A Pattern-Based Architectural Style for Self-Organizing Software Systems

2014 ◽  
pp. 163-186
2008 ◽  
Vol 50 (2) ◽  
Author(s):  
Gero Decker ◽  
Oliver Kopp ◽  
Alistair Barros

SummaryService oriented architecture (SOA) is an architectural style for building software systems based on services. Especially in those scenarios where services implement business processes, complex conversations between the services occur. Service choreographies are a means to capture all interaction obligations and constraints from a global perspective. This article introduces choreographies as an important artifact for SOA, compares them to service orchestrations and surveys existing languages for modeling them.


2021 ◽  
Vol 24 (5) ◽  
pp. 808-869
Author(s):  
Феликс Освальдович Каспаринский

Modern software and hardware tools provide unprecedented freedom for a variety of activities in the forex markets, from trading to analyzing the feasibility of models of nonlinear processes in self-organizing systems. To reduce risks and increase the efficiency of interaction with stock market instruments, it is proposed to provide variable adaptability of trading by combining trading strategies using several trading accounts of different brokers, multiple financial instruments, and Complex Indicators Tendencies of price changes. As a result of three years of experimental work, the basic principles of multitrading have been formulated and tested, and an information environment has been compiled, contributing to the development of an individualized trading system. The basic concept of organizing a multitrading information environment: the use of specialized hardware and software systems for strategic analysis and forecasting of price changes for an individual financial instrument, tactical selection of a promising financial instrument from the available set, and effective operating activities with orders of trading accounts. It can be expected that the evolution of the principles of multitrading will lead to the creation of analytical systems for predicting the kinetics of non-equilibrium changes in the characteristic parameters of self-organizing cooperative systems for wide application in biology, cybernetics, economics, and the social sphere.


Author(s):  
Jan Sudeikat ◽  
Wolfgang Renz

Agent Oriented Software-Engineering (AOSE) proposes the design of distributed software systems as collections of autonomous and pro-active actors, so-called agents. Since software applications results from agent interplay in Multi-Agent Systems (MAS), this design approach facilitates the construction of software applications that exhibit self-organizing and emergent dynamics. In this chapter, we examine the relation between self-organizing MAS and Complex Adaptive Systems (CAS), highlighting the resulting challenges for engineering approaches. We argue that AOSE developers need to be aware of the possible causes of complex system dynamics, which result from underlying feedback loops. In this respect current approaches to develop SO-MAS are analyzed, leading to a novel classification scheme of typically applied computational techniques. To relieve development efforts and bridge the gap between top-down engineering and bottom-up emerging phenomena, we discuss how multi-level analysis, so-called mesoscopic modeling, can be used to comprehend MAS dynamics and guide agent design, respectively iterative redesign.


2015 ◽  
Vol 30 (4) ◽  
pp. 419-434 ◽  
Author(s):  
H. Van Dyke Parunak ◽  
Sven A. Brueckner

AbstractSelf-organizing software systems are an increasingly attractive approach to highly distributed, decentralized, dynamic applications. In some domains (such as the Internet), the interaction of originally independent systems yields a self-organizing systemde facto, and engineers must take these characteristics into account to manage them. This review surveys current work in this field and outlines its main themes, identifies challenges for future research, and addresses the continuity between software engineering in general and techniques appropriate for self-organizing systems.


2011 ◽  
pp. 767-787 ◽  
Author(s):  
Jan Sudeikat ◽  
Wolfgang Renz

Agent Oriented Software-Engineering (AOSE) proposes the design of distributed software systems as collections of autonomous and pro-active actors, so-called agents. Since software applications results from agent interplay in Multi-Agent Systems (MAS), this design approach facilitates the construction of software applications that exhibit self-organizing and emergent dynamics. In this chapter, we examine the relation between self-organizing MAS and Complex Adaptive Systems (CAS), highlighting the resulting challenges for engineering approaches. We argue that AOSE developers need to be aware of the possible causes of complex system dynamics, which result from underlying feedback loops. In this respect current approaches to develop SO-MAS are analyzed, leading to a novel classification scheme of typically applied computational techniques. To relieve development efforts and bridge the gap between top-down engineering and bottom-up emerging phenomena, we discuss how multi-level analysis, so-called mesoscopic modeling, can be used to comprehend MAS dynamics and guide agent design, respectively iterative redesign.


2021 ◽  
Vol 66 (1) ◽  
pp. 54
Author(s):  
E.-M. Manole

Self Organizing Maps (SOM) are unsupervised neural networks suited for visualisation purposes and clustering analysis. This study uses SOM to solve a software engineering problem: detecting the most important (key) classes from software projects. Key classes are meant to link the most valuable concepts of a software system and in general these are found in the solution documentation. UML models created in the design phase become deprecated in time and tend to be a source of confusion for large legacy software. Therefore, developers try to reconstruct class diagrams from the source code using reverse engineering. However, the resulting diagram is often very cluttered and difficult to understand. There is an interest for automatic tools for building concise class diagrams, but the machine learning possibilities are not fully explored at the moment. This paper proposes two possible algorithms to transform SOM in a classification algorithm to solve this task, which involves separating the important classes - that should be on the diagrams - from the others, less important ones. Moreover, SOM is a reliable visualization tool which able to provide an insight about the structure of the analysed projects.


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