2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)最新文献_第5页

Preface to 9th International Workshop on Model-Driven Requirements Engineering 第九届模型驱动需求工程国际研讨会前言

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/rew.2019.00009

N. Bencomo, G. Mussbacher, A. Moreira, J. Araújo, Pablo Sánchez

引用次数: 0

The 6th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE'19) 第六届需求工程人工智能国际研讨会(AIRE’19)

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/rew.2019.00043

Jaspreet Bhatia, P. Murukannaiah, Nan Niu, F. Dalpiaz

引用次数: 1

SysML Modeling Mistakes and Their Impacts on Requirements SysML建模错误及其对需求的影响

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00010

Mounifah Alenazi, Nan Niu, J. Savolainen

引用次数: 11

On the Use of Word Embeddings for Identifying Domain Specific Ambiguities in Requirements 用词嵌入识别需求中特定领域的歧义

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00048

S. Mishra, Arpit Sharma

{"title":"On the Use of Word Embeddings for Identifying Domain Specific Ambiguities in Requirements","authors":"S. Mishra, Arpit Sharma","doi":"10.1109/REW.2019.00048","DOIUrl":"https://doi.org/10.1109/REW.2019.00048","url":null,"abstract":"Software requirements are usually written in common natural language. An important quality criterion for each documented requirement is unambiguity. This simply means that all readers of the requirement must arrive at the same understanding of the requirement. Due to differences in the domain expertise of requirements engineer and other stakeholders of the project, it is possible that requirements contain several words that allow alternative interpretations. Our objective is to identify and detect domain specific ambiguous words in natural language text. This paper applies an NLP technique based on word embeddings to detect such ambiguous words. More specifically, we measure the ambiguity potential of most frequently used computer science (CS) words when they are used in other application areas or subdomains of engineering, e.g., aerospace, civil, petroleum, biomedical and environmental etc. Our extensive and detailed experiments with several different subdomains show that word embedding based techniques are very effective in identifying domain specific ambiguities. Our findings also demonstrate that this technique can be applied to documents of varying sizes. Finally, we provide pointers for future research.","PeriodicalId":166923,"journal":{"name":"2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117255675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

CrowdRE, User Feedback and GDPR: Towards Tackling GDPR Implications with Adequate Technical and Organizational Measures in an Effort-Minimal Way CrowdRE，用户反馈和GDPR:以最小的努力方式通过适当的技术和组织措施解决GDPR影响

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00038

Eduard C. Groen, M. Ochs

引用次数: 2

Ontology-Driven Security Requirements Recommendation for APT Attack 针对APT攻击的本体驱动安全需求建议

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00032

Min-Ju Kim, Sangeeta Dey, Seok-Won Lee

{"title":"Ontology-Driven Security Requirements Recommendation for APT Attack","authors":"Min-Ju Kim, Sangeeta Dey, Seok-Won Lee","doi":"10.1109/REW.2019.00032","DOIUrl":"https://doi.org/10.1109/REW.2019.00032","url":null,"abstract":"Advanced Persistent Threat (APT) is one of the cyber threats that continuously attack specific targets exfiltrate information or destroy the system [1]. Because the attackers use various tools and methods according to the target, it is difficult to describe APT attack in a single pattern. Therefore, APT attacks are difficult to defend against with general countermeasures. In these days, systems consist of various components and related stakeholders, which makes it difficult to consider all the security concerns. In this paper, we propose an ontology knowledge base and its design process to recommend security requirements based on APT attack cases and system domain knowledge. The proposed knowledge base is divided into three parts; APT ontology, general security knowledge ontology, and domain-specific knowledge ontology. Each ontology can help to understand the security concerns in their knowledge. While integrating three ontologies into the problem domain ontology, the appropriate security requirements can be derived with the security requirements recommendation process. The proposed knowledge base and process can help to derive the security requirements while considering both real attacks and systems.","PeriodicalId":166923,"journal":{"name":"2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124183902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Implementation-Centric Classification of Business Rules from Documents 以实现为中心的文档业务规则分类

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00047

Preethu Rose Anish, A. Sainani, Abdul Ahmed, S. Ghaisas

{"title":"Implementation-Centric Classification of Business Rules from Documents","authors":"Preethu Rose Anish, A. Sainani, Abdul Ahmed, S. Ghaisas","doi":"10.1109/REW.2019.00047","DOIUrl":"https://doi.org/10.1109/REW.2019.00047","url":null,"abstract":"In large multi-site multi-vendor projects, studying requirement documents to understand the problem domain and inferring possible solution to the posed problem is an important activity in Requirements Engineering. The process of reading User require-ments Specification (URS) to create Software Requirement Speci-fication (SRS) is a knowledge intensive activity that precedes sev-eral other important Software Engineering (SE) activities such as design and test plans. Automated Interpretation of the URS in terms of implementation-specific knowledge elements for software engineers' consumption has been reported in the past. The aim of such an interpretation is to reduce the effort associated with a manual extraction of knowledge elements and subsequently, their \"translation\" into primitives understood by those who must build the intended software. In this paper, we present a deep learning model for an implementation-centric classification of one such knowledge element, namely, business rules. We discuss an approach based on a Bidirectional Long Short Term Memory Network (BiLSTM) to capture the context information for each word, followed by an attention model to aggregate useful infor-mation from these words to get to the final classification. Our model adopts an end-to-end architecture that does not rely on any handcrafted features.","PeriodicalId":166923,"journal":{"name":"2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128179039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Bridging the Gap Between Requirements Document and Formal Specifications using Development Patterns 使用开发模式弥合需求文档和正式规范之间的差距

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-09-01 DOI: 10.1109/REW.2019.00026

Imen Sayar, J. Souquières

引用次数: 2

Requirements Engineering Challenges in Building AI-Based Complex Systems 构建基于人工智能的复杂系统中的需求工程挑战

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-08-30 DOI: 10.1109/REW.2019.00051

H. Belani, M. Vuković, Z. Car

引用次数: 51

Automated Generation of Test Models from Semi-Structured Requirements 从半结构化需求中自动生成测试模型

2019 IEEE 27th International Requirements Engineering Conference Workshops (REW) Pub Date : 2019-08-22 DOI: 10.1109/REW.2019.00053

Jannik Fischbach, Maximilian Junker, Andreas Vogelsang, Dietmar Freudenstein

{"title":"Automated Generation of Test Models from Semi-Structured Requirements","authors":"Jannik Fischbach, Maximilian Junker, Andreas Vogelsang, Dietmar Freudenstein","doi":"10.1109/REW.2019.00053","DOIUrl":"https://doi.org/10.1109/REW.2019.00053","url":null,"abstract":"[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 light-weight language for these test models are Cause-Effect-Graphs (CEG) that can be used to derive test cases. [Problem:] The creation of test models is laborious and we lack an automated solution that covers the entire process from requirement detection to test model creation. In addition, the majority of requirements is expressed in natural language (NL), which is hard to translate to test models automatically. [Principal Idea:] We build on the fact that not all NL requirements are equally unstructured. We found that 14% of the lines in requirements documents of our industry partner contain \"pseudo-code\"-like descriptions of business rules. We apply Machine Learning to identify such semi-structured requirements descriptions and propose a rule-based approach for their translation into CEGs. [Contribution:] We make three contributions: (1) an algorithm for the automatic detection of semi-structured requirements descriptions in documents, (2) an algorithm for the automatic translation of the identified requirements into a CEG and (3) a study demonstrating that our proposed solution leads to 86% time savings for test model creation without loss of quality.","PeriodicalId":166923,"journal":{"name":"2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115565826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7