2,759 research outputs found
Practical Run-time Checking via Unobtrusive Property Caching
The use of annotations, referred to as assertions or contracts, to describe
program properties for which run-time tests are to be generated, has become
frequent in dynamic programing languages. However, the frameworks proposed to
support such run-time testing generally incur high time and/or space overheads
over standard program execution. We present an approach for reducing this
overhead that is based on the use of memoization to cache intermediate results
of check evaluation, avoiding repeated checking of previously verified
properties. Compared to approaches that reduce checking frequency, our proposal
has the advantage of being exhaustive (i.e., all tests are checked at all
points) while still being much more efficient than standard run-time checking.
Compared to the limited previous work on memoization, it performs the task
without requiring modifications to data structure representation or checking
code. While the approach is general and system-independent, we present it for
concreteness in the context of the Ciao run-time checking framework, which
allows us to provide an operational semantics with checks and caching. We also
report on a prototype implementation and provide some experimental results that
support that using a relatively small cache leads to significant decreases in
run-time checking overhead.Comment: 30 pages, 1 table, 170 figures; added appendix with plots; To appear
in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201
Analytical/ML Mixed Approach for Concurrency Regulation in Software Transactional Memory
In this article we exploit a combination of analytical and Machine Learning (ML) techniques in order to build a performance model allowing to dynamically tune the level of concurrency of applications based on Software Transactional Memory (STM). Our mixed approach has the advantage of reducing the training time of pure machine learning methods, and avoiding approximation errors typically affecting pure analytical approaches. Hence it allows very fast construction of highly reliable performance models, which can be promptly and effectively exploited for optimizing actual application runs. We also present a real implementation of a concurrency regulation architecture, based on the mixed modeling approach, which has been integrated with the open source Tiny STM package, together with experimental data related to runs of applications taken from the STAMP benchmark suite demonstrating the effectiveness of our proposal. © 2014 IEEE
Engineering DFS-Based Graph Algorithms
Depth-first search (DFS) is the basis for many efficient graph algorithms. We
introduce general techniques for the efficient implementation of DFS-based
graph algorithms and exemplify them on three algorithms for computing strongly
connected components. The techniques lead to speed-ups by a factor of two to
three compared to the implementations provided by LEDA and BOOST.
We have obtained similar speed-ups for biconnected components algorithms. We
also compare the graph data types of LEDA and BOOST
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