2014/02/24 by Richard McClatchey, McClatchey, Richard, Andrew Branson +3 · 4 citations
Business, Management and Accounting · Computer Science · Decision Sciences · #Advanced Database Systems and Queries #Business Process Modeling and Analysis #FOS: Computer and information sciences #Scientific Computing and Data Management #Semantic Web and Ontologies #Software Engineering (cs.SE) #cs.SE
paper · pdf · doi:10.48550/arxiv.1402.5764
8 pages, 1 figure and 1 table. Accepted by the 9th Int Conf on the Evaluation of Novel Approaches to Software Engineering (ENASE'14). Lisbon, Portugal. April 2014
arxiv created 2014/02/24 · openalex publication_date 2014/02/24 · arxiv updated 2014/02/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In the age of the Cloud and so-called Big Data systems must be increasingly flexible, reconfigurable and adaptable to change in addition to being developed rapidly. As a consequence, designing systems to cater for evolution is becoming critical to their success. To be able to cope with change, systems must have the capability of reuse and the ability to adapt as and when necessary to changes in requirements. Allowing systems to be self-describing is one way to facilitate this. To address the issues of reuse in designing evolvable systems, this paper proposes a so-called description-driven approach to systems design. This approach enables new versions of data structures and processes to be created alongside the old, thereby providing a history of changes to the underlying data models and enabling the capture of provenance data. The efficacy of the description-driven approach is exemplified by the CRISTAL project. CRISTAL is based on description-driven design principles; it uses versions of stored descriptions to define various versions of data which can be stored in diverse forms. This paper discusses the need for capturing holistic system description when modelling large-scale distributed systems.