A Goal Modeling Framework for Self-contextualizable Software

Abstract. Self-contextualizability refers to the system ability to autonomously adapt its behaviour to context in order to maintain its objectives satisfied. In this paper, we propose a modeling framework to deal with self-contextualizability at the requirements level. We use Tropos goal models to express requirements; we provide constructs to analyse and represent context at each variation point of the goal model; and we exploit the goal and context analysis to define how the system satisfies its requirements in different contexts. Tropos goal analysis provides constructs to hierarchically analyse goals and discover alternative sets of tasks the system can execute to satisfy goals; our framework extends Tropos goal model by considering context at its variation points, and provides constructs to hierarchically analyse context and discover alternative sets of facts the system has to monitor to verify a context. A self-contextualizable promotion information system scenario is used to illustrate our approach. Key words: GORE, Context Analysis, Self-Contextualization

Optimizing monitoring requirements in self-adaptive systems

Monitoring the system environment is a key functionality of a self- adaptive system. Monitoring requirements denote the information a self-adaptive system has to capture at runtime to decide upon whether an adaptation action has to be taken. The identification of monitoring requirements is a complex task which can easily lead to redundancy and uselessness in the set of information to be monitored and this, consequently, means unjustified instalment of monitoring infrastructure and extra processing time. In this paper, we study the optimiza- tion of monitoring requirements. We discuss the case of contextual goal model, which is a requirements model that weaves between variability of goals (func- tional and non-functional requirements) and variability of context (monitoring requirements) and is meant to be used for modelling mobile and self-adaptive sys- tems requirements.We provide automated analysis —based on a SAT-solver—to process a contextual goal model and find a reduced set of contextual information monitor guaranteeing that this reduction does not sacrifice the system ability of taking correct adaptation decisions when fulfilling its requirements

Is compensation enough? Relational concerns in responding to unintended inequity

Traditional justice models suggest that monetary compensation is an adequate response to unintended distributive harm. This perspective is widely accepted in real world settings, and is manifested in policies ranging from worker compensation to the court-based tort system. Drawing on the arguments from relational models of authority, we hypothesize that compensation for losses may be viewed by victims as an inadequate response to the situation, even when those losses are accidental and not the result of intentional harm. In four experimental studies, respondents were asked to react to the receipt of monetary compensation for accidental distributive inequities under varying degrees of relational concern. Results indicate that judgments about the favorability of compensation are only one aspect of people's reaction to responses to harm. In each case, victims displayed more favorable reactions toward the group when compensation was supplemented by relational concern. © 2007 SAGE Publications

Volatile compounds in strawberry jam : influence of cooking on volatiles

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