1,928,019 research outputs found

    How software engineering research aligns with design science: A review

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    Background: Assessing and communicating software engineering research can be challenging. Design science is recognized as an appropriate research paradigm for applied research but is seldom referred to in software engineering. Applying the design science lens to software engineering research may improve the assessment and communication of research contributions. Aim: The aim of this study is 1) to understand whether the design science lens helps summarize and assess software engineering research contributions, and 2) to characterize different types of design science contributions in the software engineering literature. Method: In previous research, we developed a visual abstract template, summarizing the core constructs of the design science paradigm. In this study, we use this template in a review of a set of 38 top software engineering publications to extract and analyze their design science contributions. Results: We identified five clusters of papers, classifying them according to their alignment with the design science paradigm. Conclusions: The design science lens helps emphasize the theoretical contribution of research output---in terms of technological rules---and reflect on the practical relevance, novelty, and rigor of the rules proposed by the research.Comment: 32 pages, 10 figure

    Modeling functional requirements using tacit knowledge: a design science research methodology informed approach

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    The research in this paper adds to the discussion linked to the challenge of capturing and modeling tacit knowledge throughout software development projects. The issue emerged when modeling functional requirements during a project for a client. However, using the design science research methodology at a particular point in the project helped to create an artifact, a functional requirements modeling technique, that resolved the issue with tacit knowledge. Accordingly, this paper includes research based upon the stages of the design science research methodology to design and test the artifact in an observable situation, empirically grounding the research undertaken. An integral component of the design science research methodology, the knowledge base, assimilated structuration and semiotic theories so that other researchers can test the validity of the artifact created. First, structuration theory helped to identify how tacit knowledge is communicated and can be understood when modeling functional requirements for new software. Second, structuration theory prescribed the application of semiotics which facilitated the development of the artifact. Additionally, following the stages of the design science research methodology and associated tasks allows the research to be reproduced in other software development contexts. As a positive outcome, using the functional requirements modeling technique created, specifically for obtaining tacit knowledge on the software development project, indicates that using such knowledge increases the likelihood of deploying software successfully

    Cause for alarm?: A multi-national, multi-institutional study of student-generated software designs

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    This paper reports a multi-national, multi-institutional study to investigate Computer Science students' understanding of software design and software design criteria. Students were recruited at two levels: those termed 'first competency' programmers, and those completing their Bachelor degrees. The study, including participants from 21 institutions over the academic year 2003/4, aimed to examine students' ability to generate software designs, to elicit students' understanding and valuation of key design activities, and to examine whether students at different stages in their undergraduate education display different understanding of software design. Differences were found in participants' recognition of ambiguity in requirements; in their use of formal (and semi-formal) design representation and in their prioritisation of design criteria

    Study of application of space telescope science operations software for SIRTF use

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    The design and development of the Space Telescope Science Operations Ground System (ST SOGS) was evaluated to compile a history of lessons learned that would benefit NASA's Space Infrared Telescope Facility (SIRTF). Forty-nine specific recommendations resulted and were categorized as follows: (1) requirements: a discussion of the content, timeliness and proper allocation of the system and segment requirements and the resulting impact on SOGS development; (2) science instruments: a consideration of the impact of the Science Instrument design and data streams on SOGS software; and (3) contract phasing: an analysis of the impact of beginning the various ST program segments at different times. Approximately half of the software design and source code might be useable for SIRTF. Transportability of this software requires, at minimum, a compatible DEC VAX-based architecture and VMS operating system, system support software similar to that developed for SOGS, and continued evolution of the SIRTF operations concept and requirements such that they remain compatible with ST SOGS operation

    A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

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    We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.Comment: 12 pages,55 reference

    Informaticology: combining Computer Science, Data Science, and Fiction Science

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    Motivated by an intention to remedy current complications with Dutch terminology concerning informatics, the term informaticology is positioned to denote an academic counterpart of informatics where informatics is conceived of as a container for a coherent family of practical disciplines ranging from computer engineering and software engineering to network technology, data center management, information technology, and information management in a broad sense. Informaticology escapes from the limitations of instrumental objectives and the perspective of usage that both restrict the scope of informatics. That is achieved by including fiction science in informaticology and by ranking fiction science on equal terms with computer science and data science, and framing (the study of) game design, evelopment, assessment and distribution, ranging from serious gaming to entertainment gaming, as a chapter of fiction science. A suggestion for the scope of fiction science is specified in some detail. In order to illustrate the coherence of informaticology thus conceived, a potential application of fiction to the ontology of instruction sequences and to software quality assessment is sketched, thereby highlighting a possible role of fiction (science) within informaticology but outside gaming

    Design of a 10 Credit Masters Level Assistive Technologies and Universal Design Module

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    The paper reports on the design and evaluation of a 10 credit module that has been designed and taught for the first to 35 full time Computer science and software engineering Masters student

    Nmag micromagnetic simulation tool - software engineering lessons learned

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    We review design and development decisions and their impact for the open source code Nmag from a software engineering in computational science point of view. We summarise lessons learned and recommendations for future computational science projects. Key lessons include that encapsulating the simulation functionality in a library of a general purpose language, here Python, provides great flexibility in using the software. The choice of Python for the top-level user interface was very well received by users from the science and engineering community. The from-source installation in which required external libraries and dependencies are compiled from a tarball was remarkably robust. In places, the code is a lot more ambitious than necessary, which introduces unnecessary complexity and reduces main- tainability. Tests distributed with the package are useful, although more unit tests and continuous integration would have been desirable. The detailed documentation, together with a tutorial for the usage of the system, was perceived as one of its main strengths by the community.Comment: 7 pages, 5 figures, Software Engineering for Science, ICSE201
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