Architectural mismatch or why it's hard to build systems out of existing parts
Proceedings of the 17th international conference on Software engineering
A formal basis for architectural connection
ACM Transactions on Software Engineering and Methodology (TOSEM)
A Classification and Comparison Framework for Software Architecture Description Languages
IEEE Transactions on Software Engineering
Towards a taxonomy of software connectors
Proceedings of the 22nd international conference on Software engineering
Data management and transfer in high-performance computational grid environments
Parallel Computing - Parallel data-intensive algorithms and applications
The 4+1 View Model of Architecture
IEEE Software
ICSE '93 Selected papers from the Workshop on Studies of Software Design
Higher-order architectural connectors
ACM Transactions on Software Engineering and Methodology (TOSEM)
Architectural Knowlege Management Strategies: Approaches in Research and Industry
SHARK-ADI '07 Proceedings of the Second Workshop on SHAring and Reusing architectural Knowledge Architecture, Rationale, and Design Intent
ArchVoc--Towards an Ontology for Software Architecture
SHARK-ADI '07 Proceedings of the Second Workshop on SHAring and Reusing architectural Knowledge Architecture, Rationale, and Design Intent
Software Connector Classification and Selection for Data-Intensive Systems
IWICSS '07 Proceedings of the Second International Workshop on Incorporating COTS Software into Software Systems: Tools and Techniques
Software connectors for highly distributed and voluminous data-intensive systems
Software connectors for highly distributed and voluminous data-intensive systems
Hi-index | 0.00 |
Ever-growing amounts of data that must be distributed from data providers to consumers across the world necessitate a greater understanding of the software architectural implications of choosing data movement technologies. Currently, this understanding is mired in the minds of software architects who have been there before, and who rely on past intuition and choices, failing to properly document their rationale and context. In this paper we describe a software architecture-based decision making framework called DISCO for selecting data movement technologies, or software connectors. DISCO effectively captures (traditionally undocumented) insight, observation and ultimately architectural knowledge about the connectors, demonstrating the effectiveness of using such information to accurately encode the connector selection decision making process