Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach

Goals are first-class entities in a self-adaptive system (SAS) as they guide the self-adaptation. A SAS often operates in dynamic and partially unknown environments, which cause uncertainty that the SAS has to address to achieve its goals. Moreover, besides the environment, other classes of uncertainty have been identified. However, these various classes and their sources are not systematically addressed by current approaches throughout the life cycle of the SAS. In general, uncertainty typically makes the assurance provision of SAS goals exclusively at design time not viable. This calls for an assurance process that spans the whole life cycle of the SAS. In this work, we propose a goal-oriented assurance process that supports taming different sources (within different classes) of uncertainty from defining the goals at design time to performing self-adaptation at runtime. Based on a goal model augmented with uncertainty annotations, we automatically generate parametric symbolic formulae with parameterized uncertainties at design time using symbolic model checking. These formulae and the goal model guide the synthesis of adaptation policies by engineers. At runtime, the generated formulae are evaluated to resolve the uncertainty and to steer the self-adaptation using the policies. In this paper, we focus on reliability and cost properties, for which we evaluate our approach on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the validation are promising and show that our approach is able to systematically tame multiple classes of uncertainty, and that it is effective and efficient in providing assurances for the goals of self-adaptive systems

Managing the trade-off implications of global supply

The cost versus response trade-off is a growing logistics issue due to many markets being increasingly characterized by demand uncertainty and shorter product life cycles. This is exacerbated further with supply increasingly moving to low cost global sources. However, the poor response implications of global supply are often not addressed or even acknowledged when undertaking such decisions. Consequently, various practical approaches to minimising, postponing or otherwise managing the impact of the demand uncertainty are often only adopted retrospectively. Even though such generic solutions are documented through case examples we lack effective tools and concepts to support the proactive identification and resolution of such trade-offs. This paper reports on case-based theory building research, involving three cases from the UK and USA used in developing a conceptual model with associated tools, in support of such a process

Principles for aerospace manufacturing engineering in integrated new product introduction

This article investigates the value-adding practices of Manufacturing Engineering for integrated New Product Introduction. A model representing how current practices align to support lean integration in Manufacturing Engineering has been defined. The results are used to identify a novel set of guiding principles for integrated Manufacturing Engineering. These are as follows: (1) use a data-driven process, (2) build from core capabilities, (3) develop the standard, (4) deliver through responsive processes and (5) align cross-functional and customer requirements. The investigation used a mixed-method approach. This comprises case studies to identify current practice and a survey to understand implementation in a sample of component development projects within a major aerospace manufacturer. The research contribution is an illustration of aerospace Manufacturing Engineering practices for New Product Introduction. The conclusions will be used to indicate new priorities for New Product Introduction and the cross-functional interactions to support flawless and innovative New Product Introduction. The final principles have been validated through a series of consultations with experts in the sponsoring company to ensure that correct and relevant content has been defined

Expressing Measurement Uncertainty in OCL/UML Datatypes

Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, di cult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations de ned for the values of these types.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Traceability for Model Driven, Software Product Line Engineering

Traceability is an important challenge for software organizations. This is true for traditional software development and even more so in new approaches that introduce more variety of artefacts such as Model Driven development or Software Product Lines. In this paper we look at some aspect of the interaction of Traceability, Model Driven development and Software Product Line

A metric to represent the evolution of CAD/analysis models in collaborative design

Computer Aided Design (CAD) and Computer Aided Engineering (CAE) models are often used during product design. Various interactions between the different models must be managed for the designed system to be robust and in accordance with initially defined specifications. Research published to date has for example considered the link between digital mock-up and analysis models. However design/analysis integration must take into consideration the important number of models (digital mock-up and simulation) due to model evolution in time, as well as considering system engineering. To effectively manage modifications made to the system, the dependencies between the different models must be known and the nature of the modification must be characterised to estimate the impact of the modification throughout the dependent models. We propose a technique to describe the nature of a modification which may be used to determine the consequence within other models as well as a way to qualify the modified information. To achieve this, a metric is proposed that allows the qualification and evaluation of data or information, based on the maturity and validity of information and model

Contingent Information Systems Development

Situated approaches based on project contingencies are becoming more and more an important research topic for information systems development organizations. The Information Services Organization, which was investigated, has recognized that it should tune its systems development approaches to the specific situation. A model has been developed, dealing with the matching between prevailing contingency factors and the preconditions of already existing situated approaches. Furthermore, a generic process model for systems development, including the information systems operations stage, is proposed. This model makes it possible to derive from it specific systems development strategies. A number of basic development strategies, specific for the Information Services Organization, are described. Preconditions, specific for this organization, are added to the standard situated approaches

Decision support for firm performance by real options analytics

This paper develops a real options decision support tool for raising the performance of the firm. It shows how entrepreneurs can use our intuitive tool quickly to assess the nature and type of action required for improved performance. This exploits our estimated econometric relationship between precipitators of entrepreneurial opportunities, time until exercise, and firm performance. Our 3D chromaticity plots show how staging investments, investment time, and firm performance support entrepreneurial decisions to embed, or to expedite, investments. Speedy entrepreneurial action is securely supported with this tool, without expertise in econometric estimation or in formulae for real options valuation