330,987 research outputs found
Extending Global Education Through Remote Laboratory Access
Advanced software technologies that are integrated with physical laboratories now allow students and researchers to access laboratory equipment and instruments remotely through the Internet. While this capability has been used in engineering and science education successfully for some time, application of this approach to human factors engineering and ergonomics education is new. The development of a remote ergonomics laboratory based on such an Internet technology is described. The focus of this new laboratory is to provide a method of evaluating protective clothing heat stress using a thermal manikin technology. The laboratory has generated global interest and created international collaboration in teaching and research
Identifying and Consolidating Knowledge Engineering Requirements
Knowledge engineering is the process of creating and maintaining
knowledge-producing systems. Throughout the history of computer science and AI,
knowledge engineering workflows have been widely used because high-quality
knowledge is assumed to be crucial for reliable intelligent agents. However,
the landscape of knowledge engineering has changed, presenting four challenges:
unaddressed stakeholder requirements, mismatched technologies, adoption
barriers for new organizations, and misalignment with software engineering
practices. In this paper, we propose to address these challenges by developing
a reference architecture using a mainstream software methodology. By studying
the requirements of different stakeholders and eras, we identify 23 essential
quality attributes for evaluating reference architectures. We assess three
candidate architectures from recent literature based on these attributes.
Finally, we discuss the next steps towards a comprehensive reference
architecture, including prioritizing quality attributes, integrating components
with complementary strengths, and supporting missing socio-technical
requirements. As this endeavor requires a collaborative effort, we invite all
knowledge engineering researchers and practitioners to join us
A Prelimanary Exploration on component based software engineering
Component-based software development (CBD) is a methodology that has been
embraced by the software industry to accelerate development, save costs and
timelines, minimize testing requirements, and boost quality and output.
Compared to the conventional software development approach, this led to the
system's development being completed more quickly. By choosing components,
identifying systems, and evaluating those systems, CBSE contributes
significantly to the software development process. The objective of CBSE is to
codify and standardize all disciplines that support CBD-related operations.
Analysis of the comparison between component-based and scripting technologies
reveals that, in terms of qualitative performance, component-based technologies
scale more effectively. Further study and application of CBSE are directly
related to the CBD approach's success. This paper explores the introductory
concepts and comparative analysis related to component-based software
engineering which have been around for a while, but proper adaption of CBSE are
still lacking issues are also focused
Testing as a Service on Cloud A Review
Software testing is an important part of software engineering life cycle. Software testing is a process used for evaluating an attributes or capability of program and makes sure that it meets the requirements. The application building techniques have changed and has adapted to newly emerging technology of cloud. Cloud computing has changed t he way of obtaining computing resources, and also has given a new direction to manage and deliver computing services, technologies, and solutions. Cloud computing not only brings new business opportunities, but also causes some majo r impacts on software testing and maintenance. Cloud computing creates an opportunity that offer s testing as a service (TaaS) for SaaS and Cloud s. This lead to a new phase shift in conventional testing thereby identifying new issues, challenges and needs in software testing, particular in testing Cloud s and Cloud - based applications. This paper gives a comprehensive view on Testing as a Service. Also a comparative view towards conventional testing and Cloud testing is also considered
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Software development: A paradigm for the future
A new paradigm for software development that treats software development as an experimental activity is presented. It provides built-in mechanisms for learning how to develop software better and reusing previous experience in the forms of knowledge, processes, and products. It uses models and measures to aid in the tasks of characterization, evaluation and motivation. An organization scheme is proposed for separating the project-specific focus from the organization's learning and reuse focuses of software development. The implications of this approach for corporations, research and education are discussed and some research activities currently underway at the University of Maryland that support this approach are presented
A cloud-based tool for sentiment analysis in reviews about restaurants on TripAdvisor
The tourism industry has been promoting its products and services based on the reviews that people often write on travel websites like TripAdvisor.com, Booking.com and other platforms like these. These reviews have a profound effect on the decision making process when evaluating which places to visit, such as which restaurants to book, etc.
In this contribution is presented a cloud based software tool for the massive analysis of this social media data (TripAdvisor.com). The main characteristics of the tool developed are: i) the ability to aggregate data obtained from social media; ii) the possibility of carrying out combined analyses of both people and comments; iii) the ability to detect the sense (positive, negative or neutral) in which the comments rotate, quantifying the degree to which they are positive or negative, as well as predicting behaviour patterns from this information; and iv) the ease of doing everything in the same application (data downloading, pre-processing, analysis and visualisation).
As a test and validation case, more than 33.500 revisions written in English on restaurants in the Province of Granada (Spain) were analyse
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
Towards guidelines for building a business case and gathering evidence of software reference architectures in industry
Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges.
Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain.
Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices.
Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version
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