Large Language Models for Software Engineering: Survey and Open Problems

Большие языковые модели для программной инженерии: обзор и открытые проблемы
Angela Fan, Jie M. Zhang, Mark Harman, Shubho Sengupta, Beliz Gokkaya, Mitya Lyubarskiy, Shin Yoo
2023-05-14

LLMs for codingLarge Language ModelsSoftware Engineeringhallucinationshybrid techniques (traditional SE + LLMs)
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs' emergent properties bring novelty and creativity with applications right across the spectrum of Software Engineering activities including coding, design, requirements, repair, refactoring, performance improvement, documentation and analytics. However, these very same emergent properties also pose significant technical challenges; we need techniques that can reliably weed out incorrect solutions, such as hallucinations. Our survey reveals the pivotal role that hybrid techniques (traditional SE plus LLMs) have to play in the development and deployment of reliable, efficient and effective LLM-based SE.
1
Emergent properties of LLMs also create significant technical challenges, notably producing incorrect solutions and hallucinations that must be reliably detected and mitigated.
2
Hybrid approaches combining traditional Software Engineering techniques with LLMs are pivotal for developing reliable, efficient, and effective LLM-based SE systems.
3
LLMs exhibit emergent properties that enable novel, creative applications across many Software Engineering tasks (coding, design, requirements, repair, refactoring, performance, documentation, analytics).
4
The paper identifies open research challenges for applying LLMs to practical technical problems faced by software engineers.

Large Language Models applied to Software Engineering tasks

Capabilities, limitations, emergent behaviors, reliability challenges (e.g., hallucinations), and hybrid integration strategies of LLMs across software engineering activities (coding, design, requirements, repair, refactoring, performance, documentation, analytics)

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Publication Date
2023-05-14
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Authors
Angela Fan
Jie M. Zhang
Mark Harman
Shubho Sengupta
Beliz Gokkaya
Mitya Lyubarskiy
Shin Yoo
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