Designers' models of the human-computer interface

Understanding design models of the human-computer interface (HCI) may produce two types of benefits. First, interface development often requires input from two different types of experts: human factors specialists and software developers. Given the differences in their backgrounds and roles, human factors specialists and software developers may have different cognitive models of the HCI. Yet, they have to communicate about the interface as part of the design process. If they have different models, their interactions are likely to involve a certain amount of miscommunication. Second, the design process in general is likely to be guided by designers' cognitive models of the HCI, as well as by their knowledge of the user, tasks, and system. Designers do not start with a blank slate; rather they begin with a general model of the object they are designing. The author's approach to a design model of the HCI was to have three groups make judgments of categorical similarity about the components of an interface: human factors specialists with HCI design experience, software developers with HCI design experience, and a baseline group of computer users with no experience in HCI design. The components of the user interface included both display components such as windows, text, and graphics, and user interaction concepts, such as command language, editing, and help. The judgments of the three groups were analyzed using hierarchical cluster analysis and Pathfinder. These methods indicated, respectively, how the groups categorized the concepts, and network representations of the concepts for each group. The Pathfinder analysis provides greater information about local, pairwise relations among concepts, whereas the cluster analysis shows global, categorical relations to a greater extent

Evolving a software development methodology for commercial ICTD projects

This article discusses the evolution of a “DistRibuted Agile Methodology Addressing Technical Ictd in Commercial Settings” (DRAMATICS) that was developed in a global software corporation to support ICTD projects from initial team setup through ICT system design, development, and prototyping, to scaling up and transitioning, to sustainable commercial models. We developed the methodology using an iterative Action Research approach in a series of commercial ICTD projects over a period of more than six years. Our learning is reflected in distinctive methodology features that support the development of contextually adapted ICT systems, collaboration with local partners, involvement of end users in design, and the transition from research prototypes to scalable, long-term solutions. We offer DRAMATICS as an approach that others can appropriate and adapt to their particular project contexts. We report on the methodology evolution and provide evidence of its effectiveness in the projects where it has been used

Exploring the Impact of Socio-Technical Core-Periphery Structures in Open Source Software Development

In this paper we apply the social network concept of core-periphery structure to the sociotechnical structure of a software development team. We propose a socio-technical pattern that can be used to locate emerging coordination problems in Open Source projects. With the help of our tool and method called TESNA, we demonstrate a method to monitor the socio-technical core-periphery movement in Open Source projects. We then study the impact of different core-periphery movements on Open Source projects. We conclude that a steady core-periphery shift towards the core is beneficial to the project, whereas shifts away from the core are clearly not good. Furthermore, oscillatory shifts towards and away from the core can be considered as an indication of the instability of the project. Such an analysis can provide developers with a good insight into the health of an Open Source project. Researchers can gain from the pattern theory, and from the method we use to study the core-periphery movements

System Evolution, Feedback and Compliant Architectures

Proceedings, International Workshop on Feedback and Evolution in Software and Business Processes (FEAST 2000), Imperial College, London. Supported by EPSRCPostprintNon peer reviewe

Project Quality of Offshore Virtual Teams Engaged in Software Requirements Analysis: An Exploratory Comparative Study

The off-shore software development companies in countries such as India use a global delivery model in which initial requirement analysis phase of software projects get executed at client locations to leverage frequent and deep interaction between user and developer teams. Subsequent phases such as design, coding and testing are completed at off-shore locations. Emerging trends indicate an increasing interest in off-shoring even requirements analysis phase using computer mediated communication. We conducted an exploratory research study involving students from Management Development Institute (MDI), India and Marquette University (MU), USA to determine quality of such off-shored requirements analysis projects. Our findings suggest that project quality of teams engaged in pure off-shore mode is comparable to that of teams engaged in collocated mode. However, the effect of controls such as user project monitoring on the quality of off-shored projects needs to be studied further

Modern Data Mining for Software Engineer, A Machine Learning PaaS Review

Using data mining methods to produce information from the data has been proven to be valuable for individuals and society. Evolution of technology has made it possible to use complicated data mining methods in different applications and systems to achieve these valuable results. However, there are challenges in data-driven projects which can affect people either directly or indirectly. The vast amount of data is collected and processed frequently to enable the functionality of many modern applications. Cloud-based platforms have been developed to aid in the development and maintenance of data-driven projects. The field of Information Technology (IT) and data-driven projects have become complex, and they require additional attention compared to standard software development. On this thesis, a literature review is conducted to study the existing industry methods and practices, to define the used terms, and describe the relevant data mining process models. We analyze the industry to find out the factors impacting the evolution of tools and platforms, and the roles of project members. Furthermore, a hands-on review is done on typical machine learning Platforms-as-a-Service (PaaS) with an example case, and heuristics are created to aid in choosing a machine learning platform. The results of this thesis provide knowledge and understanding for the software developers and project managers who are part of these data-driven projects without the in-depth knowledge of data science. In this study, we found out that it is necessary to have a valid process model or methodology, precise roles, and versatile tools or platforms when developing data-driven applications. Each of these elements affects other elements in some way. We noticed that traditional data mining process models are insufficient in the modern agile software development. Nevertheless, they can provide valuable insights and understanding about how to handle the data in the correct way. The cloud-based platforms aid in these data-driven projects to enable the development of complicated machine learning projects without the expertise of either a data scientist or a software developer. The platforms are versatile and easy to use. However, developing functionalities and predictive models which the developer does not understand can be seen as bad practice, and cause harm in the future