In recent year the research field of the combinatorial testing, which can roughlybe divided into two kinds including pair-wise coverage and multi-wise coverage. a lot of scholar try to use various strategies to generate test data automatically. In order to weight the generated test set, the generated test data must satisfy certain criterion. But these combinatorial strategy neglected the flexibility of using on the practice. Considering software testing from the practice, which often be restricted by the cost. For this reason, how to obtaint the greatest testing benefits under the limited cost must be considered on the parctice. But in the extant combinatorial strategy, there is no flexible use. In other words, we must testing test set totally. Therefore, there is very great restriction to exist on using the test data generated by the extant combinatorial strategy on the practice. So, this paper proposes a flexible combinatorial strategy based on CSP, which allow users to do the most valid testing under the limited cost, which also allow users join the constraints that needs at any time during the testing process, revise the test data that we produced dynamically. The experimental result indicate that our method perform well, it can avoid including the test data whether some users think the interests less or unnecessarier, in order to achive the greatest testing beneifts.Further, we can achive the goal of reducing the quantity of testing data.

Most applications spend a significant amount of time in the iterative parts of a computation. They typically iterate over the same set of operations with different values. These values either depend on inputs or values calculated in previous iterations. While loops capture some iterative behavior, in many cases such a behavior is spread over whole program sometimes through recursion. Understanding iterative behavior of the computation can be very useful to fine-tune it. In this thesis, we present a profiling based framework to understand and improve performance of iterative computation. We capture the state of iterations in two aspects 1) Algorithmic State 2) Program State. We demonstrate the applicability of our framework for capturing algorithmic state by applying it to the SAT Solvers and program state by applying it to a variety of benchmarks exhibiting completely parallelizable loops. Further, we show that such a performance characterization can be successfully used to improve the performance of the underlying application. Many high performance combinatorial optimization applications involve SAT solving. A variety of SAT solvers have been developed that employ different data structures and different propagation methods for converging on a fixed point for generating a satisfiable solution. The performance debugging and tuning of SAT solvers to a given domain is an important problem encountered in practice. Unfortunately not much work has been done to quantify the iterative efficiency of SAT solvers. In this work, we develop quantifiable measures for calculating convergence efficiency of SAT solvers. Here, we capture the Algorithmic state of the application by tracking the assignment of variables for each iteration. A compact representation of profile data is developed to track the rate of progress and convergence. The novelty of this approach is that it is independent of the specific strategies used in individual solvers, yet it gives key insights into the "progress" and "convergence behavior" of the solver in terms of a specific implementation at hand. An analysis tool is written to interpret the profile data and extract values of the following metrics such as: average convergence rate, efficiency of iteration and variable stabilization. Finally, using this system we produce a study of 4 well known SAT solvers to compare their iterative efficiency using random as well as industrial benchmarks. Using the framework, iterative inefficiencies that lead to slow convergence are identified. We also show how to fine-tune the solvers by adapting the key steps. We also show that the similar profile data representation can be easily applied to loops, in general, to capture their program state. One of the key attributes of the program state inside loops is their branch behavior. We demonstrate the applicability of the framework by profiling completely parallelizable loops (no cross-iteration dependence) and by storing the branching behavior of each iteration. The branch behavior across a group of iterations is important in devising the thread warps from parallel loops for efficient execution on GPUs. We show how some loops can be effectively parallelized on GPUs using this information.

<p>This thesis describes the development and use ofnon-immunoglobulin affinity proteins denoted affibodies asalternatives to antibodies in different immunotechnologyapplications. A 58 aa IgG Fc binding three-helix bundle domainZ, derived from staphylococcal protein A has been used asframework for library constructions, in which the face of themolecule involved in the native binding activity has beenengineered by combinatorial protein engineering. Recruting 13surface-located positions for simultanenous substitutionmutagenesis, using degenerated oligonucleotides for libraryassembly at the genetic level, two libraries differing in thechoice of codons were constructed to serve as general sourcesof novel affinity proteins. The libraries were adapted fordisplay on<i>E. coli</i>filamentous phage particles allowing<i>in vitro</i>selection of desired variants capable ofbinding a given target molecule. In selections using human IgAas target, several new IgA specific affibodies could beidentified. One variant Z_IgA1, was further investigated and showed binding toboth IgA1 and IgA2 human subclasses as well as to secretoryIgA. This variant was further demonstrated uesful as ligand inaffinity chromatography purification for recovery of IgA fromdifferent samples including unconditioned human plasma.Affibodies of different specificities were also fused to otherprotein domains to construct fusion proteins of relevance forimmunotechnology applications. Using Fc of human IgG as genefusion partner, "artificial antbodies" could be produced in<i>E. coli</i>as homodimeic proteins, where the antigenbinding was confered by N-terminally positioned affibodymoieties of different valencies. One area of application forthis type of constructs was demonstrated through specificdetection of the target protein by Western blotting. Exploitingthe uncomplicated structure of affibody affinity proteins, genefusions between affibodies and the homotetrameric reporterenzyme β-galactosidase were constructed, which could beproduced as soluble proteins intracellularly in<i>E. coli</i>. The potential use of such recombinantimmunoconjugates in immunotechnology was demonstrated in ELISAdot-blot and immunohistochemistry, where in the latter case IgAdepositions in the glomeruli of a human kidney biopsy could bespecfically detected with low background staining ofsurrounding tissues. In a novel format for sandwich ELISA, thepossible advantage of the bacterial origin of the affibodyclass of affinity proteins was investigated. As a means tocircumvent problems associated with the presence of humanheterophilic antibodies in serum, causing bakground signals dueto analyte-independent crosslinking of standard capture anddetection antibody reagents, assay formats based oncombinations of antibody and affibody reagents for capture anddetection were investigated and found to be of potentialuse.</p><p><b>Keywords:</b>phage display, combinatorial, affinity, IgAligand, immunohistochemistry, affibody-fusions</p>

Thesis (M.S.)--Rochester Institute of Technology, 2004. / Typescript. Includes bibliographical references (leaves 71-75).

Thesis (M.A.) in Mathematics--University of Maine, 2001. / Includes vita. Includes bibliographical references (leaf 45).

Thesis (Ph. D.)--University of Oregon, 2002. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 118-120). Also available for download via the World Wide Web; free to University of Oregon users.

Network coding is a novel technique to improve the throughput of networks to transfer messages from sources to sinks. Before the birth of network coding, intermediate nodes can only forward the received messages. In a network coding scheme, the intermediate nodes are allowed to mix the received messages from different incoming links. Network coding has found a wide range of applications, such as peer-to-peer networks, distributed storage and content distribution. The theory of network encoding complexity aims to deal with the question what the minimum number of encoding nodes needed in networks is. In order to tackle this question, we convert it into a combinatorial optimization problem. For directed networks, I examine the number of “mergings”, a special type of graph structure. Consider an acyclic directed network G with l source-sink pairs. Let ci denote the minimum size of edge-cut between i-th source-sink pair for 1 ≤ i ≤ l. Then, by Menger’s theorem, there exists a group of ci edge-disjoint paths (Menger’s paths) between i-th source-sink pair. Although within the same group these paths are edge-disjoint, the paths from different groups may have to merge with each other. It is known that by choosing Menger’s paths appropriately, the number of mergings among different groups of Menger’s paths is always bounded by a constant, which is independent of the size of G. The tightest such constant for the all the above-mentioned networks is denoted byM(c1, c2, . . . , cl) when all sources are distinct, and by M∗(c1, c2, . . . , cl) when all sources are identical. It turns out that M and M∗ are closely related to the network encoding complexity for a variety of networks, such as multicast networks, two-way networks and networks with multiple sessions of unicast. Computation of these two important functions, however, appears to be rather difficult; so far there are no explicit formulas for M and M∗ for a generic parameter c1, c2, . . . , cl. In this thesis, I derive exact values of and tighter bounds on M and M∗ for some parameters, and establish the inequality relationships between M and M∗. For undirected networks, I examine the number of “hubs”, the vertices of degree at least three. Compared to directed networks, study on network en-coding complexity in undirected networks has seen little progress. Consider an undirected network G with l source-sink pairs. For i = 1, 2, . . . , l, let ci de-note the minimum size of vertex-cut between i-th source-sink pair. I study H (c1, c2, . . . , cl), the minimum number of hubs needed in an undirected network with min-cut constraints. The function H is closely related to network en-coding complexity for undirected networks. I prove that under some constraints, regardless of the size of the undirected networks, such minimum number is always bounded above and I derive tight upper bounds for some special parameters. In particular, for two pairs of sources and sinks, I present a novel path-searching algorithm, the analysis of which is instrumental for the derivations of the tight upper bounds. / published_or_final_version / Mathematics / Doctoral / Doctor of Philosophy

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This thesis introduces 'spy agents' as a new security paradigm for evaluating trust in remote hosts in mobile code scenarios. In this security paradigm, a spy agent, i.e. a mobile agent which circulates amongst a number of remote hosts, can employ a variety of techniques in order to both appear 'normal' and suggest to a malicious host that it can 'misuse' the agent's data or code without being held accountable. A framework for the operation and deployment of such spy agents is described. Subsequently, a number of aspects of the operation of such agents within this framework are analysed in greater detail. The set of spy agent routes needs to be constructed in a manner that enables hosts to be identified from a set of detectable agent-specific outcomes. The construction of route sets that both reduce the probability of spy agent detection and support identification of the origin of a malicious act is analysed in the context of combinatorial group testing theory. Solutions to the route set design problem are proposed. A number of spy agent application scenarios are introduced and analysed, including: a) the implementation of a mobile code email honeypot system for identifying email privacy infringers, b) the design of sets of agent routes that enable malicious host detection even when hosts collude, and c) the evaluation of the credibility of host classification results in the presence of inconsistent host behaviour. Spy agents can be used in a wide range of applications, and it appears that each application creates challenging new research problems, notably in the design of appropriate agent route sets.

published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy