41,535 research outputs found
Blackbox: A Large Scale Repository of Novice Programmers’ Activity
Automatically observing and recording the programming be- haviour of novices is an established computing education research technique. However, prior studies have been con- ducted at a single institution on a small or medium scale, without the possibility of data re-use. Now, the widespread availability of always-on Internet access allows for data col- lection at a much larger, global scale. In this paper we re- port on the Blackbox project, begun in June 2013. Black- box is a perpetual data collection project that collects data from worldwide users of the BlueJ IDE – a programming environment designed for novice programmers. Over one hundred thousand users have already opted-in to Blackbox. The collected data is anonymous and is available to other researchers for use in their own studies, thus benefitting the larger research community. In this paper, we describe the data available via Blackbox, show some examples of analyses that can be performed using the collected data, and discuss some of the analysis challenges that lie ahead
Full-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights
In recent years, Quantum Computing (QC) has progressed to the point where
small working prototypes are available for use. Termed Noisy Intermediate-Scale
Quantum (NISQ) computers, these prototypes are too small for large benchmarks
or even for Quantum Error Correction, but they do have sufficient resources to
run small benchmarks, particularly if compiled with optimizations to make use
of scarce qubits and limited operation counts and coherence times. QC has not
yet, however, settled on a particular preferred device implementation
technology, and indeed different NISQ prototypes implement qubits with very
different physical approaches and therefore widely-varying device and machine
characteristics.
Our work performs a full-stack, benchmark-driven hardware-software analysis
of QC systems. We evaluate QC architectural possibilities, software-visible
gates, and software optimizations to tackle fundamental design questions about
gate set choices, communication topology, the factors affecting benchmark
performance and compiler optimizations. In order to answer key cross-technology
and cross-platform design questions, our work has built the first top-to-bottom
toolflow to target different qubit device technologies, including
superconducting and trapped ion qubits which are the current QC front-runners.
We use our toolflow, TriQ, to conduct {\em real-system} measurements on 7
running QC prototypes from 3 different groups, IBM, Rigetti, and University of
Maryland. From these real-system experiences at QC's hardware-software
interface, we make observations about native and software-visible gates for
different QC technologies, communication topologies, and the value of
noise-aware compilation even on lower-noise platforms. This is the largest
cross-platform real-system QC study performed thus far; its results have the
potential to inform both QC device and compiler design going forward.Comment: Preprint of a publication in ISCA 201
Meaningful Categorisation of Novice Programmer Errors
The frequency of different kinds of error made by students learning to write computer programs has long been of interest to researchers and educators. In the past, various studies investigated this topic, usually by recording and analysing compiler error messages, and producing tables of relative frequencies of specific errors diagnostics produced by the compiler. In this paper, we improve on such prior studies by investigating actual logical errors in student code, as opposed to diagnostic messages produced by the compiler. The actual errors reported here are more precise, more detailed and more accurate than the diagnostic produced automatically
Using Cognitive Computing for Learning Parallel Programming: An IBM Watson Solution
While modern parallel computing systems provide high performance resources,
utilizing them to the highest extent requires advanced programming expertise.
Programming for parallel computing systems is much more difficult than
programming for sequential systems. OpenMP is an extension of C++ programming
language that enables to express parallelism using compiler directives. While
OpenMP alleviates parallel programming by reducing the lines of code that the
programmer needs to write, deciding how and when to use these compiler
directives is up to the programmer. Novice programmers may make mistakes that
may lead to performance degradation or unexpected program behavior. Cognitive
computing has shown impressive results in various domains, such as health or
marketing. In this paper, we describe the use of IBM Watson cognitive system
for education of novice parallel programmers. Using the dialogue service of the
IBM Watson we have developed a solution that assists the programmer in avoiding
common OpenMP mistakes. To evaluate our approach we have conducted a survey
with a number of novice parallel programmers at the Linnaeus University, and
obtained encouraging results with respect to usefulness of our approach
Array operators using multiple dispatch: a design methodology for array implementations in dynamic languages
Arrays are such a rich and fundamental data type that they tend to be built
into a language, either in the compiler or in a large low-level library.
Defining this functionality at the user level instead provides greater
flexibility for application domains not envisioned by the language designer.
Only a few languages, such as C++ and Haskell, provide the necessary power to
define -dimensional arrays, but these systems rely on compile-time
abstraction, sacrificing some flexibility. In contrast, dynamic languages make
it straightforward for the user to define any behavior they might want, but at
the possible expense of performance.
As part of the Julia language project, we have developed an approach that
yields a novel trade-off between flexibility and compile-time analysis. The
core abstraction we use is multiple dispatch. We have come to believe that
while multiple dispatch has not been especially popular in most kinds of
programming, technical computing is its killer application. By expressing key
functions such as array indexing using multi-method signatures, a surprising
range of behaviors can be obtained, in a way that is both relatively easy to
write and amenable to compiler analysis. The compact factoring of concerns
provided by these methods makes it easier for user-defined types to behave
consistently with types in the standard library.Comment: 6 pages, 2 figures, workshop paper for the ARRAY '14 workshop, June
11, 2014, Edinburgh, United Kingdo
A Swiss Pocket Knife for Computability
This research is about operational- and complexity-oriented aspects of
classical foundations of computability theory. The approach is to re-examine
some classical theorems and constructions, but with new criteria for success
that are natural from a programming language perspective.
Three cornerstones of computability theory are the S-m-ntheorem; Turing's
"universal machine"; and Kleene's second recursion theorem. In today's
programming language parlance these are respectively partial evaluation,
self-interpretation, and reflection. In retrospect it is fascinating that
Kleene's 1938 proof is constructive; and in essence builds a self-reproducing
program.
Computability theory originated in the 1930s, long before the invention of
computers and programs. Its emphasis was on delimiting the boundaries of
computability. Some milestones include 1936 (Turing), 1938 (Kleene), 1967
(isomorphism of programming languages), 1985 (partial evaluation), 1989 (theory
implementation), 1993 (efficient self-interpretation) and 2006 (term register
machines).
The "Swiss pocket knife" of the title is a programming language that allows
efficient computer implementation of all three computability cornerstones,
emphasising the third: Kleene's second recursion theorem. We describe
experiments with a tree-based computational model aiming for both fast program
generation and fast execution of the generated programs.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455
- …