Expressing and enforcing user-defined constraints of AADL models

The Architecture Analysis and Design Language AADL allows one to model complete systems, but also to define specific extensions through property sets and library of models. Yet, it does not define an explicit mechanism to enforce some semantics or consistency checks to ensure property sets are correctly used. In this paper, we present REAL (Requirements and Enforcements Analysis Language) as an integrated solution to this issue. REAL is defined as an AADL annex language. It adds the possibility to express constraints as theorems based on set theory to enforce implicit semantics of property sets or AADL models. We illustrate the use of the language on case studies we developed with industrial partners

Actor perception in business use case modeling

Mainstream literature recognizes the validity and effectiveness of use cases as a technique for gathering and capturing system requirements. Use cases represent the driver of various modern development methods, mainly of object-oriented extraction, such as the Unified Process. Although the adoption of use cases proliferated in the context of software systems development, they are not as extensively employed in business modeling . The concept of business use case is not a novelty, but only recently did it begin to re-circulate in the literature and in case tools. This paper examines the issues involved in adopting business use cases for capturing the functionality of an organization and proposes guidelines for their identification, packaging, and mapping to system use cases. The proposed guidelines are based on the principle of actor perception described in the paper. The application of this principle is exemplified with a worked example aimed at demonstrating the utility of the proposed guidelines and at clarifying the application of the principle of actor perception. The worked example is based on a series of workshops run at a major UK financial institution

A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-Based, Simulations, Methodology, Calibration, Validation, Sensitivity Analysis

A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-based, simulations, methodology, calibration, validation.