Two Rule-Based Natural Language Strategies for Requirements Discovery and Classification in Open Source Software Development Projects

Open source projects do have requirements; they are, however, mostly informal text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requiremen...

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Published in:Journal of management information systems Vol. 28; no. 4; pp. 11 - 38
Main Authors: Vlas, Radu E., Robinson, William N.
Format: Journal Article
Language:English
Published: Abingdon Routledge 01.04.2012
M. E. Sharpe
Sharpe
Taylor & Francis Ltd
Subjects:
Automation
Betriebliche Dokumentation
Classification
Classifiers
Comparative analysis
Computer programmes
Computer software
Copyright
Datasets
Development programs
Development projects
Development strategies
Error analysis
Grammar
Information classification
Information technology
Keywords
Klassifikation
Language
Natural language
Natural language processing
Open Source
Open source software
Project management
Projektmanagement
Property
requirements classification
requirements discovery
Social engineering
Software
Software development
Software engineering
software requirements
Softwareentwicklung
Special Section: Creating Value with Information
Sprachverarbeitung
Studies
Systems development
ISSN:0742-1222, 1557-928X
Online Access:Get full text
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Abstract Open source projects do have requirements; they are, however, mostly informal text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects, error prone. Automated analysis of natural language requirements, even partial, will be of great benefit. Toward that end, we describe the design and validation of an automated natural language requirements classifier for open source projects. We compare two strategies for recognizing requirements in open forums of software features. Our results suggest that classifying text at the forum postaggregation and sentence aggregation levels may be effective. Our results suggest that it can reduce the effort required to analyze requirements of open source projects.
AbstractList Open source projects do have requirements; they are, however, mostly informal text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects, error prone. Automated analysis of natural language requirements, even partial, will be of great benefit. Toward that end, we describe the design and validation of an automated natural language requirements classifier for open source projects. We compare two strategies for recognizing requirements in open forums of software features. Our results suggest that classifying text at the forum postaggregation and sentence aggregation levels may be effective. Our results suggest that it can reduce the effort required to analyze requirements of open source projects. [PUBLICATION ABSTRACT]
Open source projects do have requirements; they are, however, mostly informal text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects, error prone. Automated analysis of natural language requirements, even partial, will be of great benefit. Toward that end, we describe the design and validation of an automated natural language requirements classifier for open source projects. We compare two strategies for recognizing requirements in open forums of software features. Our results suggest that classifying text at the forum postaggregation and sentence aggregation levels may be effective. Our results suggest that it can reduce the effort required to analyze requirements of open source projects.
Author Robinson, William N.
Vlas, Radu E.
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  organization: Department of Computer Information Systems at the J. Mack Robinson College of Business, Georgia State University
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  doi: 10.2753/MIS0742-1222220408
– volume: 2
  start-page: 957
  issue: 5
  year: 2010
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  article-title: REAS: An interactive semi-automated system for software requirements elicitation assistance
  publication-title: International Journal of Engineering Science and Technology
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  article-title: Mining aspects in requirements
– volume: 3
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  article-title: Requirements traceability: Theory and practice
  publication-title: Annals of Software Engineering
  doi: 10.1023/A:1018969401055
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Snippet Open source projects do have requirements; they are, however, mostly informal text descriptions found in requests, forums, and other correspondence....
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SubjectTerms Automation
Betriebliche Dokumentation
Classification
Classifiers
Comparative analysis
Computer programmes
Computer software
Copyright
Datasets
Development programs
Development projects
Development strategies
Error analysis
Grammar
Information classification
Information technology
Keywords
Klassifikation
Language
Natural language
Natural language processing
Open Source
Open source software
Project management
Projektmanagement
Property
requirements classification
requirements discovery
Social engineering
Software
Software development
Software engineering
software requirements
Softwareentwicklung
Special Section: Creating Value with Information
Sprachverarbeitung
Studies
Systems development
Title Two Rule-Based Natural Language Strategies for Requirements Discovery and Classification in Open Source Software Development Projects
URI https://www.tandfonline.com/doi/abs/10.2753/MIS0742-1222280402
https://www.jstor.org/stable/41713856
http://www.econis.eu/PPNSET?PPN=718796225
https://www.proquest.com/docview/1366387158
https://www.proquest.com/docview/1024213121
Volume 28
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