Teaching Concurrent Software Design: A Case Study Using Android

In this article, we explore various parallel and distributed computing topics from a user-centric software engineering perspective. Specifically, in the context of mobile application development, we study the basic building blocks of interactive applications in the form of events, timers, and asynchronous activities, along with related software modeling, architecture, and design topics.Comment: Submitted to CDER NSF/IEEE-TCPP Curriculum Initiative on Parallel and Distributed Computing - Core Topics for Undergraduate

Nineteen Ways of Looking at Statistical Software

We identify principles and practices for writing and publishing statistical software with maximum benefit to the scholarly community.

Towards a re-engineering method for web services architectures

Recent developments in Web technologies – in particular through the Web services framework – have greatly enhanced the flexible and interoperable implementation of service-oriented software architectures. Many older Web-based and other distributed software systems will be re-engineered to a Web services-oriented platform. Using an advanced e-learning system as our case study, we investigate central aspects of a re-engineering approach for the Web services platform. Since our aim is to provide components of the legacy system also as services in the new platform, re-engineering to suit the new development paradigm is as important as re-engineering to suit the new architectural requirements

Teaching programming with computational and informational thinking

Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming. There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming. Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving. Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related. In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming

Some Notes on the Past and Future of Lisp-Stat

Lisp-Stat was originally developed as a framework for experimenting with dynamic graphics in statistics. To support this use, it evolved into a platform for more general statistical computing. The choice of the Lisp language as the basis of the system was in part coincidence and in part a very deliberate decision. This paper describes the background behind the choice of Lisp, as well as the advantages and disadvantages of this choice. The paper then discusses some lessons that can be drawn from experience with Lisp-Stat and with the R language to guide future development of Lisp-Stat, R, and similar systems.