3,956 research outputs found
A Concurrency-Agnostic Protocol for Multi-Paradigm Concurrent Debugging Tools
Today's complex software systems combine high-level concurrency models. Each
model is used to solve a specific set of problems. Unfortunately, debuggers
support only the low-level notions of threads and shared memory, forcing
developers to reason about these notions instead of the high-level concurrency
models they chose.
This paper proposes a concurrency-agnostic debugger protocol that decouples
the debugger from the concurrency models employed by the target application. As
a result, the underlying language runtime can define custom breakpoints,
stepping operations, and execution events for each concurrency model it
supports, and a debugger can expose them without having to be specifically
adapted.
We evaluated the generality of the protocol by applying it to SOMns, a
Newspeak implementation, which supports a diversity of concurrency models
including communicating sequential processes, communicating event loops,
threads and locks, fork/join parallelism, and software transactional memory. We
implemented 21 breakpoints and 20 stepping operations for these concurrency
models. For none of these, the debugger needed to be changed. Furthermore, we
visualize all concurrent interactions independently of a specific concurrency
model. To show that tooling for a specific concurrency model is possible, we
visualize actor turns and message sends separately.Comment: International Symposium on Dynamic Language
Knowledge management, innovation and big data: Implications for sustainability, policy making and competitiveness
This Special Issue of Sustainability devoted to the topic of “Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness” attracted exponential attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the expanding cross-section of the uses of sophisticated information and communication technology (ICT) and insights from social science and engineering, all papers included in this Special Issue contribute to the opening of new avenues of research in the field of innovation, knowledge management, and big data. By triggering a lively debate on diverse challenges that companies are exposed to today, this Special Issue offers an in-depth, informative, well-structured, comparative insight into the most salient developments shaping the corresponding fields of research and policymaking
A Brief Study of Open Source Graph Databases
With the proliferation of large irregular sparse relational datasets, new
storage and analysis platforms have arisen to fill gaps in performance and
capability left by conventional approaches built on traditional database
technologies and query languages. Many of these platforms apply graph
structures and analysis techniques to enable users to ingest, update, query and
compute on the topological structure of these relationships represented as
set(s) of edges between set(s) of vertices. To store and process Facebook-scale
datasets, they must be able to support data sources with billions of edges,
update rates of millions of updates per second, and complex analysis kernels.
These platforms must provide intuitive interfaces that enable graph experts and
novice programmers to write implementations of common graph algorithms. In this
paper, we explore a variety of graph analysis and storage platforms. We compare
their capabil- ities, interfaces, and performance by implementing and computing
a set of real-world graph algorithms on synthetic graphs with up to 256 million
edges. In the spirit of full disclosure, several authors are affiliated with
the development of STINGER.Comment: WSSSPE13, 4 Pages, 18 Pages with Appendix, 25 figure
Towards Exascale Scientific Metadata Management
Advances in technology and computing hardware are enabling scientists from
all areas of science to produce massive amounts of data using large-scale
simulations or observational facilities. In this era of data deluge, effective
coordination between the data production and the analysis phases hinges on the
availability of metadata that describe the scientific datasets. Existing
workflow engines have been capturing a limited form of metadata to provide
provenance information about the identity and lineage of the data. However,
much of the data produced by simulations, experiments, and analyses still need
to be annotated manually in an ad hoc manner by domain scientists. Systematic
and transparent acquisition of rich metadata becomes a crucial prerequisite to
sustain and accelerate the pace of scientific innovation. Yet, ubiquitous and
domain-agnostic metadata management infrastructure that can meet the demands of
extreme-scale science is notable by its absence.
To address this gap in scientific data management research and practice, we
present our vision for an integrated approach that (1) automatically captures
and manipulates information-rich metadata while the data is being produced or
analyzed and (2) stores metadata within each dataset to permeate
metadata-oblivious processes and to query metadata through established and
standardized data access interfaces. We motivate the need for the proposed
integrated approach using applications from plasma physics, climate modeling
and neuroscience, and then discuss research challenges and possible solutions
A review of data visualization: opportunities in manufacturing sequence management.
Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application
Embodied Discourses of Literacy in the Lives of Two Preservice Teachers
This study examines the emerging teacher literacy identities of Ian and A.J., two preservice teachers in a graduate teacher education program in the United States. Using a poststructural feminisms theoretical framework, the study illustrates the embodiment of literacy pedagogy discourses in relation to the literacy courses’ discourse of comprehensive literacy and the literacy biographical discourses of Ian and A.J. The results of this study indicate the need to deconstruct how the discourse of comprehensive literacy limits how we, as literacy teacher educators, position, hear and respond to our preservice teachers and suggests the need for differentiation in our teacher education literacy courses
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