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Large Language Models (LLMs) are revolutionizing Software Engineering (SE) by introducing innovative methods for tasks such as collecting requirements, designing software, generating code, and creating test cases, among others. This article…

软件工程 · 计算机科学 2024-05-06 Malik Abdul Sami , Zeeshan Rasheed , Muhammad Waseem , Zheying Zhang , Tomas Herda , Pekka Abrahamsson

Successful software projects depend on the quality of software requirements. Creating high-quality requirements is a crucial step toward successful software development. Effective support in this area can significantly reduce development…

Requirements Engineering (RE) is a critical phase in software development including the elicitation, analysis, specification, and validation of software requirements. Despite the importance of RE, it remains a challenging process due to the…

软件工程 · 计算机科学 2023-11-02 Chetan Arora , John Grundy , Mohamed Abdelrazek

Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them…

软件工程 · 计算机科学 2024-05-16 Andreas Vogelsang , Jannik Fischbach

This paper presents a focused literature survey on the use of large language models (LLM) to assist in writing formal specifications for software. A summary of thirty-five key papers is presented, including examples for specifying programs…

软件工程 · 计算机科学 2025-06-16 Arshad Beg , Diarmuid O'Donoghue , Rosemary Monahan

Normative requirements specify social, legal, ethical, empathetic, and cultural (SLEEC) norms that must be observed by a system. To support the identification of SLEEC requirements, numerous standards and regulations have been developed.…

软件工程 · 计算机科学 2025-07-09 Alex Kleijwegt , Sinem Getir Yaman , Radu Calinescu

Software correctness is ensured mathematically through formal verification, which involves the resources of generating formal requirement specifications and having an implementation that must be verified. Tools such as model-checkers and…

软件工程 · 计算机科学 2025-08-29 Arshad Beg , Diarmuid O'Donoghue , Rosemary Monahan

Generative artificial intelligence (GAI), specifically large language models (LLMs), are increasingly used in software engineering, mainly for coding tasks. However, requirements engineering - particularly requirements validation - has seen…

软件工程 · 计算机科学 2026-02-10 Adam Trendowicz , Daniel Seifert , Andreas Jedlitschka , Marcus Ciolkowski , Anton Strahilov

The advent of Large Language Models (LLMs) has ushered in a new era for design science in Information Systems, demanding a paradigm shift in tailoring LLMs design for business contexts. We propose and test a novel framework to customize…

计算机与社会 · 计算机科学 2024-05-15 Wen Wang , Zhenyue Zhao , Tianshu Sun

Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in critical scenarios. This paper introduces a rigorously…

计算与语言 · 计算机科学 2023-11-21 Saizhuo Wang , Zhihan Liu , Zhaoran Wang , Jian Guo

The rapid advancement of large language models (LLMs) has revolutionized artificial intelligence, introducing unprecedented capabilities in natural language processing and multimodal content generation. However, the increasing complexity…

软件工程 · 计算机科学 2024-11-27 Shenao Wang , Yanjie Zhao , Xinyi Hou , Haoyu Wang

Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled widespread adoption, evolving demands in application…

软件工程 · 计算机科学 2024-11-20 Dawen Zhang , Xiwei Xu , Chen Wang , Zhenchang Xing , Robert Mao

Recent frontier large language models (LLMs) have shown strong performance in identifying security vulnerabilities in large, mature open-source systems. As LLM-generated code becomes increasingly common, a natural goal is to prevent such…

软件工程 · 计算机科学 2026-05-13 Zhaorui Li , Chengyu Song

Cognitive systems generally require a human to translate a problem definition into some specification that the cognitive system can use to attempt to solve the problem or perform the task. In this paper, we illustrate that large language…

人工智能 · 计算机科学 2024-06-12 Robert E. Wray , James R. Kirk , John E. Laird

The majority of research around Large Language Models (LLM) application to software development has been on the subject of code generation. There is little literature on LLMs' impact on requirements engineering (RE), which deals with the…

软件工程 · 计算机科学 2025-02-05 Cory Hymel , Hiroe Johnson

This article analyzes the use of Large Language Models (LLMs) as support for the conceptual modeling of relational databases through the automatic generation of Entity-Relationship (ER) diagrams from natural language requirements. The…

Design assistants are frameworks, tools or applications intended to facilitate both the creative and technical facets of design processes. Large language models (LLMs) are AI systems engineered to analyze and produce text resembling human…

人机交互 · 计算机科学 2025-02-12 Swaroop Panda

Large language models (LLMs) process and predict sequences containing text to answer questions, and address tasks including document summarization, providing recommendations, writing software and solving quantitative problems. We provide a…

数值分析 · 数学 2026-02-02 Ricardo Baptista , Andrew Stuart , Son Tran

The growing popularity and widespread use of software applications (apps) across various domains have driven rapid industry growth. Along with this growth, fast-paced market changes have led to constantly evolving software requirements.…

软件工程 · 计算机科学 2025-07-28 Pragyan KC , Rambod Ghandiparsi , Thomas Herron , John Heaps , Mitra Bokaei Hosseini

A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as writing formal specifications is an error-prone and…

计算机科学中的逻辑 · 计算机科学 2023-03-10 Matthias Cosler , Christopher Hahn , Daniel Mendoza , Frederik Schmitt , Caroline Trippel
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