Learning to adapt requirements specifications of evolving systems (NIER track).

Saved in:
Bibliographic Details
Title: Learning to adapt requirements specifications of evolving systems (NIER track).
Authors: Borges, Rafael V., D'Avila Garcez, Artur, Lamb, Luis C., Nuseibeh, Bashar
Source: ICSE: International Conference on Software Engineering. 2011, p856-859. 4p.
Subjects: Requirements engineering, Software reengineering, Computer simulation, Machine learning, Software engineering
Abstract: We propose a novel framework for adapting and evolving software requirements models. The framework uses model checking and machine learning techniques for verifying properties and evolving model descriptions. The paper offers two novel contributions and a preliminary evaluation and application of the ideas presented. First, the framework is capable of coping with errors in the specification process so that performance degrades gracefully. Second, the framework can also be used to re-engineer a model from examples only, when an initial model is not available. We provide a preliminary evaluation of our framework by applying it to a Pump System case study, and integrate our prototype tool with the NuSMV model checker. We show how the tool integrates verification and evolution of abstract models, and also how it is capable of re-engineering partial models given examples from an existing system. [ABSTRACT FROM AUTHOR]
Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
Description
Abstract:We propose a novel framework for adapting and evolving software requirements models. The framework uses model checking and machine learning techniques for verifying properties and evolving model descriptions. The paper offers two novel contributions and a preliminary evaluation and application of the ideas presented. First, the framework is capable of coping with errors in the specification process so that performance degrades gracefully. Second, the framework can also be used to re-engineer a model from examples only, when an initial model is not available. We provide a preliminary evaluation of our framework by applying it to a Pump System case study, and integrate our prototype tool with the NuSMV model checker. We show how the tool integrates verification and evolution of abstract models, and also how it is capable of re-engineering partial models given examples from an existing system. [ABSTRACT FROM AUTHOR]
DOI:10.1145/1985793.1985924