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相关论文: From Requirements to Test Cases: An NLP-Based Appr…

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It is a long-standing desire of industry and research to automate the software development and testing process as much as possible. In this process, requirements engineering (RE) plays a fundamental role for all other steps that build on…

软件工程 · 计算机科学 2023-09-26 Viju Sudhi , Libin Kutty , Robin Gröpler

Despite advances in machine learning (ML) and large language models (LLMs), rule-based natural language processing (NLP) systems remain active in clinical settings due to their interpretability and operational efficiency. However, their…

计算与语言 · 计算机科学 2025-06-23 Jianlin Shi , Brian T. Bucher

Natural Language Processing (NLP) is now a cornerstone of requirements automation. One compelling factor behind the growing adoption of NLP in Requirements Engineering (RE) is the prevalent use of natural language (NL) for specifying…

软件工程 · 计算机科学 2024-07-17 Mehrdad Sabetzadeh , Chetan Arora

This literature review studies the field of automated process extraction, i.e., transforming textual descriptions into structured processes using Natural Language Processing (NLP). We found that Machine Learning (ML) / Deep Learning (DL)…

计算与语言 · 计算机科学 2024-09-24 William Van Woensel , Soroor Motie

Software testing remains critical for ensuring reliability, yet traditional approaches are slow, costly, and prone to gaps in coverage. This paper presents an AI-driven framework that automates test case generation and validation using…

软件工程 · 计算机科学 2025-08-25 Saba Naqvi , Mohammad Baqar

[Context:] Model-based testing is an instrument for automated generation of test cases. It requires identifying requirements in documents, understanding them syntactically and semantically, and then translating them into a test model. One…

软件工程 · 计算机科学 2019-08-26 Jannik Fischbach , Maximilian Junker , Andreas Vogelsang , Dietmar Freudenstein

We describe our ongoing research that centres on the application of natural language processing (NLP) to software engineering and systems development activities. In particular, this paper addresses the use of NLP in the requirements…

计算与语言 · 计算机科学 2014-07-24 S. G. Macdonell , K. Min , A. M. Connor

Natural Language Processing (NLP) is widely used to support the automation of different Requirements Engineering (RE) tasks. Most of the proposed approaches start with various NLP steps that analyze requirements statements, extract their…

软件工程 · 计算机科学 2022-06-15 Riad Sonbol , Ghaida Rebdawi , Nada Ghneim

Improvement of software development methodologies attracts developers to automatic Requirement Formalisation (RF) in the Requirement Engineering (RE) field. The potential advantages by applying Natural Language Processing (NLP) and Machine…

计算与语言 · 计算机科学 2023-03-24 Shekoufeh Kolahdouz-Rahimi , Kevin Lano , Chenghua Lin

In this paper, we present a tool for analyzing .NET CLR event logs based on a novel method inspired by Natural Language Processing (NLP) approach. Our research addresses the growing need for effective monitoring and optimization of software…

软件工程 · 计算机科学 2025-02-07 Maxim Stavtsev , Sergey Shershakov

Initial fault detection and diagnostics are imperative measures to improve the efficiency, safety, and stability of vehicle operation. In recent years, numerous studies have investigated data-driven approaches to improve the vehicle…

系统与控制 · 电气工程与系统科学 2021-12-01 Ali Khodadadi , Soroush Ghandiparsi , Chen-Nee Chuah

Requirements Engineering (RE) is the initial step towards building a software system. The success or failure of a software project is firmly tied to this phase, based on communication among stakeholders using natural language. The problem…

软件工程 · 计算机科学 2021-12-07 Mohammad Kasra Habib , Stefan Wagner , Daniel Graziotin

Context: To reduce manual effort of extracting test cases from natural-language requirements, many approaches based on Natural Language Processing (NLP) have been proposed in the literature. Given the large amount of approaches in this…

软件工程 · 计算机科学 2020-03-25 Vahid Garousi , Sara Bauer , Michael Felderer

Natural language processing supported requirements engineering is an area of research and development that seeks to apply NLP techniques, tools and resources to a variety of requirements documents or artifacts to support a range of…

The application of Natural Language Processing (NLP) has achieved a high level of relevance in several areas. In the field of software engineering (SE), NLP applications are based on the classification of similar texts (e.g. software…

软件工程 · 计算机科学 2021-12-02 Eliane Maria De Bortoli Fávero , Dalcimar Casanova

This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis…

计算与语言 · 计算机科学 2018-06-18 Zexian Zeng , Yu Deng , Xiaoyu Li , Tristan Naumann , Yuan Luo

We investigate the use of Natural Language Inference (NLI) in automating requirements engineering tasks. In particular, we focus on three tasks: requirements classification, identification of requirements specification defects, and…

软件工程 · 计算机科学 2024-05-09 Mohamad Fazelnia , Viktoria Koscinski , Spencer Herzog , Mehdi Mirakhorli

Computer manufacturers typically offer platforms for users to report faults. However, there remains a significant gap in these platforms' ability to effectively utilize textual reports, which impedes users from describing their issues in…

Research in applying natural language processing (NLP) techniques to requirements engineering (RE) tasks spans more than 40 years, from initial efforts carried out in the 1980s to more recent attempts with machine learning (ML) and deep…

计算与语言 · 计算机科学 2022-04-12 Liping Zhao , Waad Alhoshan , Alessio Ferrari , Keletso J. Letsholo

System behavior is often based on causal relations between certain events (e.g. If event1, then event2). Consequently, those causal relations are also textually embedded in requirements. We want to extract this causal knowledge and utilize…

软件工程 · 计算机科学 2020-06-30 Jannik Fischbach , Benedikt Hauptmann , Lukas Konwitschny , Dominik Spies , Andreas Vogelsang
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