Elicitation and utilization of application-level utility functions

deGrandis, Paul; Valetto, Giuseppe

doi:10.1145/1555228.1555259

Cited by 31 publications

(23 citation statements)

References 18 publications

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“…A requirements engineer must derive utility functions that can monitor the satisfaction of requirements in a DAS [8,17,22]. Each utility function comprises mathematical relationships that map monitoring data to a scalar value between zero and one.…”

Section: Assumptions Inputs and Outputsmentioning

confidence: 99%

Automatically RELAXing a Goal Model to Cope with Uncertainty

Ramirez

Fredericks

Jensen

et al. 2012

Lecture Notes in Computer Science

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Abstract. Dynamically adaptive systems (DAS) must cope with changing system and environmental conditions that may not have been fully understood or anticipated during development time. RELAX is a fuzzy logic-based specification language for making DAS requirements more tolerable to unanticipated environmental conditions. This paper presents AutoRELAX, an approach that generates RELAXed goal models that address environmental uncertainty by identifying which goals to RE-LAX, which RELAX operators to apply, and the shape of the fuzzy logic function that defines the goal satisfaction criteria. AutoRELAX searches for RELAXed goal models that enable a DAS to satisfy its functional requirements while balancing tradeoffs between minimizing the number of RELAXed goals and minimizing the number of adaptations triggered by minor and adverse environmental conditions. We apply AutoRELAX to an industry-provided network application that self-reconfigures in response to adverse environmental conditions, such as link failures.

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Section: Assumptions Inputs and Outputsmentioning

confidence: 99%

Automatically RELAXing a Goal Model to Cope with Uncertainty

Ramirez

Fredericks

Jensen

et al. 2012

Lecture Notes in Computer Science

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“…For instance, Garlan et al [3] applied utility functions to evaluate and select among different reconfiguration strategies depending on how each satisfied architectural and performance-based constraints. Even though utility functions provide numerous benefits for decision-making within a DAS, these are usually elicited either from domain experts or application users [9].…”

Section: Utility Functions For Self-adaptive Systemsmentioning

confidence: 99%

“…This monitoring information enables a DAS to detect both requirements violations, as well as conditions conducive to their occurrence [7,8,16]. Utility functions have been successfully applied for self-assessment purposes in DASs [3,9,15,17]. Within the context of a DAS, a utility function maps monitoring data to a scalar value, typically within the ranges of zero and one, that is proportional to how well the DAS satisfies its requirements at run time.…”

Section: Introductionmentioning

confidence: 99%

“…Utility functions provide a light-weight technique for associating the actions taken by a decision-making process with a DAS's high-level goals, concerns, and requirements [9,17]. As such, utility functions can be used to monitor both functional and non-functional requirements of a DAS.…”

Section: Introductionmentioning

confidence: 99%

“…Utility functions for monitoring the functional behavior of a DAS are often derived manually by requirements engineers with the aid of domain experts. In contrast, utility functions for monitoring the non-functional requirements (e.g., performance) of a DAS may be indirectly inferred at run time through statistical regression-based techniques [1,9]. These performance-based utility functions often generate a single, applicationlevel utility value representative of the overall system's performance.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Derivation of Utility Functions for Monitoring Software Requirements

Ramirez¹,

Cheng²

2011

Lecture Notes in Computer Science

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Abstract. Utility functions can be used to monitor requirements of a dynamically adaptive system (DAS). More specifically, a utility function maps monitoring information to a scalar value proportional to how well a requirement is satisfied. Utility functions may be manually elicited by requirements engineers, or indirectly inferred through statistical regression techniques. This paper presents a goal-based requirements modeldriven approach for automatically deriving state-, metric-, and fuzzy logic-based utility functions for RELAXed goal models. State-and fuzzy logic-based utility functions are responsible for detecting requirements violations, and metric-based utility functions are used to detect conditions conducive to a requirements violation. We demonstrate the proposed approach by applying it to the goal model of an intelligent vehicle system (IVS) and use the derived utility functions to monitor the IVS under different environmental conditions at run time.

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