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A Knowledge Management Framework in Software Requirements Engineering Based on the SECI Model
Open accessAbstract
Software requirements engineering deals with: elicitation, specification, and validation of software requirements. Furthermore there is a need to facilitate collaboration amongst stakeholders and analysts. Fewer efforts were deployed to support them in performing their job on a day to day basis. To solve this problem we use knowledge management for software requirements engineering. This paper proposes a knowledge management framework, based on the SECI model of knowledge creation, aimed at exploiting tacit and explicit knowledge related to software requirements within a given software project. The core part of the proposed framework is a set of four sub systems “Socializer”; “Externalizer”; “Combiner”; and “Internalizer”, attached to a couple of domain ontologies and a set of knowledge assets. Indeed we aim to facilitate a semantic based interpretation of knowledge assets related to software requirements by restricting their interpretation through the application domain and software requirements ontologies. We anticipate that this framework would be very helpful for stakeholders as well as analysts to exchange and manage their knowledge within a given software project. We show in the case study, through a virtual payroll project using the two-step approach: domain level requirements plus design level requirements, how the key elicitation SRE techniques are used during the first phase of domain requirements elicitation through the four subsystems of our framework.
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“SECI has been applied to software engineering (Rus and Lindvall 2002; Bjørnson and Dingsøyr 2008; Chikh 2011; Astorga-Vargas et al. 2017) and digital education ( ˙ Zatuchin 2024), but has not been applied to AI agent memory systems.”
From From Organizational Knowledge to AI Agent Memory: Empirical Validation of the SECI Model on the LongMemEval Benchmark (2026) · cites this paper as Chikh 2011
In the citing paper
“SECI has been applied to software engineering (Rus and Lindvall 2002; Bjørnson and Dingsøyr 2008; Chikh 2011; Astorga-Vargas et al. 2017) and digital education ( ˙ Zatuchin 2024), but has not been applied to AI agent memory systems.”
From From Organizational Knowledge to AI Agent Memory: Empirical Validation of the SECI Model on the LongMemEval Benchmark (2026) · cites this paper as Chikh 2011
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Research works printed but not linked: 29
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Cited by
Sorted by citations
Żatuchin, D. (2026) · Research Square (preprint) · doi:10.21203/rs.3.rs-9801639/v1
Metadata
- Authors
- Chikh, A.
- Affiliations
- King Saud University (SA)
- Corresponding author
- Chikh, Azeddine
- Venue
- Journal of Software Engineering and Applications
- Publisher
- Scientific Research Publishing, Inc.
- Published
- 2011
- Volume
- 04
- Issue
- 12
- Pages
- 718-728
- ISSN
- 1945-3116 (ISSN-L)
- 1945-3124
- OpenAlex
- W2031065205
- Cited by
- 20
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 1 · 2017: 5 · 2016: 2 · 2015: 4 · 2014: 2
- FWCI
- 1.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Software Engineering and Applications (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Keywords
- knowledge management, software requirements engineering, SECI model, tacit knowledge, explicit knowledge, knowledge production, domain ontology, knowledge assets, requirements analysis, stakeholder collaboration, knowledge management framework
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