During software testing, defect prediction approaches measure current reliability status, forecasting future program failures, and provide information on how many defects need to be removed before shipping. Existing a...
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ISBN:
(纸本)9783642218262
During software testing, defect prediction approaches measure current reliability status, forecasting future program failures, and provide information on how many defects need to be removed before shipping. Existing approaches often require faults to be detected and identified as a new one, before a model-based trend can be fitted. While during regression testing failures may frequently occur, it is not evident which are related to new faults. Consequently, reliability growth trending can only be performed in sync with fault identification and repair, which is often performed in between regression test cycles. In this paper we present a dynamic, reasoning approach to estimate the number of defects in the system early in the process of regression testing. Our approach, coined Dracon, is based on Bayesian fault diagnosis over abstractions of program traces (also known as program spectra). Experimental results show that Dracon systematically estimates the exact number of (injected) defects, provided sufficient tests cases are available. Furthermore, we also propose a simple, analytic performance model to assess the influence of failed test cases in the estimation. We observe that our empirical findings are in agreement with the model.
Molecular dynamics method is used for computing equilibrium in many physical systems as well as a powerful solver used for minimization of criterion functions such as the stress function in multidimensional scaling. W...
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Verification of software for embedded systems is crucial for ensuring a product's integrity. Formal approaches like static analysis and model checking are gaining momentum in this context. To make an exhaustive ex...
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We are witnessing today an exponential growth of internet technology at an accelerating pace. There are increasingly more and more open and free teaching and learning websites of competitively high quality. When compu...
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This paper deals with the approximate string-matching problem with Hamming distance and a single gap for sequence alignment. We consider an extension of the approximate string-matching problem with Hamming distance, b...
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There is critical, nation-wide need to improve health care and its cost. Health information technology has great promise that is yet to be realized. In this panel four noted experts will discuss key issues that should...
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ISBN:
(纸本)9781450302289
There is critical, nation-wide need to improve health care and its cost. Health information technology has great promise that is yet to be realized. In this panel four noted experts will discuss key issues that should drive health IT, and the challenges for the CHI community to play a leading role.
Recently, there has been great interest in Bioinformatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solvi...
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Recently, there has been great interest in Bioinformatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is Haplotyping, the goal of which is categorizing SNP-fragments into two clusters and deducing a haplotype for each. Since the problem is proved to be NP-hard, several computational and heuristic methods have addressed the problem seeking feasible answers. In this paper, harmony search (HS) is considered as a clustering approach. Extensive computational experiments indicate that the designed HS algorithm achieves a higher accuracy than the genetic algorithm (GA) and particle swarm optimization (PSO) to the MEC model in most cases.
Background: Competitions in text mining have been used to measure the performance of automatic text processing solutions against.a manually annotated gold standard corpus (GSC). The preparation of the GSC is time-cons...
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Background: Competitions in text mining have been used to measure the performance of automatic text processing solutions against.a manually annotated gold standard corpus (GSC). The preparation of the GSC is time-consuming and costly and the final corpus consists at the most of a few thousand documents annotated with a limited set of semantic groups. To overcome these shortcomings, the CALBC project partners (PPs) have produced a large-scale annotated biomedical corpus with four different semantic groups through the harmonisation of annotations from automatic text mining solutions, the first version of the Silver Standard Corpus (SSC-I). The four semantic groups are chemical entities and drugs (CHED), genes and proteins (PRGE), diseases and disorders (DISO) and species (SPE). This corpus has been used for the First CALBC Challenge asking the participants to annotate the corpus with their text processing solutions. Results: All four PPs from the CALBC project and in addition, 12 challenge participants (CPs) contributed annotated data sets for an evaluation against.the SSC-I. CPs could ignore the training data and deliver the annotations from their genuine annotation system, or could train a machine-learning approach on the provided pre-annotated data. In general, the performances of the annotation solutions were lower for entities from the categories CHED and PRGE in comparison to the identification of entities categorized as DISO and SPE. The best performance over all semantic groups were achieved from two annotation solutions that have been trained on the SSC-I. The data sets from participants were used to generate the harmonised Silver Standard Corpus II (SSC-II), if the participant did not make use of the annotated data set from the SSC-I for training purposes. The performances of the participants' solutions were again measured against.the SSC-II. The performances of the annotation solutions showed again better results for DISO and SPE in comparison to CHED and P
In-packet Bloom filters are recently proposed as a possible building block of future Internet architectures replacing IP or MPLS addressing that solves efficient multicast routing, security and other functions in a st...
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ISBN:
(纸本)9781457702495
In-packet Bloom filters are recently proposed as a possible building block of future Internet architectures replacing IP or MPLS addressing that solves efficient multicast routing, security and other functions in a stateless manner. In such frameworks a bloom filter is placed in the header which stores the addresses of the destination nodes or the traversed links. In contrast to the standard Bloom filter, the length of the in-packet Bloom filter must be highly adaptive to the number of stored elements to achieve low communication overhead. In this paper we propose a novel type of Bloom filter called Adaptive Bloom filter, which can adapt its length to the number of elements to be represented with a very fine granularity. The novel filter can significantly reduce the header size for in-packet bloom filter architecture, by eliminating the wasting effect experienced in existing "block-based" approaches which rely on concatenating several standard Bloom filters. Nevertheless, it requires slightly more calculations when adding and removing elements.
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