process. By providing some empirical evidence from our firsthand experience using LLMs for software development, we explore how LLMs can significantly augment a developer's toolkit, making what are often time-consuming tasks more efficient and reliable. Automated test generation, for instance, not only speeds up the testing process but also ensures a more comprehensive coverage, leading to robust software products. Similarly, leveraging LLMs for code review can preemptively identify potential issues, optimizing code quality before it reaches human reviewers. Furthermore, the ability of LLMs to generate and update documentation in tandem with code changes addresses one of the most common challenges in software development, maintaining accurate and helpful documentation. Beyond these key areas, the presentation also touches upon additional use cases where LLMs can make a significant impact, including debugging assistance, code implementation, and code refactoring, among others. We discuss effective ways for integrating LLMs into the development workflow, emphasizing the importance of clear communication, context provision, and iterative refinement. Ethical considerations, particularly in addressing potential biases and ensuring responsible use, are also explored. Join us as we navigate the practicalities of incorporating LLMs into coding practices, aiming to inspire developers to harness these AI tools for more efficient, high-quality software development. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE- NA0003525.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-15
DOI
https://doi.org/10.5281/zenodo.13946887
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
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article

Leveraging Large Language Models for Effective Coding

Zenodo (CERN European Organization for Nuclear Research)
Software Engineering Research
article

Leveraging Large Language Models for Effective Coding

article en

Abstract

In the field of research software engineering, Large Language Models (LLMs) have emerged as powerful tools for enhancing coding practices. This presentation, "Leveraging LLMs for Effective Coding," delves into the practical applications of LLMs in automating and improving various aspects of the development process. By providing some empirical evidence from our firsthand experience using LLMs for software development, we explore how LLMs can significantly augment a developer's toolkit, making what are often time-consuming tasks more efficient and reliable. Automated test generation, for instance, not only speeds up the testing process but also ensures a more comprehensive coverage, leading to robust software products. Similarly, leveraging LLMs for code review can preemptively identify potential issues, optimizing code quality before it reaches human reviewers. Furthermore, the ability of LLMs to generate and update documentation in tandem with code changes addresses one of the most common challenges in software development, maintaining accurate and helpful documentation. Beyond these key areas, the presentation also touches upon additional use cases where LLMs can make a significant impact, including debugging assistance, code implementation, and code refactoring, among others. We discuss effective ways for integrating LLMs into the development workflow, emphasizing the importance of clear communication, context provision, and iterative refinement. Ethical considerations, particularly in addressing potential biases and ensuring responsible use, are also explored. Join us as we navigate the practicalities of incorporating LLMs into coding practices, aiming to inspire developers to harness these AI tools for more efficient, high-quality software development. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE- NA0003525.

Zenodo (CERN European Organization for Nuclear Research)
Sandia National Laboratories (US)
Partnerships for the goals
Openalex Percentile: Top 37%
Software Engineering Research
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