Representing and reasoning about preferences in requirements engineering

Liaskos, Sotirios; McIlraith, Sheila A.; Sohrabi, Shirin; Mylopoulos, John

doi:10.1007/s00766-011-0129-9

Cited by 107 publications

(87 citation statements)

References 42 publications

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“…Goal models, instead, incorporate a large space of alternatives in one compact hierarchy. Moreover, quality measures, softgoals in goal models, are not a first-class requirement in problem frames and, thus, goal models offer the basis of representing the influence of contexts on these measures and prioritizing requirements alternatives accordingly [18,10,12]. Lapouchnian et al [30] share with us similar vision of integrating context with intentional variability captured by goal models.…”

Section: Related Workmentioning

confidence: 99%

“…Customizing goal models to fit to user skills and preferences was studied in [10,12]. Such work can be used at deployment time where specific user skills and preference will rule out some alternatives and, thus, the deployed system will not need to support them.…”

Section: Related Workmentioning

confidence: 99%

“…Hui et al [10] describe how requirements can be customized to fit the actual skills of users. Liaskos et al [11,12] discuss customizing the requirements to users' preferences expressed over non-functional and optional requirements. Baresi et al [13] propose adaptation requirements, called adaptation goals, to customize a system at runtime and maintain a correct execution course.…”

Section: Introductionmentioning

confidence: 99%

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Requirements-driven deployment

2012

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Deployment is a main development phase which configures a software to be ready for use in a certain environment. The ultimate goal of deployment is to enable users to achieve their requirements while using the deployed software. However, requirements are not uniform and differ between deployment environments. In one environment, certain requirements could be useless or redundant, thereby making some software functionalities superfluous. In another environment, instead, some requirements could be impossible to achieve and, thus, additional functionalities would be required. We advocate that ensuring fitness between requirements and the system environment is a basic and critical step to achieve a comprehensive deployment process. We propose a tool-supported modelling and analysis approach to tailor a requirements model to each environment in which the system is to be deployed. We study the case of contextual goal model, which is a requirements model that captures the relationship between the variability of requirements (goal variability space) and the varying states of a deployment environment (context variability space). Our analysis relies on sampling a deployment environment to discover its context variability space and use it to identify loci in the contextual goal model where a modification has to take place. Finally, we apply our approach in practice and report on the obtained results.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Requirements-driven deployment

2012

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“…user preferences [19]. In our approach, the variability of MobIS is based on the different locations the system can adapt to, and the set of behaviors it can choose among.…”

Section: Location In Troposmentioning

confidence: 99%

“…Preferences can be specified using contributions to soft-goals as in [19]. We need this analysis in two cases:…”

Section: Preferences Analysis (Pa)mentioning

confidence: 99%

Modeling and Analyzing Variability for Mobile Information Systems

Ali

Dalpiaz

Giorgini

Computational Science and Its Applications – ICCSA 2008

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Abstract. Advances in size, power, and ubiquity of computing, sensors, and communication technology made possible the development of mobile or nomadic information systems. Variability of location and system behavior is a central issue in mobile information systems, where behavior of software has to change and re-adapt to the different location settings. This paper concerns modeling and analysis of the complementary relation between software and location variability. We use graphical and formal location modeling techniques, show how to elicit and use location model in conjunction with Tropos goal-oriented framework, and introduce automated analysis on the location-based models.

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Fifty Shades of Green: How Informative is a Compliant Process Trace?

Burattin¹,

Guizzardi

Maggi

et al. 2019

Advanced Information Systems Engineering

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The problem of understanding whether a process trace satisfies a prescriptive model is a fundamental conceptual modeling problem in the context of process-based information systems. In business process management, and in process mining in particular, this amounts to check whether an event log conforms to a prescriptive process model, i.e., whether the actual traces present in the log are allowed by all behaviors implicitly expressed by the model. The research community has developed a plethora of very sophisticated conformance checking techniques that are particularly effective in the detection of non-conforming traces, and in elaborating on where and how they deviate from the prescribed behaviors. However, they do not provide any insight to distinguish between conforming traces, and understand their differences. In this paper, we delve into this rather unexplored area, and present a new process mining quality measure, called informativeness, which can be used to compare conforming traces to understand which are more relevant (or informative) than others. We introduce a technique to compute such measure in a very general way, as it can be applied on process models expressed in any language (e.g., Petri nets, Declare, process trees, BPMN) as long as a conformance checking tool is available. We then show the versatility of our approach, showing how it can be meaningfully applied when the activities contained in the process are associated to costs/rewards, or linked to strategic goals.

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Representing and reasoning about preferences in requirements engineering

Cited by 107 publications

References 42 publications

Requirements-driven deployment

Requirements-driven deployment

Modeling and Analyzing Variability for Mobile Information Systems

Fifty Shades of Green: How Informative is a Compliant Process Trace?

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