Aujourd'hui, les éditeurs logiciels ne conçoivent, développent et ne maintiennent plus leur offre logicielle avec comme cible un client unique. Au contraire, les offres logicielles sont conçues pour cibler plusieurs entités. Par conséquent, ces applications doivent s'intégrer dans des environnements différents et s'adapter aux besoins des clients. Ainsi, les produits logiciels développés ne sont plus des programmes uniques, mais des familles de produits. Les systèmes configurables facilitent la création de ces familles de produits. Grâce à eux il est possible de créer un produit logiciel en sélectionnant les fonctionnalités qui seront intégrées. Cependant, la validation de ces systèmes  est une tâche complexe. Un système configurable peut générer plusieurs millions de configurations possibles. Il ne s'agit donc plus de valider un seul et unique produit, mais un ensemble de produits. Cet important nombre de configurations est un problème pour les personnes chargées de la validation. Nous proposons trois contributions qui visent à mieux répondre aux problématiques liées à la variabilité lors des projets de test : une présentation détaillée de deux projets de test industriels faisant face à des problématiques de variabilité issus de deux entreprises : Cisco et Orange ; une méthode originale basée sur les techniques de programmation par contraintes pour extraire des configurations de test qui respectent le critère Pairwise à partir d'un modèle explicite de la variabilité ; une comparaison de cette approche par rapport aux techniques de l'état de l'art et une étude de l'application de cette technique de test sur deux projets de tests industriels. / Nowadays, software companies develop and maintain their software for several clients. Consequently, these applications have to  be integrated in heterogenous context and adapt to the user requriements. All these products are sharing commonalities but also differ in certain point due to business specific constraints. Configurable systems facilitate the creation of these product families. With them it is possible to create a software product by selecting the features that will be integrated, thus, the creation of a product is greatly simplified. However,  the validation of these systems is a complex task. A configurable system can generate millions of possible configurations. Thus, validation process doesn't consist in validating a single product but in validating a set of products. This large number of configurations is a problem for those responsible of the validation. In this thesis we propose three contributions that aim to solve issues raised by  variability during test projects : A detailled presentation of two industrial test projects coping tat variaibility issues; an original methodology based on constraint programming techniques to select test configurations that respect pairwise criteria from a feature model ; an exhaustive comparison of this approach with the existing approches and a detailled study of the application of a such techniques on the two industrials projects.

This thesis shows highly encouraging results as the gain of accuracy reached 18.4% when the pairwise comparisons method was used instead of the direct method for comparing random shapes. The thesis describes a heuristic for generating random but nice shapes, called placated shapes. Random, but visually nice shapes, are often needed for cognitive experiments and processes. These shapes are produced by applying the Gaussian blur to randomly generated polygons. Afterwards, the threshold is set to transform pixels to black and white from di erent shades of gray. This transformation produces placated shapes for easier estimation of areas. Randomly generated placated shapes are used to perform the Monte Carlo method to test the accuracy of cognitive processes by using pairwise comparisons. An on-line questionnaire has been implemented and participants were asked to estimate the areas of ve shapes using a provided unit of measure. They were also asked to compare the shapes in pairs. Such Monte Carlo experiment has never been conducted for 2D case. The received results are of considerable importance.

An incomplete Latin square is a v x v array with an empty n x n subarray with every row and every column containing each symbol at most once and no row or column with an empty cell containing one of the last n symbols. A set of t incomplete mutually orthogonal Latin squares of order v and hole size n is a set of t incomplete Latin squares (containing the same empty subarray on the same set of symbols) with a natural extension to the condition of orthogonality. The existence of such sets have been previously explored only for small values of t. We determine an asymptotic result for the existence of t incomplete mutually orthogonal Latin squares for general t requiring large holes, which we develop from our results on incomplete pairwise balanced designs and incomplete group divisible designs. / Graduate

The Internet has a loosely hierarchical structure. At the top of the hierarchy are the backbones, also called Internet Access Providers (hereafter IAPs). The second layer of the hierarchy is comprised of Internet Service Providers (hereafter ISPs). At the bottom of the hierarchy are the end users, consumers, who browse the web, and websites. To provide access to the whole Internet, the providers must interconnect with each other and share their network infrastructure. Two main forms of interconnection have emerged — peering under which the providers carry each other's traffic without any payments and transit under which the downstream provider pays the upstream provider a certain settlement payment for carrying its traffic. This dissertation develops three game theoretical models to describe the interconnection agreements among the providers, and analysis of those models from two alternative modeling perspectives: a purely non-cooperative game and a network perspective. There are two original contributions of the dissertation. First, we model the formation of peering/transit contracts explicitly as a decision variable in a non-cooperative game, while the current literature does not employ such modeling techniques. Second, we apply network analysis to examine interconnection decisions of the providers, which yields much realistic results. Chapter 1 provides a brief description of the Internet history, architecture and infrastructure as well as the economic literature. In Chapter 2 we develop a model, in which IAPs decide on private peering agreements, comparing the benefits of private peering relative to being connected only through National Access Points (hereafter NAPs). The model is formulated as a multistage game. Private peering agreements reduce congestion in the Internet, and so improve the quality of IAPs. The results show that even though the profits are lower with private peerings, due to large investments, the network where all the providers privately peer is the stable network. Chapter 3 discusses the interconnection arrangements among ISPs. Intra-backbone peering refers to peering between ISPs connected to the same backbone, whereas inter-backbone peering refers to peering between ISPs connected to different backbones. We formulate the model as a two-stage game. Peering affects profits through two channels - reduction of backbone congestion and ability to send traffic circumventing congested backbones. The relative magnitude of these factors helps or hinders peering. In Chapter 4 we develop a game theoretic model to examine how providers decide who they want to peer with and who has to pay transit. There is no regulation with regard to interconnection policies of providers, though there is a general convention that the providers peer if they perceive equal benefits from peering, and have transit arrangements otherwise. The model discusses a set of conditions, which determine the formation of peering and transit agreements. We argue that market forces determine the terms of interconnection, and there is no need for regulation to encourage peering. Moreover, Pareto optimum is achieved under the transit arrangements. / Ph. D.

In this thesis we investigate the use of pairwise testing for PLC embedded software. We compare these automatically generated tests with tests created manually by industrial engineers. The tests were evaluated in terms of fault detection, code coverage and cost. In addition, we compared pairwise testing with randomly generated tests of the same size as pairwise tests. In order to automatically create test suites for PLC software a previously created tool called Combinatorial Test Tool (CTT) was extended to support pairwise testing using the IPOG algorithm. Once test suites were created using CTT they were executed on real industrial programs. The fault detection was measured using mutation analysis. The results of this thesis showed that manual tests achieved better fault detection (8% better mutation score in average) than tests generated using pairwise testing. Even if pairwise testing performed worse in terms of fault detection than manual testing, it achieved better fault detection in average than random tests of the same size. In addition, manual tests achieved in average 97.29% code coverage compared to 93.95% for pairwise testing, and 84.79% for random testing. By looking closely on all tests, manual testing performed equally good as pairwise in terms of achieved code coverage. Finally, the number of tests for manual testing was lower (12.98 tests in average) compared to pairwise and random testing (21.20 test in average). Interestingly enough, for the majority of the programs pairwise testing resulted in fewer tests than manual testing.

The genome sequence alignment problems are very important ones from the computational biology perspective. These problems deal with large amount of data which is memory intensive as well as computation intensive. In the literature, two separate algorithms have been studied and improved – one is a Pairwise sequence alignment algorithm which aligns pairs of genome sequences with memory reduction and parallelism for the computation and the other one is the multiple sequence alignment algorithm that aligns multiple genome sequences and this algorithm is also parallelized efficiently so that the workload of the alignment program is well distributed. The parallel applications can be launched on different environments where shared memory is very well suited for these kinds of applications. But shared memory environment has the limitation of memory usage as well as scalability also these machines are very costly. A better approach is to use the cluster of computers and the cluster environment can be further enhanced to a grid environment so that the scalability can be improved introducing multiple clusters. Here the grid environment is studied as well as the shared memory and cluster environment for the two applications. It can be stated that for carefully designed algorithms the grid environment is comparable for its performance to other distributed environments and it sometimes outperforms the others in terms of the limitations of resources the other distributed environments have.

Pairwise comparison matrices (PCMs) play a key role in multi-criteria decision making, especially in the analytic hierarchy process. It could be necessary for an expert to compare alternatives based on various criteria. However, for a variety of reasons, such as lack of time or insufficient knowledge, it may happen that the expert cannot provide judgments on all pairs of alternatives. In this case, an incomplete pairwise comparison matrix is formed. In the first research part, an optimization algorithm is proposed for the optimal completion of an incomplete PCM. It is intended to numerically minimize a constrained eigenvalue problem, in which the objective function is difficult to write explicitly in terms of variables. Numerical simulations are carried out to examine the performance of the algorithm. The simulation results show that the proposed algorithm is capable of solving the minimization of the constrained eigenvalue problem. In the second part, a comparative analysis of eleven completion methods is studied. The similarity of the eleven completion methods is analyzed on the basis of numerical simulations and hierarchical clustering. Numerical simulations are performed for PCMs of different orders considering various numbers of missing comparisons. The results suggest the existence of a cluster of five extremely similar methods, and a method significantly dissimilar from all the others. In the third part, the filling in patterns (arrangements of known comparisons) of incomplete PCMs based on their graph representation are investigated under given conditions: regularity, diameter and number of vertices, but without prior information. Regular and quasi-regular graphs with minimal diameter are proposed. Finally, the simulation results indicate that the proposed graphs indeed provide better weight vectors than alternative graphs with the same number of comparisons. This research problem’s contributions include a list of (quasi-)regular graphs with diameters of 2 and 3, and vertices from 5 up to 24.

Due to increasing numbers of non-coding RNA (ncRNA) being discovered recently, there is interest in identifying homologs of a given structured RNA sequence. Exhaustive homology searching for structured RNA molecules using covariance models is infeasible on genome-length sequences. Hence, heuristic methods are employed, but they largely ignore structural information in the query. We present a novel method, which uses secondary structure information, to perform homology searches for a structured RNA molecule. We define the concept of a <em>pair seed</em> and theoretically model alignments of random and related paired regions to compute expected sensitivity and specificity. We show that our method gives theoretical gains in sensitivity and specificity compared to a BLAST-based heuristic approach. We provide experimental verification of this gain. <br /><br /> We also show that pair seeds can be effectively combined with the spaced seeds approach to nucleotide homology search. The hybrid search method has theoretical specificity superior to that of the BLAST seed. We provide experimental evaluation of our hypotheses. Finally, we note that our method is easily modified to process pseudo-knotted regions in the query, something outside the scope of covariance model based methods.

Pairwise sequence alignment is a fundamental problem in bioinformatics with wide applicability. This thesis presents three new algorithms for this well-studied problem. First, we present a new algorithm, RDA, which aligns sequences in small segments, rather than by individual bases. Then, we present two algorithms for aligning long genomic sequences: CAPE, a pairwise global aligner, and FEAST, a pairwise local aligner. RDA produces interesting alignments that can be substantially different in structure than traditional alignments. It is also better than traditional alignment at the task of homology detection. However, its main negative is a very slow run time. Further, although it produces alignments with different structure, it is not clear if the differences have a practical value in genomic research. Our main success comes from our local aligner, FEAST. We describe two main improvements: a new more descriptive model of evolution, and a new local extension algorithm that considers all possible evolutionary histories rather than only the most likely. Our new model of evolution provides for improved alignment accuracy, and substantially improved parameter training. In particular, we produce a new parameter set for aligning human and mouse sequences that properly describes regions of weak similarity and regions of strong similarity. The second result is our new extension algorithm. Depending on heuristic settings, our new algorithm can provide for more sensitivity than existing extension algorithms, more specificity, or a combination of the two. By comparing to CAPE, our global aligner, we find that the sensitivity increase provided by our local extension algorithm is so substantial that it outperforms CAPE on sequence with 0.9 or more expected substitutions per site. CAPE itself gives improved sensitivity for sequence with 0.7 or more expected substitutions per site, but at a great run time cost. FEAST and our local extension algorithm improves on this too, the run time is only slightly slower than existing local alignment algorithms and asymptotically the same.

Due to increasing numbers of non-coding RNA (ncRNA) being discovered recently, there is interest in identifying homologs of a given structured RNA sequence. Exhaustive homology searching for structured RNA molecules using covariance models is infeasible on genome-length sequences. Hence, heuristic methods are employed, but they largely ignore structural information in the query. We present a novel method, which uses secondary structure information, to perform homology searches for a structured RNA molecule. We define the concept of a <em>pair seed</em> and theoretically model alignments of random and related paired regions to compute expected sensitivity and specificity. We show that our method gives theoretical gains in sensitivity and specificity compared to a BLAST-based heuristic approach. We provide experimental verification of this gain. <br /><br /> We also show that pair seeds can be effectively combined with the spaced seeds approach to nucleotide homology search. The hybrid search method has theoretical specificity superior to that of the BLAST seed. We provide experimental evaluation of our hypotheses. Finally, we note that our method is easily modified to process pseudo-knotted regions in the query, something outside the scope of covariance model based methods.