Does choice of programming language affect student understanding of programming concepts in a first year engineering course?

Most undergraduate engineering curricula include computer programming to some degree,introducing a structured language such as C, or a computational system such as MATLAB, or both. Many of these curricula include programming in first year engineering courses, integrating the solution of simple engineering problems with an introduction to programming concepts. In line with this practice, Roger Williams University has included an introduction to programming as a part of the first year engineering curriculum for many years. However, recent industry and pedagogical trends have motivated the switch from a structured language (VBA) to a computational system (MATLAB). As a part of the pilot run of this change,the course instructors felt that it would be worthwhile to verify that changing the programming language did not negatively affect students’ ability to understand key programming concepts. In particular it was appropriate to explore students’ ability to translate word problems into computer programs containing inputs, decision statements, computational processes, and outputs. To test the hypothesis that programming language does not affect students’ ability to understand programming concepts, students from consecutive years were given the same homework assignment, with the first cohort using VBA and the second using MATLAB to solve the assignment. A rubric was developed which allowed the investigators to rate assignments independent of programming language. Results from this study indicate that there is not a significant impact of the change in programming language. These results suggest that the choice of programming language likely does not matter for student understanding of programming concepts. Course instructors should feel free to select programming language based on other factors, such as market demand, cost, or the availability of pedagogical resources

CS 1160: Introduction to Computer Programming I

Basic concepts of computer programming with an emphasis on structured programming techniques. Includes an introduction to object-oriented programming. Integrated lecture/lab

Literate programming in C : CWEBx manual

This is the manual for the CWEBx system that supports literate programming in the programming language C. We give an introduction to the concept of Literate programming for structured software documentation, which was developed by D.~E. Knuth. This is followed by a concrete example and a detailed description of the CWEBx system

Behavioural Types

Behavioural type systems in programming languages support the specification and verification of properties of programs beyond the traditional use of type systems to describe data processing. A major example of such a property is correctness of communication in concurrent and distributed systems, motivated by the importance of structured communication in modern software. Behavioural Types: from Theory to Tools presents programming languages and software tools produced by members of COST Action IC1201: Behavioural Types for Reliable Large-Scale Software Systems, a European research network that was funded from October 2012 to October 2016. As a survey of the most recent developments in the application of behavioural type systems, it is a valuable reference for researchers in the field, as well as an introduction to the area for graduate students and software developers

Behavioural Types

Behavioural type systems in programming languages support the specification and verification of properties of programs beyond the traditional use of type systems to describe data processing. A major example of such a property is correctness of communication in concurrent and distributed systems, motivated by the importance of structured communication in modern software. Behavioural Types: from Theory to Tools presents programming languages and software tools produced by members of COST Action IC1201: Behavioural Types for Reliable Large-Scale Software Systems, a European research network that was funded from October 2012 to October 2016. As a survey of the most recent developments in the application of behavioural type systems, it is a valuable reference for researchers in the field, as well as an introduction to the area for graduate students and software developers

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

Safe software development for a video-based train detection system in accordance with EN 50128

Diese Studienarbeit gibt einen Überblick über ausgewählte Teile des Softwareentwicklungsprozesses für sicherheitsrelevante Applikationen am Beispiel eines videobasierten Zugerkennungssystems. Eine IP-Kamera und ein externer Bildverarbeitungscomputer wurden dazu mit einer speziell entworfenen, verteilten Software ausgestattet. Die in Ada und C geschriebenen Teile kommunizieren dabei über ein dediziertes, UDP-basiertes Netzwerkprotokoll. Beide Programme wurden intensiv anhand verschiedener Techniken analysiert, die in der Norm EN 50128 festgelegt sind, welche sich speziell an Software für Eisenbahnsteuerungs- und überwachungssysteme richtet. Eine an der Norm orientierte Struktur mit Verweisen auf die diskutierten Techniken zu Beginn eines jeden Abschnitts erlaubt einen schnellen Vergleich mit den originalen Anforderungen des Normtexts. Zusammenfassend haben sich die Techniken bis auf wenige Ausnahmen als sehr geeignet für die praktische Entwicklung von sicherer Software erwiesen. Allerdings entbindet die Norm durch ihre teils sehr abstrakten Anforderungen das am Projekt beteiligte Personal in keinster Weise von seiner individuellen Verantwortung. Entsprechend sind die hier vorgestellten Techniken für andere Projekte nicht ohne Anpassungen zu übernehmen.:1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2 Description of the problem . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Real-time constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.4 Safety requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Implementation details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1 Camera type and output format . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Transfer Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3 Real-world constrains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.4 Train Detection Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3 EN 50128 requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.1 Software architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.1 Defensive Programming . . . . . . . . . . . . . . . . . . . . . . . 20 3.1.2 Fully Defined Interface . . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.3 Structured Methodology . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.4 Error Detecting and Correcting Codes . . . . . . . . . . . . . . . . 29 3.1.5 Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.1.6 Alternative optionally required measures . . . . . . . . . . . . . . 34 3.2 Software Design and Implementation . . . . . . . . . . . . . . . . . . . . . 35 3.2.1 Structured Methodology . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.2 Modular Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.2.3 Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.4 Design and Coding Standards . . . . . . . . . . . . . . . . . . . . 39 3.2.5 Strongly Typed Programming Languages . . . . . . . . . . . . . . 41 3.2.6 Alternative optionally required measures . . . . . . . . . . . . . . 44 3.3 Unit Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48This paper intends to give an overview of selected parts of the software development process for safety-relevant applications using the example of a video-based train detection. An IP-camera and an external image processing computer were equipped with a custom-built, distributed software system. Written in Ada and C, the system parts communicate via a dedicated UDP-based protocol. Both programs were subject to intense analysis according to measures laid down in the EN 50128 standard specifically targeted at software for railway control and protection systems. Preceding each section, a structure resembling the standard document with references to the discussed measures allows for easy comparison with the original requirements of EN 50128. In summary, the techniques have proven to be very suitable for practical safe software development in all but very few edge-cases. However, the highly abstract descriptive level of the standard requires the staff involved to accept an enormous personal responsibility throughout the entire development process. The specific measures carried out for this project may therefore not be equally applicable elsewhere.:1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2 Description of the problem . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Real-time constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.4 Safety requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Implementation details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1 Camera type and output format . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Transfer Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3 Real-world constrains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.4 Train Detection Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3 EN 50128 requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.1 Software architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.1 Defensive Programming . . . . . . . . . . . . . . . . . . . . . . . 20 3.1.2 Fully Defined Interface . . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.3 Structured Methodology . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.4 Error Detecting and Correcting Codes . . . . . . . . . . . . . . . . 29 3.1.5 Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.1.6 Alternative optionally required measures . . . . . . . . . . . . . . 34 3.2 Software Design and Implementation . . . . . . . . . . . . . . . . . . . . . 35 3.2.1 Structured Methodology . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.2 Modular Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.2.3 Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.4 Design and Coding Standards . . . . . . . . . . . . . . . . . . . . 39 3.2.5 Strongly Typed Programming Languages . . . . . . . . . . . . . . 41 3.2.6 Alternative optionally required measures . . . . . . . . . . . . . . 44 3.3 Unit Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4