ArchOptions: A Real Options-Based Model for Predicting the Stability of Software Architectures

Architectural stability refers to the extent an architecture is flexible to endure evolutionary changes in stakeholders\' requirements and the environment. We assume that the primary goal of software architecture is to guide the system\'s evolution. We contribute to a novel model that exploits options theory to predict architectural stability. The model is predictive: it provides \"insights\" on the evolution of the software system based on valuing the extent an architecture can endure a set of likely evolutionary changes. The model builds on Black and Scholes financial options theory (Noble Prize wining) to value such extent. We show how we have derived the model: the analogy and assumptions made to reach the model, its formulation, and possible interpretations. We refer to this model as ArchOptions

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

ECONOMIC AGENCY THROUGH MODULARITY THEORY

Economic agency as a matter of rational decision-making and as a problem of bounded rationality has never gone too far from its earlier formalization in the 1950s. Not that the advancement on this topic is so slow, but the same problem concerning higher level cognition as another general program of cognitive science is not as easy as behavioral studies. This paper will show a parallelism between economic agency and folkpsychological perspective, and in turn will give a short description on how folk psychology is unseparable from modularity theory. In short, then there must be a way to cope with cognition as the black box of economics if we can identify the appropriate level of description of cognitive structure, i.e.: modularity theory.bounded rationality, folk psychology, modularity theory

Using real options to select stable Middleware-induced software architectures

The requirements that force decisions towards building distributed system architectures are usually of a non-functional nature. Scalability, openness, heterogeneity, and fault-tolerance are examples of such non-functional requirements. The current trend is to build distributed systems with middleware, which provide the application developer with primitives for managing the complexity of distribution, system resources, and for realising many of the non-functional requirements. As non-functional requirements evolve, the `coupling' between the middleware and architecture becomes the focal point for understanding the stability of the distributed software system architecture in the face of change. It is hypothesised that the choice of a stable distributed software architecture depends on the choice of the underlying middleware and its flexibility in responding to future changes in non-functional requirements. Drawing on a case study that adequately represents a medium-size component-based distributed architecture, it is reported how a likely future change in scalability could impact the architectural structure of two versions, each induced with a distinct middleware: one with CORBA and the other with J2EE. An option-based model is derived to value the flexibility of the induced-architectures and to guide the selection. The hypothesis is verified to be true for the given change. The paper concludes with some observations that could stimulate future research in the area of relating requirements to software architectures

Mass customization of teaching and learning in organizations

In search of methods that improve the efficiency of teaching and training in organizations, several authors point out that mass customization (MC) is a principle that covers individual needs of knowledge and skills and, at the same time, limits the development costs of customized training to those of mass training. MC is proven and established in the economic sector, and shows high potential for continuing education, too. The paper explores this potential and proposes a multidisciplinary, pragmatic approach to teaching and training in organizations. The first section of the paper formulates four design principles of MC deduced from an examination of economics literature. The second section presents amit™, a frame for mass customized training, designed according to the principles presented in the first section. The evaluation results encourage the further development and use of mass customized training in continuing education, and offer suggestions for future research

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF