Exploring Problem Solving Paths in a Java Programming Course

Assessment of students’ programming submissions has been the focus of interest in many studies. Although the final submissions capture the whole program, they often tell very little about how it was developed. In this paper, we are able to look at intermediate programming steps using a unique dataset that captures a series of snapshots showing how students developed their program over time. We assessed each of these intermediate steps and performed a fine-grained concept-based analysis on each step to identify the most common programming paths. Analysis of results showed that most of the students tend to incrementally build the program and improve its correctness. This finding provides us with evidence that intermediate programming steps are important, and need to be taken into account for not only improving user modelling in educational programming systems, but also for providing better feedback to students

Context-Oriented Language Engineering

Context-oriented programming (COP) facilitates creating software that can dynamically adapt to its environment, such as device, user preferences, sensor inputs and so on. Software language engineering (SLE) is the discipline of principled methods and techniques for creating software languages (programming languages, specification languages, DSLs, modeling languages etc.). In this talk I will look at language engineering through the lens of COP: In particular, I’ll explore whether engineering COP language is different from other software languages, what it could mean for programming systems themselves to be context-oriented, how context-oriented concepts such as layers and activation could be applied during language engineering. I’ll conclude with a sketch of further research directions to bring COP closer to SLE, and vice versa

The OmpSs reductions model and how to deal with scatter-updates

Scatter-updates represent a reoccurring algorithmic pattern in many scientific applications. Their scalable execution on modern systems is difficult due to performance limitations introduced by their irregular memory access pattern that prohibits an efficient use of the memory subsystem. Further performance degradation is caused by techniques that are required in order to eliminate potential data races and come at the cost of overhead. Taking a closer look at algorithmic properties, access patterns and common support techniques reveals that a one-size-fits-all solution does not exist and solutions are needed that can adapt to individual properties of the algorithm while maintaining programming transparency. In this work we propose a solution framework that supports a broad set of techniques, provides the required access pattern analytics to allow dynamic decision making and shows what language extensions are needed to maintain programming transparency. A reference implementation in OmpSs, a task-based parallel programming model, shows programmability and scalability of this solution

Benefits of Session Types for software Development

Session types are a formalism used to specify and check the correctness of communication based systems. Within their scope, they can guarantee the absence of communication errors such as deadlock, sending an unexpected message or failing to handle an incoming message. Introduced over two decades ago, they have developed into a significant theme in programming languages. In this paper we examine the beliefs that drive research into this area and make it popular. We look at the claims and motivation behind session types throughout the literature. We identify the hypotheses upon which session types have been designed and implemented, and attempt to clarify and formulate them in a more suitable manner for testing

Distributed Programming with Shared Data

Until recently, at least one thing was clear about parallel programming: tightly coupled (shared memory) machines were programmed in a language based on shared variables and loosely coupled (distributed) systems were programmed using message passing. The explosive growth of research on distributed systems and their languages, however, has led to several new methodologies that blur this simple distinction. Operating system primitives (e.g., problem-oriented shared memory, Shared Virtual Memory, the Agora shared memory) and languages (e.g., Concurrent Prolog, Linda, Emerald) for programming distributed systems have been proposed that support the shared variable paradigm without the presence of physical shared memory. In this paper we will look at the reasons for this evolution, the resemblances and differences among these new proposals, and the key issues in their design and implementation. It turns out that many implementations are based on replication of data. We take this idea one step further, and discuss how automatic replication (initiated by the run time system) can be used as a basis for a new model, called the shared data-object model, whose semantics are similar to the shared variable model. Finally, we discuss the design of a new language for distributed programming, Orca, based on the shared data-object model. 1

Scientific Programming and Computer Architecture

A variety of programming models relevant to scientists explained, with an emphasis on how programming constructs map to parts of the computer.What makes computer programs fast or slow? To answer this question, we have to get behind the abstractions of programming languages and look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture. Two themes emerge: program speed and program modularity. Throughout this book, the premise is to "get under the hood," and the discussion is tied to specific programs. The book digs into linkers, compilers, operating systems, and computer architecture to understand how the different parts of the computer interact with programs. It begins with a review of C/C++ and explanations of how libraries, linkers, and Makefiles work. Programming models covered include Pthreads, OpenMP, MPI, TCP/IP, and CUDA.The emphasis on how computers work leads the reader into computer architecture and occasionally into the operating system kernel. The operating system studied is Linux, the preferred platform for scientific computing. Linux is also open source, which allows users to peer into its inner workings. A brief appendix provides a useful table of machines used to time programs. The book's website (https://github.com/divakarvi/bk-spca) has all the programs described in the book as well as a link to the html text

Do Pair Programming Approaches Transcend Coding? Measuring Agile Attitudes in Diverse Information Systems Courses

Agile methods and approaches such as eXtreme programming (XP) have become the norm for successful organizations not only in the software industry but also for businesses seeking to improve internal software processes. Pair programming in some form is touted as a major functionality and productivity improvement. However, numerous studies show that simply placing two programmers side by side in front of a single computer screen is not enough. We must look at other factors such as programmer expertise, project preparation, and perceived solution quality to understand pair programming’s promises and pitfalls. In our study, we apply tailored programming challenges to a multifaceted group of first-year through senior Information Systems (IS) and non-IS majors to analyze how participant attitudes and perceived benefits of pair programming change from pre- to post-study, as well as determine whether the quality and functionality of the solutions differ across education levels and disciplines. Our findings show a strong interaction effect of gender and major composition (CIS vs. non-CIS majors) in all four dimensions of the ATMI attitude scale. Findings also suggest that experience in problem solving and solution formation are more important than prior specific domain knowledge. Finally, participants’ perceived ability, sense of accomplishment, and completion of the assigned work, regardless of background or demographic, determined their performance outcome on the pair-programming tasks, which suggests that not all forms of attitude and perceived benefits contribute to the performance outcome

A Mathematical Study on “Additive Technique” Versus “Branch and Bound Technique” for Solving Binary Programming Problem

A solid body needs adequate supplements from nourishment that we eat each day. Eating pretty much than what our body needs will prompt lack of healthy sustenance (under-nourishment and over-nourishment).In Malaysia, a few reviews have been directed to examine the wholesome status of Malaysians, particularly among youngsters and youths.However there are different methods for taking care of the menu arranging issue and in this paper Binary Programming (BP) is executed. Separately, "Additive Technique (AT)" and "Branch and Bound Technique (BBT)" are utilized as a part of BP.Both methodologies utilize diverse systems and might yield distinctive ideal arrangements. Along these lines, this study expects to build up a scientific model for eating regimen arranging that meets the essential supplement admission and look at the outcomes yield through additive substance and branch and bound methodologies. The information was gathered from different all inclusive schools and furthermore from the Ministry of Education. The model was illuminated by utilizing the Balas Algorithm through AT and Binary Programming through BBT. © 2018 Institute of Physics Publishing. All rights reserved