Autonomic computing systems reduce software maintenance costs and management complexity by taking on the responsibility for their configuration, optimization, healing, and protection. These tasks are accomplished by switching at runtime to a different system behaviour – the one that is more efficient, more secure, more stable, etc. – while still fulfilling the main purpose of the system. Thus, identifying and analyzing alternative ways of how the main objectives of the system can be achieved and designing a system that supports all of these alternative behaviours is a promising way to develop autonomic systems. This paper proposes the use of requirements goal models as a foundation for such software development process and sketches a possible architecture for autonomic systems that can be built using the this approach.

Several surveys indicate that a significant percentage of data warehouses fail to meet business objectives or are outright failures. One of the reasons for this is that requirement analysis is typically overlooked in real projects. In this paper we propose a goal-oriented approach to requirement analysis for data warehouses, based on the Tropos methodology. Two different perspectives are integrated for requirement analysis: organizational modeling, centered on stakeholders, and decisional modeling, focused on decision makers. Our approach can be employed within both a demand-driven and a mixed supply/demand-driven design framework: in the second case, while the operational sources are still explored to shape hierarchies, user requirements play a fundamental role in restricting the area of interest for analysis and in choosing facts, dimensions, and measures. The methodology proposed, supported by a prototype, is described with reference to a real case study. 1

Abstract. Tropos is an agent-oriented software methodology proposed in [1, 2]. The methodology is founded on the notions of agent and goal, and goal analysis is used extensively to support software development during different phases. This paper adopts a formal goal model defined and analyzed in [9, 15] to make the goal analysis process concrete through the use of forward and backward reasoning for goal models. The formal goal analysis is illustrated through examples, using an implemented goal reasoning tool.

We investigate the personalization capabilities of common personal software systems. We use a typical e-mail client as an example of such a system, and examine the configuration screens it offers to its users. We discover that each configuration value reflects each of the ways with which the user goals can be satisfied. Thus, we construct a goal model in which alternative ways for satisfying high level goals are matched with alternative system configurations. This way, automatic configuration of the system by reasoning about the overlaying goal model can be achieved. We find that the vast majority of the configuration options that refer to system functionality can be configured using this method, facilitating thereby the personalization tasks for users with no technical background, and ensuring, at the same time, consistency and meaningfulness in the configuration result. 1.

Given a Boolean satisfiability (Sat) problem whose variables have non-negative weights, the minimum-cost satisfiability (MinCostSat) problem finds a satisfying truth assignment that minimizes a weighted sum of the truth values of the variables. Many NP-optimization problems are either special cases of MinCostSat or can be transformed into MinCostSat efficiently. However, in the past, these problems have been largely considered in isolation. In this dissertation, we (1) classify existing Min-CostSat problems, (2) study factors affecting the performance of MinCostSat solvers, (3) propose algorithms for MinCostSat problems, and (4) implement and validate the performance of state-of-the-art solvers for special cases of MinCostSat, including set and binate covering, Max-Sat, and group-partial Max-Sat. We categorize MinCostSat problems as either native or non-native. Non-native problems can only be transformed into MinCostSat by adding slack variables. These problems include the Max-Sat, partial Max-Sat, and group-partial Max-Sat problems which have applications ranging from course assignment to FPGA detailed routing. Native problems are various sub-cases of MinCostSat. We further divide these into two

Abstract. Modelling and analysing risk is one of the most critical activity in system engineering. However, in literature approaches like Fault Tree Analysis, Event Tree Analysis, Failure Modes and Criticality Analysis focus on the system-to-be without considering the impact of the associated risks to the organization where the system will operate. The Tropos framework has been proved effective in modelling strategic interests of the stakeholders at organizational level. In this paper, we introduce the extended Tropos goal model to analyse risk at organization level and we illustrate a number of different techniques to help the analyst in identifying and enumerating relevant countermeasures for risk mitigation.

The shift in software engineering from the design, implementation and management of isolated software elements towards a network of autonomous interoperable service is calling for a shift in the way software is designed. We propose the use of the agent-oriented methodology Tropos for the analysis of web service requirements. We shown how the Tropos methodology adapts to the case of web services and in particular how it can be used to model quality of service requirements. We base the investigation on a representative case study in the retailing industry.

Monitoring the satisfaction of software requirements and diagnosing what went wrong in case of failure is a hard problem that has received little attention in the Software and Requirement Engineering literature. To address this problem, we propose a framework adapted from artificial intelligence theories of action and diagnosis. Specifically, the framework monitors the satisfaction of software requirements and generates log data at a level of granularity that can be tuned adaptively at runtime depending on monitored feedback. When errors are found, the framework diagnoses the denial of the requirements and identifies problematic components. To support diagnostic reasoning, we transform the diagnostic problem into a propositional satisfiability (SAT) problem that can be solved by existing SAT solvers. We preprocess log data into a compact propositional encoding that better scales with problem size. The proposed theoretical framework has been implemented as a diagnosing component that will return sound and complete diagnoses accounting for observed aberrant system behaviors. Our solution is illustrated with two medium-sized publicly available case studies: a Web-based email client and an ATM simulation. Our experimental results demonstrate the feasibility of scaling our approach to medium-size software systems.

Abstract. Software requirements consist of functionalities and qualities to be accommodated during design. Through goal-oriented requirements engineering, stakeholder goals are refined into a space of alternative functionalities. We adopt this framework and propose a decision-making process to generate a generic software design that can accommodate the full space of alternatives each of which can fulfill stakeholder goals. Specifically, we present a process for generating complementary design views from a goal model with high variability in configurations, behavioral specifications, architectures and business processes. 1

The protection of customer privacy is a fundamental issue in today's corporate marketing strategies. Not surprisingly, many research efforts have proposed new privacy-aware technologies. Among them, Hippocratic databases offer mechanisms for enforcing privacy rules in database systems for inter-organizational business processes (also known as virtual organizations). This paper extends these mechanisms to allow for hierarchical purposes, distributed authorizations and minimal disclosure supporting the business processes of virtual organizations that want to offer their clients a number of ways to fulfill a service. Specifically, we use a goal-oriented approach to analyze privacy policies of the enterprises involved in a business process. Based on the purpose hierarchy derived through a goal refinement process, we provide algorithms for determining the minimum set of authorizations needed to achieve a service. This allows us to automatically derive access control policies for an inter-organizational business process from the collection of privacy policies associated with different participating enterprises. By using effective on-line algorithms, the derivation of such minimal information can also be done on-the-fly by the customer wishing to access a service.