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Title: Run-time monitoring of goal-oriented requirements specification
Author: Dingwall-Smith, Andrew Ross
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 2006
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The environment in which a software system operates is as important to the correct operation of the system as the software itself. Most software development involves making assumptions about the environment in which the resulting system will operate. These assumptions may cease to be valid if the environment changes, causing the system to fail to operate correctly. One solution to this problem is to use run-time requirements monitoring to deter mine, as a system operates, whether it is satisfying the requirements specified for it and to take action to rectify these problems. This thesis describes work that has been carried out in the area of run-time requirements monitoring. A framework has been developed for monitoring requirements which are formally specified using temporal logic and the KAOS goal-oriented requirements specification language. The framework uses AspecU to instrument the monitored system so that events are emitted which are used to determine whether the monitored system satisfies the requirements specification. The framework also provides a language which can specify a mapping between requirements and implementation which can be used to generate instrumentation code. The monitoring framework supports monitoring of soft goals by allowing the formal specification of metrics which can be used to determine whether soft goals are in fact being satisfied. These contributions are validated using a workforce scheduling system as a case study. This is a real world system and the requirements monitored were those considered useful by the developers of the system. The case study shows that the monitoring framework can be used to instrument a system to monitor hard and soft goals and that those goals can be monitored with reasonable performance overhead. Goal failures due to changes in the environment can be detected using the information supplied by the monitoring framework.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available