The transition from static to dynamic web design

University of Technology, Sydney. Faculty of Design, Architecture and Building.Recent developments in open source software are enabling web designers to configure dynamic web sites quickly, easily and cheaply. The promise of open source CMS software, ultimately is a web environment in which users are programmers. On the surface it would appear that web site creation is moving in the direction of no longer needing expensive custom solutions by professional web developers. These new software systems use a variety of approaches from mere configuration of the system to script implementation. They may require limited programming experience beyond the web designer’s CSS and XHTML capabilities. Based on the Open Source platform, PHP and MySQL offer an easily learned and supported framework to web designers. Web designers now have a tremendous opportunity to harness open source content management systems and extend what they are offering to clients and their employers. Increasingly, it will become the duty of web instructors and of tertiary institutions to equip students with these capabilities, so that they can function effectively in the new environment. This research uses surveys, interviews, and a research workshop with longitudinal results to explore the questions posed. The collation of materials is hosted on a dedicated web site. The findings of this research indicate that students would benefit from a practical approach to web development through the introduction of a CMS in their studies. These are skills employers consider valuable. The main conclusions and recommendations are firstly that many design students see themselves as performing an exclusively aesthetic role in the development of web projects, and secondly, that these students, with proper instruction in the usage of open source CMS’s, are more than capable of making and implementing decisions concerning the functionality or programming of web projects. As a result of this study it is my belief that design students with a deeper understanding of open source CMS’s will be able to occupy a role currently falling between the occupations of graphic design, web development and object-oriented programming. It is my hope that this project will inform and educate so that the wider design community, and in particular design educators, can make more informed decisions about the transition from static to dynamic web design

Code Reuse in Open Source Software Development: Quantitative Evidence, Drivers, and Impediments

The focus of existing open source software (OSS) research has been on how and why individuals and firms add to the commons of public OSS code—that is, on the “giving” side of this open innovation process. In contrast, research on the corresponding “receiving” side of the innovation process is scarce. We address this gap, studying how existing OSS code is reused and serves as an input to further OSS development. Our findings are based on a survey with 686 responses from OSS developers. As the most interesting results, our multivariate analyses of developers’ code reuse behavior point out that developers with larger personal networks within the OSS community and those who have experience in a greater number of OSS projects reuse more, presumably because both network size and a broad project experience facilitate local search for reusable artifacts. Moreover, we find that a development paradigm that calls for releasing an initial functioning version of the software early—as the “credible promise” in OSS—leads to increased reuse. Finally, we identify developers’ interest in tackling difficult technical challenges as detrimental to efficient reuse-based innovation. Beyond OSS, we discuss the relevance of our findings for companies developing software and for the receiving side of open innovation processes, in general

A Framework Analysis of the Open Source Software Development Paradigm

Open Source Software (OSS) has become the subject of much commercial interest of late. Certainly, OSS seems to hold much promise in addressing the core issues of the software crisis, namely that of software taking too long to develop, exceeding its budget, and not working very well. Indeed, there have been several examples of significant OSS success stories—the Linux operating system, the Apache web server, the BIND domain name resolution utility, to name but a few. However, little by way of rigorous academic research on OSS has been conducted to date. In this study, a framework was derived from two previous frameworks which have been very influential in the IS field, namely that of Zachman’s IS architecture (ISA) and Checkland’s CATWOE framework from Soft Systems Methodology (SSM). The resulting framework is used to analyze the OSS approach in detail. The potential future of OSS research is also discussed

Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology

Application of deep learning on histopathological whole slide images (WSIs) holds promise of improving diagnostic efficiency and reproducibility but is largely dependent on the ability to write computer code or purchase commercial solutions. We present a code-free pipeline utilizing free-to-use, open-source software (QuPath, DeepMIB, and FastPathology) for creating and deploying deep learning-based segmentation models for computational pathology. We demonstrate the pipeline on a use case of separating epithelium from stroma in colonic mucosa. A dataset of 251 annotated WSIs, comprising 140 hematoxylin-eosin (HE)-stained and 111 CD3 immunostained colon biopsy WSIs, were developed through active learning using the pipeline. On a hold-out test set of 36 HE and 21 CD3-stained WSIs a mean intersection over union score of 95.5 and 95.3% was achieved on epithelium segmentation. We demonstrate pathologist-level segmentation accuracy and clinical acceptable runtime performance and show that pathologists without programming experience can create near state-of-the-art segmentation solutions for histopathological WSIs using only free-to-use software. The study further demonstrates the strength of open-source solutions in its ability to create generalizable, open pipelines, of which trained models and predictions can seamlessly be exported in open formats and thereby used in external solutions. All scripts, trained models, a video tutorial, and the full dataset of 251 WSIs with ~31 k epithelium annotations are made openly available at to accelerate research in the field.Peer reviewe

5G and the Internet of everyone: motivation, enablers, and research agenda

As mobile broadband subscriptions grow twice as fast as the fixed ones and the Internet of Things comes forth, the 5G vision of the Internet of Everything (people, devices, and things), becomes a substantial and credible part of the near future. In this paper, we argue that the 5G vision is still missing a fundamental concept to realize its societal promise: the Internet of EveryOne (IoEO), i.e., means and principles to overcome the concerns that the current 5G perspective raises for the digital divide and the network neutrality principle. We discuss open-source software and hardware, Community Networks, mobile edge computing and blockchains as enablers of the IoEO and highlight open research challenges with respect to them. The ultimate objective of our paper is to stimulate research with a short-term, lasting impact also on that 50% (or more) of population that will not enjoy 5G anytime soon. Internet of EveryOne, community networks, 5G, mobile edge computing, network neutrality, community cloud computing.Peer ReviewedPostprint (author's final draft

Sport Analytics: Using Open Source Logistic Regression Software to Classify Upcoming Play Type in the NFL

The purpose of this study was to utilize data analytics as means to classify National Football League offensive play types. The open source software R was employed to create a logistic regression based on data for the Cleveland Browns and Pittsburgh Steelers from 13 recent seasons. The regression is based on all first, second, and third downs within regulation play, totaling 26,310 data points. The initial algorithms classify rush or pass for each offense. Revealed through differing coefficients of the independent variables, each team shows a slightly different approach to play selections in response to in-game situations. Identifying the driving factors to play selection is possible by isolating each attribute within the regression. Further examination could yield improved precision to control for changes in head coach, offensive coordinators, player personnel and other factors such as weather because these may influence play type. Logistic regression shows promise as an in-game aid to determining opponent behavior. Specifically, Cleveland\u27s offensive play selection algorithm was correct for 66.4% of plays versus 66.9% for Pittsburgh. Use of open source software and logistic regression of NFL play selection could be beneficial in aiding future game decisions. Further research is recommended to explore possible improvement of the algorithm accuracy

The Open Source Revolution: Transforming the Software Industry with Help from the Government

A new method for making software is stealthily gaining ground in the computer industry, offering a promise of better, cheaper software and the empowerment of the user. The open source movement could revolutionize the software industry...if it succeeds. Open source means software that you are allowed to copy, modify, and give to friends. Source code , the lists of instructions which tell computers how to run, is readily available, allowing you to look inside the workings of a program and change it to suit your needs. A group of programmers, companies, users, and activists have gathered in support of this empowering technology, seeking to persuade businesses and users that open source is the way to go. However, open source faces stiff challenges. The economic basis for the software industry is to charge users by the copy when they buy software. Copying and modification are illegal. The industry and its customers are so mired in this worldview that the idea of giving out a program\u27s recipe, along with a license to change or copy it at will, seems preposterous. Powerful players in the software industry, such as Microsoft, see open source as a threat to their bottom line, and have devoted their energies to discrediting and marginalizing the movement. Beginning from the assumption that cheap, reliable software that empowers the user is a good thing, this thesis looks at the claims made by advocates about the benefits of open source. I explore how the advocates make their case to the business world, the public, and government. I also look at ways in which the government could help bring about an open source revolution, using the policy tools of procurement, research funding, standards enforcement, and antitrust law. I conclude that programmers and public interest lobbyists must join forces to carry this revolution forward, and that the time for action is now, while Microsoft is on trial

Predictiveness and Effectiveness of Story Points in Agile Software Development

Agile Software Development (ASD) is one of the most popular iterative software development methodologies, which takes a different approach from the conventional sequential methods. Agile methods promise a faster response to unanticipated changes during development, typically contrasted with traditional project development, which assumes that software is specifiable and predictable. Traditionally, practitioners and researchers have utilised different Functional Size Measures (FSMs) as the main cost driver to estimate the effort required to develop a project (Software Effort Estimation – SSE). However, FSM methods are not easy to use with ASD. Thus, another measure, namely Story Point (SP), has become popular in this context. SP is a relative unit representing an intuitive mixture of complexity and the required effort of a user requirement. Although recent surveys report on a growing trend toward intelligent effort estimation techniques for ASD, the adoption of these techniques is still limited in practice. Several factors limit the accuracy and adaptability of these techniques. The primary factor is the lack of enough noise-free information at the estimation time, restricting the model’s accuracy and reliability. This thesis concentrates on SEE for ASD from both the technique and data perspectives. Under this umbrella, I first evaluate two prominent state-of-the-art works for SP estimation to understand their strengths and weaknesses. I then introduce and evaluate a novel method for SP estimation based on text clustering. Next, I investigate the relationship between SP and development time by conducting a thorough empirical study. Finally, I explore the effectiveness of SP estimation methods when used to estimate the actual time. To carry out this research, I have curated the TAWOS (Tawosi Agile Web-based Open-Source) dataset, which consists of over half a million issues from Agile, open-source projects. TAWOS has been made publicly available to allow for reproduction and extension in future work