Valuating requirements arguments in the online user's forum for requirements decision‐making: The CrowdRE‐VArg framework
- 14 August 2022
- journal article
- research article
- Published by Wiley in Software: Practice and Experience
- Vol. 52 (12) , 2537-2573
Abstract
User forums enable a large population of crowd‐users to publicly share their experience, useful thoughts, and concerns about the software applications in the form of user reviews. Recent research studies have revealed that end‐user reviews contain rich and pivotal sources of information for the software vendors and developers that can help undertake software evolution and maintenance tasks. However, such user‐generated information is often fragmented, with multiple viewpoints from various stakeholders involved in the ongoing discussions in the Reddit forum. In this article, we proposed a crowd‐based requirements engineering by valuation argumentation (CrowdRE‐VArg) approach that analyzes the end‐users discussion in the Reddit forum and identifies conflict‐free new features, design alternatives, or issues, and reach a rationale‐based requirements decision by gradually valuating the relative strength of their supporting and attacking arguments. The proposed approach helps to negotiate the conflict over the new features or issues between the different crowd‐users on the run by finding a settlement that satisfies the involved crowd‐users in the ongoing discussion in the Reddit forum using argumentation theory. For this purpose, we adopted the bipolar gradual valuation argumentation framework, extended from the abstract argumentation framework and abstract valuation framework. The automated CrowdRE‐VArg approach is illustrated through a sample crowd‐users conversation topic adopted from the Reddit forum about Google Map mobile application. Finally, we applied natural language processing and different machine learning algorithms to support the automated execution of the CrowdRE‐VArg approach. The results demonstrate that the proposed CrowdRE‐VArg approach works as a proof‐of‐concept and automatically identifies prioritized requirements‐related information for software engineers.Keywords
This publication has 62 references indexed in Scilit:
- Bridging the gap between software architecture rationale formalisms and actual architecture documents: An ontology-driven approachScience of Computer Programming, 2012
- Weighted argument systems: Basic definitions, algorithms, and complexity resultsArtificial Intelligence, 2011
- Recognizing entailment in intelligent tutoring systemsNatural Language Engineering, 2009
- Software Engineering Using RATionaleJournal of Systems and Software, 2008
- A study of the behavior of several methods for balancing machine learning training dataACM SIGKDD Explorations Newsletter, 2004
- EditorialACM SIGKDD Explorations Newsletter, 2004
- Rationale-Based Use Case SpecificationRequirements Engineering, 2002
- Machine learning in automated text categorizationACM Computing Surveys, 2002
- On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person gamesArtificial Intelligence, 1995
- Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit.Psychological Bulletin, 1968