DAIDA: an environment for evolving information systems
ACM Transactions on Information Systems (TOIS)
Representing and using nonfunctional requirements: a process-oriented approach
IEEE Transactions on Software Engineering - Special issue on knowledge representation and reasoning in software development
Dealing with non-functional requirements: three experimental studies of a process-oriented approach
Proceedings of the 17th international conference on Software engineering
Managing performance requirements for information systems
Proceedings of the 1st international workshop on Software and performance
Management of Performance Requirements for Information Systems
IEEE Transactions on Software Engineering
Representing and Using Nonfunctional Requirements: A Process-Oriented Approach
IEEE Transactions on Software Engineering - Special issue on knowledge representation and reasoning in software development
| Hi-index | 0.00 |
Suppose you are given a conceptual design specification for an information system, written in an entity-based specification language which supports features including entity classes, declaratively-defined transactions, and generalisation hierarchies. You are also given some performance requirements, such as “minimise the time to reimburse a researcher” or “minimise storage space for information on meetings.” Your task is to generate an implementation (relational database and application programmes) which is consistent with the design specification and meets the performance requirements. We consider the development of a framework to accomplish this task by “mapping” information system design specifications into implementations. Two issues are addressed. Performance prediction: Given a design specification, a particular implementation of it, and expected usage statistics (e.g., class cardinalities), obtain estimates of performance measures. Selection among implementation alternatives: Given a specification, statistics, and some performance goals, select an efficient implementation (from sets of pre-defined alternatives) by a process of goal decomposition. To structure prediction and selection, we use a multi-layered approach, based on subsets of data model and language features.