Practical Combinatorial Testing: Beyond Pairwise

With new algorithms and tools, developers can apply high-strength combinatorial testing to detect elusive failures that occur only when multiple components interact. In pairwise testing, all possible pairs of parameter values are covered by at least one test, and good tools are available to generate arrays with the value pairs. In the past few years, advances in covering-array algorithms, integrated with model checking or other testing approaches, have made it practical to extend combinatorial testing beyond pairwise tests. The US National Institute of Standards and Technology (NIST) and the University of Texas, Arlington, are now distributing freely available methods and tools for constructing large t-way combination test sets (known as covering arrays), converting covering arrays into executable tests, and automatically generating test oracles using model checking (http://csrc.nist.gov/acts). In this review, we focus on real-world problems and empirical results from applying these methods and tools.     

Beyond Brute Force: Testing Financial Software

Large software development projects that follow formal processes generally divide the work among separate roles on structured teams that tend to employ development staff whose technical expertise is domain-neutral. This is especially true of large outsourcing vendors. Yet, the end users' needs are expressed in the applied domain's specific concepts, terms, and logic. Testing financial software's functionality requires deep subject expertise and an understanding of quality assurance methods and processes. Thorough domain analysis, efficient test designs, specific methods, and well-prepared quality assurance staff are key elements for success.     

全尺寸结构试验应变数据线性化修正方法研究

针对全尺寸飞机结构静力/疲劳试验中的应变测量数据非线性化的问题,进行应变测量数据线性化修正方法研究,提出一种适用于全尺寸飞机结构静力/疲劳试验应变测量数据线性化修正方法并进行工程应用。结果表明,该方法明显提高应变测量数据的准确性,是可行和有效的。该方法为后续海量应变数据自动化处理软件的开发提供理论依据。     

State-of-the-art in Large-Scale Volume Visualization Beyond Structured Data

Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state-of-the-art report, we review works focusing on large-scale volume rendering beyond those typical structured and regular grid representations. We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out-of-core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever-increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large-scale volume rendering systems and also include a review of tools that support the various volume data types discussed.     

Inclusion of Textual Documentation in the Analysis of Multidimensional Data Sets: Application to Gene Expression Data

Recently, biology has been confronted with large multidimensional gene expression data sets where the expression of thousands of genes is measured over dozens of conditions. The patterns in gene expression are frequently explained retrospectively by underlying biological principles. Here we present a method that uses text analysis to help find meaningful gene expression patterns that correlate with the underlying biology described in scientific literature. The main challenge is that the literature about an individual gene is not homogenous and may addresses many unrelated aspects of the gene. In the first part of the paper we present and evaluate the neighbor divergence per gene (NDPG) method that assigns a score to a given subgroup of genes indicating the likelihood that the genes share a biological property or function. To do this, it uses only a reference index that connects genes to documents, and a corpus including those documents. In the second part of the paper we present an approach, optimizing separating projections (OSP), to search for linear projections in gene expression data that separate functionally related groups of genes from the rest of the genes; the objective function in our search is the NDPG score of the positively projected genes. A successful search, therefore, should identify patterns in gene expression data that correlate with meaningful biology. We apply OSP to a published gene expression data set; it discovers many biologically relevant projections. Since the method requires only numerical measurements (in this case expression) about entities (genes) with textual documentation (literature), we conjecture that this method could be transferred easily to other domains. The method should be able to identify relevant patterns even if the documentation for each entity pertains to many disparate subjects that are unrelated to each other.     

复杂文本网数据的主题建模进展

文中介绍了大规模文本网数据的主题建模研究的特点和近年来的重要进展.主题建模方法吸引了世界范围的广泛兴趣,并且促进了许多重要的数据挖掘、计算机视觉和计算生物应用系统的发展,包括文本自动摘要、信息检索、信息推荐、主题检测和追踪、自然场景理解、人体动作识别以及微阵列基因表达分析等.文中重点介绍文本网数据的4个主要特点以及对应的主题模型.文本网数据含有动态、高阶、多通路及分布式的结构,而之前的主题模型仅对部分的结构进行建模.而文中讨论了在三维马尔可夫模型的框架下统一对文本网数据的4个结构特点进行建模,并分析了结合三维马尔可夫模型和二型模糊系统对分布式单词计算和主题建模应用的可能性.除了对文本网数据的结构建模之外,还讨论了一些对三维马尔可夫模型能量最小化的机器学习算法.     

Component-Trees and Multivalued Images: Structural Properties

Component-trees model the structure of grey-level images by considering their binary level-sets obtained from successive thresholdings. They also enable to define anti-extensive filtering procedures for such images. In order to extend this image processing approach to any (grey-level or multivalued) images, both the notion of component-tree, and its associated filtering framework, have to be generalised. In this article we deal with the generalisation of the component-tree structure. We define a new data structure, the component-graph, which extends the notion of component-tree to images taking their values in any (partially or totally) ordered set. The component-graphs are declined in three variants, of increasing richness and size, whose structural properties are studied.     

基于扩展有限状态机测试中测试输入数据自动选取的研究

扩展有限状态机(EFSM)模型是有限状态机(FSM)模型的一个扩展，它在FSM模型的基础上增加了变量、操作以及状态迁移的前置条件，通过EFSM我们可以更加精确地刻画软件系统的动态行为．基于EFSM的测试可以应用到许多领域，因此具有重要的研究价值和实际意义．许多研究人员已经提出了基于FSM测试的测试输入序列的构造方法，但基于EFSM的测试与FSM相比由于变量和状态迁移的前置条件的引入，增加了构造其测试输入的复杂性．我们认为基于EFSM测试的测试输入应该包含两个部分：即测试输入序列以及该输入序列上包含的输入变量的确定值(测试输入数据)．手工选取这些测试数据的工作十分繁琐，极大地增加了测试的花费，因此自动选取这些测试数据可以大大提高实际测试工作的效率．该文提出一种基于EFSM测试的测试数据自动选取方法，该方法利用两个关键的步骤：①区间削减和②分段梯度最优下降算法来自动选取测试数据．实验表明利用该方法可以自动选取大部分的测试数据，并且收敛速度较快；在某些无法得到确定解的情况下，区间削减也可以为测试人员提供一个较小的输入变量取值区间，方便了测试人员从中手工选择测试数据．     

Query Languages for Data Exchange: Beyond Unions of Conjunctive Queries

The class of unions of conjunctive queries (UCQ) has been shown to be particularly well-behaved for data exchange; its certain answers can be computed in polynomial time (in terms of data complexity). However, this is not the only class with this property; the certain answers to any Datalog program can also can be computed in polynomial time. The problem is that both UCQ and Datalog do not allow negated atoms, as adding an unrestricted form of negation to these languages yields to intractability.     

Testing for Structural Breaks at Unknown Time: A Steeplechase

This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.     

Verification of Safety Properties Using Integer Programming: Beyond the State Equation

The state equation is a verification technique that has been applied—not always under this name—to numerous systems modelled as Petri nets or communicating automata. Given a safety property P, the state equation is used to derive a necessary condition for P to hold which can be mechanically checked. The necessary conditions derived from the state equation are known to be of little use for systems communicating by means of shared variables, in the sense that many of these systems satisfy the property but not the conditions. In this paper, we use traps, a well-known notion of net theory, to obtain stronger conditions that can still be efficiently checked. We show that the new conditions significantly extend the range of verifiable systems.     

Beyond Music Sharing: An Evaluation of Peer-to-Peer Data Dissemination Techniques in Large Scientific Collaborations

The avalanche of data from scientific instruments and the ensuing interest from geographically distributed users to analyze and interpret it accentuates the need for efficient data dissemination. A suitable data distribution scheme will find the delicate balance between conflicting requirements of minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We identify several data distribution techniques, some successfully employed by today’s peer-to-peer networks: staging, data partitioning, orthogonal bandwidth exploitation, and combinations of the above. We use simulations to explore the performance of these techniques in contexts similar to those used by today’s data-centric scientific collaborations and derive several recommendations for efficient data dissemination. Our experimental results show that the peer-to-peer solutions that offer load balancing and good fault tolerance properties and have embedded participation incentives lead to unjustified costs in today’s scientific data collaborations deployed on over-provisioned network cores. However, as user communities grow and these deployments scale, peer-to-peer data delivery mechanisms will likely outperform other techniques.     

数据融合技术在航空发动机试验中的应用

将分布图法和基于算术平均值与分批估计的数据融合方法应用到航空发动机试验稳态数据采集的性能计算中,使稳态数据更准确地反映发动机的性能.这种方法计算简单,易于实现,具有较高的可靠性,通过在某型航空发动机试车台的实际应用结果证明了该方法的有效性.     

数据融合算法在农药残毒检测系统中的应用

农药残毒检测在食品安全监管的过程中具有重要意义。通过自行设计的微型农药残毒快速检测仪对不同浓度的敌百虫溶液进行了多组测量。试验结果表明,大于最低检出值的溶液浓度与发光强度之间呈线性关系。在概率融合意义下定义模糊支持区间和模糊支持概率,将一种适合于单传感器重复采样的数据融合方法应用于农药残毒检测数据的处理中,克服了传统数字滤波方法在抗干扰方面的不稳定性,达到快速、准确检测的目的。     

Extended Branch Decomposition Graphs: Structural Comparison of Scalar Data

We present a method to find repeating topological structures in scalar data sets. More precisely, we compare all subtrees of two merge trees against each other – in an efficient manner exploiting redundancy. This provides pair‐wise distances between the topological structures defined by sub/superlevel sets, which can be exploited in several applications such as finding similar structures in the same data set, assessing periodic behavior in time‐dependent data, and comparing the topology of two different data sets. To do so, we introduce a novel data structure called the extended branch decomposition graph, which is composed of the branch decompositions of all subtrees of the merge tree. Based on dynamic programming, we provide two highly efficient algorithms for computing and comparing extended branch decomposition graphs. Several applications attest to the utility of our method and its robustness against noise.     

基因组高通量测序数据结构变异识别算法

遗传变异是生命的基本特征,遗传变异与表型差异之间的关系,是现代生物学的一个基本问题.由基因决定生物体的遗传特征和主要个体差异的观念正在逐渐改变,过去几年的许多研究显示,基因组中大尺度的结构变异与个体的表型差异和疾病等有一定的关联.有关遗传变异和表型多样性的研究,需要比较生物体个体基因组间的各种不同.利用NGS数据全面分析结构变异的技术目前仍然不成熟.因此本文根据生物学知识,利用高通量测序数据,对植物基因组结构变异的识别问题深入系统的研究,提出新的结构变异识别方法和精确的断点预测方法.