1,075,988 research outputs found
How software engineering research aligns with design science: A review
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
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
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
Design of a 10 Credit Masters Level Assistive Technologies and Universal Design Module
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
Designing requirements engineering research
Engineering sciences study different different topics than natural sciences, and utility is an essential factor in choosing engineering research problems. But despite these differences, research methods for the engineering sciences are no different than research methods for any other kind of science. At most there is a difference in emphasis. In the case of requirements engineering research - and more generally software engineering research - there is a confusion about the relative roles of research and about design and the methods appropriate for each of these activities. This paper analyzes these roles and provides a classification of research methods that can be used in any scienceāengineering or otherwise
Nmag micromagnetic simulation tool - software engineering lessons learned
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
Ethical and Social Aspects of Self-Driving Cars
As an envisaged future of transportation, self-driving cars are being
discussed from various perspectives, including social, economical, engineering,
computer science, design, and ethics. On the one hand, self-driving cars
present new engineering problems that are being gradually successfully solved.
On the other hand, social and ethical problems are typically being presented in
the form of an idealized unsolvable decision-making problem, the so-called
trolley problem, which is grossly misleading. We argue that an applied
engineering ethical approach for the development of new technology is what is
needed; the approach should be applied, meaning that it should focus on the
analysis of complex real-world engineering problems. Software plays a crucial
role for the control of self-driving cars; therefore, software engineering
solutions should seriously handle ethical and social considerations. In this
paper we take a closer look at the regulative instruments, standards, design,
and implementations of components, systems, and services and we present
practical social and ethical challenges that have to be met, as well as novel
expectations for software engineering.Comment: 11 pages, 3 figures, 2 table
Informaticology: combining Computer Science, Data Science, and Fiction Science
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 science methodology for information systems and software engineering
Textbook on design science methodology. http://link.springer.com/book/10.1007/978-3-662-43839-
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OntoEng: A design method for ontology engineering in information systems
This paper addresses the design problem relating to ontology engineering in the discipline of information systems. Ontology engineering is a realm that covers issues related to ontology development and use throughout its life span. Nowadays, ontology as a new innovation promises to improve the design, semantic integration, and utilization of information systems. Ontologies are the backbone of knowledge-based systems. In addition, they establish sharable and reusable common understanding of specific domains amongst people, information systems, and software agents. Notwithstanding, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. On the basis of the
gathered experience during the development of V4 Telecoms Business Model Ontology as well as the conducted integration of the related literature from the design science paradigm, this paper introduces OntoEng and its application as a novel systematic design
method for ontology engineering
GOES-R Algorithms: A Common Science and Engineering Design and Development Approach for Delivering Next Generation Environmental Data Products
GOES-R, the next generation of the National Oceanic and Atmospheric Administrationās (NOAA) Geostationary Operational Environmental Satellite (GOES) System, represents a new technological era in operational geostationary environmental satellite systems. GOES-R will provide advanced products that describe the state of the atmosphere, land, oceans, and solar/ space environments over the western hemisphere. The Harris GOES-R Ground Segment team will provide the software, based on government-supplied algorithms, and engineering infrastructures designed to produce and distribute these next-generation data products. The Harris GOES-R Team has adopted an integrated applied science and engineering approach that combines rigorous system engineering methods, with modern software design elements to facilitate the transition of algorithms for Level 1 and 2+ products to operational software. The Harris Team GOES-R GS algorithm framework, which includes a common data model interface, provides general design principles and standardized methods for developing general algorithm services, interfacing to external data, generating intermediate and L1b and L2 products and implementing common algorithm features such as metadata generation and error handling.
This work presents the suite of GOES-R products, their properties and the process by which the related requirements are maintained during the complete design/development life-cycle. It also describes the algorithm architecture/engineering approach that will be used to deploy these algorithms, and provides a preliminary implementation road map for the development of the GOES-R GS software infrastructure, and a view into the integration of the framework and data model into the final design
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