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Architectural Knowledge

General Introduction

Modern software development increasingly takes place in a geographically distributed context, involving multiple development teams and customers. In this setting, the Requirements Engineering (RE) activities of analysis, negotiation, and documentation cannot be efficiently performed with the traditional documentation-based approaches for three main reasons. First, two important types of knowledge about requirements are more easily lost across distributed sites: the rationale behind selecting and prioritizing requirements and the changes of requirements artifacts over time. Second, the misinterpretation of requirements is higher due to the social, cultural, and geographical differences. Third, it is more difficult to detect violating and conflicting requirements, when they are evolved across multiple sites. These problems in turn lead to high risk of project failure. The STAND project aims at tackling these problems by adopting a knowledge-based approach, following the current trend in software engineering. It will develop formal models, methods, and tooling to promote semantic-enabled collaboration in requirements analysis, negotiation and documentation in an integrated way. It will focus on documenting tacit requirements knowledge and further extracting formalized knowledge. The former will be shared and used among distributed stakeholders while the latter will be subject to automated reasoning. The tradeoff between cost and benefit of the approach will be analyzed to demonstrate its applicability.

Research Projects

  • STAND (Semantic-enabled collaboration Towards Analysis, Negotiation and Documentation on distributed requirements engineering)
    Grant: AFR
    Period: 2010-2014

Tools and Demos

For tools and demos regarding this research area, please visit our Resources page.

Recent Publications

(For more publications go to the publications page for Architectural Knowledge.)

Chen Yang, Peng Liang, and Paris Avgeriou. Assumptions and Their Management in Software Development: A Systematic Mapping Study. Information and Software Technology, 2017.   doi
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Chen Yang, Peng Liang, Paris Avgeriou, Ulf Eliasson, Rogardt Heldal, Patrizio Pelliccione, and Tingting Bi. An Industrial Case Study on an Architectural Assumption Documentation Framework. Journal of Systems and Software, 134(12):190–210, 2017.   doi
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Chen Yang, Peng Liang, Paris Avgeriou, Ulf Eliasson, Rogardt Heldal, and Patrizio Pelliccione. Architectural Assumptions and Their Management in Industry - An Exploratory Study. In Proceedings of the 11th European Conference on Software Architecture (ECSA). Springer, pages 191–207, 2017.   doi
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Chen Yang, Peng Liang, and Paris Avgeriou. A Survey on Software Architectural Assumptions. Journal of Systems and Software, 113(3):362–380, 2016.   doi
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