Many quality aspects of software systems are addressed in the existing literature on software architecture patterns. But the aspect of system administration seems to be a bit overlooked, even though it is an important aspect too. In this work we present three software architecture patterns that, when applied by software architects, support the work of system administrators: PROVIDE AN ADMINISTRATION API, SINGLE FILE LOCATION, and CENTRALIZED SYSTEM LOGGING. PROVIDE AN ADMINISTRATION API should solve problems encountered when trying to automate administration tasks. The SINGLE FILE LOCATION pattern should help system administrators to find the files of an application in one (hierarchical) place. CENTRALIZED SYSTEM LOGGING is useful to prevent coming up with several logging formats and locations. Abstract provided by the authors. Published in PLoP '13: Proceedings of the 20th Conference on Pattern Languages of Programs ACM.
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"The booklet presents curated real-world good practice examples that help translate our strategy into concrete actions, and in turn, into the design of education and training programmes that will contribute to skill, upskill, or reskill individuals into high demand professional software roles."
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Author supplied: "Abstract Software Architecture Compliance Checking (SACC) is an approach to verify conformance of implemented program code to high-level models of architectural design. Static SACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient SACC. This document describes a test approach that may be used to determine how accurate a tested SACCT-tool is with respect to dependency analysis and violation reporting. This technical report is intended as a test manual and describes how a SACCT-tool can be tested. Two separate tests are described: the Benchmark test, and the FreeMind test."
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Software reference architectures have been around for quite some years. They have been designed and used with varying success. We have conducted an exploratory survey among software architects and developers to establish the extent to which SRA have penetrated among practitioners and to identify the benefits and problems practitioners face when using and designing SRA. In this article, we present our findings.
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Presentatie voor de 20e Nederlandse Testdag, m.m.v. Raymond Slot, Wiebe Wiersema, (HU), Christian Köppe (HAN, Arnhem), Sjaak Brinkkemper, Jan Martijn van der Werf (UU Utrecht). The Software Architecture of the Schiphol Group is taken as an example. Compliance checking of software rulescan be done with the Hogeschool Utrecht Software Architecture Compliance Checking Tool which is available at http://husacct.github.io/HUSACCT/
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Both Software Engineering and Machine Learning have become recognized disciplines. In this article I analyse the combination of the two: engineering of machine learning applications. I believe the systematic way of working for machine learning applications is at certain points different from traditional (rule-based) software engineering. The question I set out to investigate is “How does software engineering change when we develop machine learning applications”?. This question is not an easy to answer and turns out to be a rather new, with few publications. This article collects what I have found until now.
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The Circular Wood 4.0 Workflow API is a comprehensive and automated “file-to-factory” system that bridges the gap between design using waste wood resources and production processes aligned with Smart Industry principles. This software serves as the core IT infrastructure for an end-to-end automated workflow, enabling seamless data flow from material availability to final production. Key features include full traceability, real-time process monitoring, and integration of design and manufacturing stages. The API is composed of several interconnected components that manage the entire workflow, from intelligent resource matching and design generation to production preparation and execution; facilitating efficient, sustainable, and transparent fabrication processes.
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Author supplied: Teaching software architecture (SA) in a bachelor computer science curriculum can be challenging, as the concepts are on a high abstraction level and not easy to grasp for students. Good techniques and tools that help with addressing the challenging SA aspects in a didactically responsible way are needed. In this tool demo we show how we used the software architecture compliance checking tool HUSACCT for addressing various concepts of SA in our courses on software architecture. The students were introduced to architectural reconstruction and architecture compliance checking, which helped them to gain important insights in aspects such as the relation between architectural models and code and the specification of dependency relations between architecture elements as concrete rules.
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This papers presents some ideas to use so-called software agents as a software representation of a product not only during manufacturing but also during the whole life cycle of the product. Software agents are autonomous entities capable of collecting useful information about products. By their design and capabilities software agents fit well in the concept of ubiquitous computing. We use these agents in our newly developed manufacturing process. This paper discusses further use of agent technology.
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Context:Rapid developments and adoption of machine learning-based software solutions have enabled novel ways to tackle our societal problems. The ongoing digital transformation has led to the incorporation of these software solutions in just about every application domain. Software architecture for machine learning applications used during sustainable digital transformation can potentially aid the evolution of the underlying software system adding to its sustainability over time.Objective:Software architecture for machine learning applications in general is an open research area. When applying it to sustainable digital transformation it is not clear which of its considerations actually apply in this context. We therefore aim to understand how the topics of sustainable digital transformation, software architecture, and machine learning interact with each other.Methods:We perform a systematic mapping study to explore the scientific literature on the intersection of sustainable digital transformation, machine learning and software architecture.Results:We have found that the intersection of interest is small despite the amount of works on its individual aspects, and not all dimensions of sustainability are represented equally. We also found that application domains are diverse and include many important sectors and industry groups. At the same time, the perceived level of maturity of machine learning adoption by existing works seems to be quite low.Conclusion:Our findings show an opportunity for further software architecture research to aid sustainable digital transformation, especially by building on the emerging practice of machine learning operations.
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