A execução da engenharia reversa orientada a objetos de um sistema legado desenvolvido com orientação procedimental é usada como base para sua reengenharia, seguindo duas abordagens diferentes. Na primeira, o sistema passa por reengenharia com mudança de orientação, por meio de segmentação e, posteriormente, é transformado para uma linguagem orientada a objetos de forma semi-automática. Na segunda, é feito o reconhecimento de padrões recorrentes de software no modelo de objetos produzido pela engenharia reversa, para depois efetuar a reengenharia utilizando esses padrões. Os resultados obtidos por intermédio dessas duas abordagens podem ser comparados quanto à manutenibilidade, legibilidade e reuso. A versão original do sistema legado escolhido para a realização da experiência está implementado na linguagem Clipper e possui cerca de vinte mil linhas de código. Trata-se de uma oficina auto-elétrica e mecânica de veículos. Para a engenharia reversa foi escolhido o método Fusion/RE, sendo feita uma proposta para sua evolução, adicionando um maior detalhamento da etapa de abstração do modelo de análise do sistema. Para mudança de orientação do paradigma de desenvolviemnto, de procedimental para orientado a objetos, são propostas duas etapas adicionais a serem executadas após a aplicação do Fusion/RE: o projeto avante do sistema e a segmentação do programa legado. Indicações sobre como fazer a segmentação são fornecidas. A transformação do código segmentado em Clipper para Java é feita com auxílio da máquina Draco-Puc. Uma estratégia é proposta para o reconhecimento de padrões a partir do modelo de objetos do sistema obtido pela engenharia reversa. Por meio dela, instâncias dos padrões Type-Object, Association-Object, State Across a Collection e Behaviour Across a Collection podem ser reconhecidas. Experiências de implementação de alguns desses padrões, em Delphi, são feitas. / The object oriented reverse engineering of a legacy system, originally developed using the procedural paradigm, is the basis for two different reengineering approaches. In the first, the reengineering is done to change the implementation paradigm by segmentation, followed by the semi-automatic transformation to an object oriented language. In the second, recurring patterns are first recognized in the object model produced by the reverse engineering, and then the reengineering is done adopting these patterns. Results obtained by these two approaches are compared to assess their maintainability, legibility and reuse. The original version of the legacy system used in this experience has about twenty thousand lines of Clipper code and refers to an electric and mechanic car repair shop. For the reverse engineering phase the Fusion/RE method is used, and a proposal is done for its evolution, adding features to detail its system analysis model abstraction phase. To change the system orientation paradigm, from procedural to object-oriented, two additional phases are proposed to be conducted after the application of the Fusion/RE method: the forward design of the system and the legacy code segmentation. Hints and rationales are supplied to conduct the code segmentaion. The code transformation from segmented Clipper to Java is done with support of the Draco-Puc machine. A strategy is proposed for pattern recognition based on the system object model obtained through reverse engineering. Through it, instances of Type-Object, Association-Object, State Across a Collection and Behaviour Across a Collection patterns can be recognized. Delphi implementation experiments of these patterns are done.

Engenharia reversa é o conceito de se produzir uma peça tomando como base um original ou modelo físico existentes, sem o uso de desenhos de engenharia. Empresas se voltam para a tecnologia da Engenharia Reversa como um complemento valioso para toda a gama de ferramentas CAD/CAM que elas possuem, devido às dificuldades encontradas quando se necessita trabalhar com superfícies de forma livre. Desta forma, faz-se necessária uma ferramenta que proporcione a inserção das formas deste modelo em um sistema CAD, de forma que se possa usufruir de todas as possibilidades, oferecidas por ele. Neste trabalho, é apresentada uma revisão bibliográfica que aborda a engenharia reversa desde sua origem até as técnicas avançadas existentes atualmente, ou seja, apresentando equipamentos e sistemas específicos usados atualmente para a prática de engenharia reversa. Mostra-se um sistema de engenharia reversa, que foi projetado e implementado realizando a integração desde uma máquina de medir 3 coordenadas até um centro de usinagem CNC com o auxílio de um software CAD comercial, o qual possui módulo de CAM integrado. São apresentados também 3 estudos de casos. / Reverse engineering is the concept of making a part based on an original or existing physical model, without engineering drawings. Companies are using reverse engineering technology as a valuable complement to many of their CAD/CAM tools, due to their difficulties of working with free-form surfaces. It is necessary a tool which provides the insertion of the model forms in the CAD system, therefore enabling to take advantages of all possibilities offered by the system. The Reverse Engineering has developed beyond the traditional copy milling. It is presented a review of the reverse engineering since its origin until recent advanced techniques, where the equipments and specific systems used for reverse engineering practice nowadays are showed. In this work a reverse engineering system has been designed and implemented, which is accomplished by the integration from the coordinate measuring machine until a CNC machining center, by using a commercial CAD software with integrated CAM module. In order to validate the system developed, three case studies are also presented.

<p>Program: MIMA student – International business and Entrepreneurship</p><p>Course name: Master Thesis (EFO705)Title: Imitation as Organization’s StrategyAuthors: Voravej AssavapisitkulSataporn Bukkavesa</p><p>Supervisor: Sven-Åke NyströmProblem: Does imitation really benefit organization?</p><p>Purpose: The authors are writing this topic because the authors feel that this topic is not widely been investigated, moreover, it is a very interesting topic for the authors. According to the course literatures that the authors have read, the authors perceived that most of them focused on innovation and seems like they ignored or mentioned little on the topic of imitation and how can imitation benefits organization. Therefore, the authors are personally interested in the topic. The authors hope that the readers would gain more knowledge on the topic and would be able to apply with their business or study.</p><p>Method: Interpretivist; Documentary; Interview</p><p>Summary: In this Master Thesis, the authors have discussed several dimensions of imitation with examples. First, the authors discussed about imitation during the early stage of industrialization with the examples in Korea. This topic discussed of the opportunity provided through imitation process for the new firms to be able to catch up and compete with experienced firms. The next topic is on unique capability. Firms can apply imitation as their own capability that can prevent others’ imitation, moreover, they can become successful in the new market. Then the authors found that there are ways to imitate other firms’ knowledge legally in the form of strategic alliances. In the topic of creation of strategic alliances, the authors suggested four patterns of engagement that firms can select according to their objectives. Under the topic of firms experience, there are some empirical data supported that the degree of imitation has negative relationship with firms’ experience curve. Moreover, the authors discussed about the how competitors’ actions affect the firms to select different strategy of organization management in the topic of the choice of alliances and mergers and acquisitions by competitor’s move. Then the authors discussed about how successful were the imitations by reverse-engineering implemented by Korea’s electronics industry. Furthermore, the authors also provide examples of imitations in other industries. The next topic is limitation and prevention on imitation. Then the authors provided the reasons why do firms imitate. Moreover, the authors discussed about the factors that affect the speed of imitation process and show how the speed of imitation related to benefits and losses of the firms. Next, the authors suggested some successful strategies for product imitation. Then the authors discussed about the drawbacks of imitation with some examples. Finally, the authors provided the results and analysis of the interviews as primary data collection to show the success of firms that implemented imitations, people’s attitudes toward imitation, and the degree that originality and product origin can limit imitation.</p>

Recognizing standard computational structures (cliches) in a program can help an experienced programmer understand the program. We develop a graph parsing approach to automating program recognition in which programs and cliches are represented in an attributed graph grammar formalism and recognition is achieved by graph parsing. In studying this approach, we evaluate our representation's ability to suppress many common forms of variation which hinder recognition. We investigate the expressiveness of our graph grammar formalism for capturing programming cliches. We empirically and analytically study the computational cost of our recognition approach with respect to two medium-sized, real-world simulator programs.

This dissertation develops and analyzes differential equation-based mathematical models and efficient numerical methods and algorithms for genetic regulatory network identification. The primary objectives of the dissertation are to design, analyze, and test a general variational framework and numerical methods for seeking its approximate solutions for reverse engineering genetic regulatory networks from microarray datasets using the approach based on differential equation modeling. In the proposed variational framework, no structure assumption on the genetic network is presumed, instead, the network is solely determined by the microarray profile of the network components and is identified through a well chosen variational principle which minimizes a biological energy functional. The variational principle serves not only as a selection criterion to pick up the right biological solution of the underlying differential equation model but also provide an effective mathematical characterization of the small-world property of genetic regulatory networks which has been observed in lab experiments. Five specific models within the variational framework and efficient numerical methods and algorithms for computing their solutions are proposed and analyzed in the dissertation. Model validations using both synthetic network datasets and real world subnetwork datasets of Saccharomyces cerevisiae (yeast) and E. Coli are done on all five proposed variational models and a performance comparison vs some existing genetic regulatory network identification methods is also provided. As microarray data is typically noisy, in order to take into account the noise effect in the mathematical models, we propose a new approach based on stochastic differential equation modeling and generalize the deterministic variational framework to a stochastic variational framework which relies on stochastic optimization. Numerical algorithms are also proposed for computing solutions of the stochastic variational models. To address the important issue of post-processing computed networks to reflect the small-world property of underlying genetic regulatory networks, a novel threshholding technique based on the Random Matrix Theory is proposed and tested on various synthetic network datasets.

The battle for cyber supremacy is a cat and mouse game: evolving threats from internal and external sources make it difficult to protect critical systems. With the diverse and high risk nature of these threats, there is a need for robust techniques that can quickly adapt and address this evolution. Existing tools such as Splunk, Snort, and Bro help IT administrators defend their networks by actively parsing through network traffic or system log data. These tools have been thoroughly developed and have proven to be a formidable defense against many cyberattacks. However, they are vulnerable to zero-day attacks, slow attacks, and attacks that originate from within. Should an attacker or some form of malware make it through these barriers and onto a system, the next layer of defense lies on the host. Host level defenses include system integrity verifiers, virus scanners, and event log parsers. Many of these tools work by seeking specific attack signatures or looking for anomalous events. The defenses at the network and host level are similar in nature. First, sensors collect data from the security domain. Second, the data is processed, and third, a response is crafted based on the processing. The application level security domain lacks this three step process. Application level defenses focus on secure coding practices and vulnerability patching, which is ineffective. The work presented in this thesis uses a technique that is commonly employed by malware, dynamic-link library (DLL) injection, to develop dynamic application level security sensors that can extract fine-grain data at runtime. This data can then be processed to provide stronger application level defense by shrinking the vulnerability window. Chapters 5 and 6 give proof of concept sensors and describe the process of developing the sensors in detail.

Program: MIMA student – International business and Entrepreneurship Course name: Master Thesis (EFO705)Title: Imitation as Organization’s StrategyAuthors: Voravej AssavapisitkulSataporn Bukkavesa Supervisor: Sven-Åke NyströmProblem: Does imitation really benefit organization? Purpose: The authors are writing this topic because the authors feel that this topic is not widely been investigated, moreover, it is a very interesting topic for the authors. According to the course literatures that the authors have read, the authors perceived that most of them focused on innovation and seems like they ignored or mentioned little on the topic of imitation and how can imitation benefits organization. Therefore, the authors are personally interested in the topic. The authors hope that the readers would gain more knowledge on the topic and would be able to apply with their business or study. Method: Interpretivist; Documentary; Interview Summary: In this Master Thesis, the authors have discussed several dimensions of imitation with examples. First, the authors discussed about imitation during the early stage of industrialization with the examples in Korea. This topic discussed of the opportunity provided through imitation process for the new firms to be able to catch up and compete with experienced firms. The next topic is on unique capability. Firms can apply imitation as their own capability that can prevent others’ imitation, moreover, they can become successful in the new market. Then the authors found that there are ways to imitate other firms’ knowledge legally in the form of strategic alliances. In the topic of creation of strategic alliances, the authors suggested four patterns of engagement that firms can select according to their objectives. Under the topic of firms experience, there are some empirical data supported that the degree of imitation has negative relationship with firms’ experience curve. Moreover, the authors discussed about the how competitors’ actions affect the firms to select different strategy of organization management in the topic of the choice of alliances and mergers and acquisitions by competitor’s move. Then the authors discussed about how successful were the imitations by reverse-engineering implemented by Korea’s electronics industry. Furthermore, the authors also provide examples of imitations in other industries. The next topic is limitation and prevention on imitation. Then the authors provided the reasons why do firms imitate. Moreover, the authors discussed about the factors that affect the speed of imitation process and show how the speed of imitation related to benefits and losses of the firms. Next, the authors suggested some successful strategies for product imitation. Then the authors discussed about the drawbacks of imitation with some examples. Finally, the authors provided the results and analysis of the interviews as primary data collection to show the success of firms that implemented imitations, people’s attitudes toward imitation, and the degree that originality and product origin can limit imitation.

Microarray experiments generate vast amounts of data that evidently reflect many aspects of the underlying biological processes. A major challenge in computational biology is to extract, from such data, significant information and knowledge about the complex interplay between genes/proteins. An analytical approach that has recently gained much interest is reverse engineering of genetic networks. This is a very challenging approach, primarily due to the dimensionality of the gene expression data (many genes, few time points) and the potentially low information content of the data. Bayesian networks (BNs) and its extension, dynamic Bayesian networks (DBNs) are statistical machine learning approaches that have become popular for reverse engineering. In the present study, a DBN learning algorithm was applied to gene expression data produced from experiments that aimed to study the etiology of necrotizing enterocolitis (NEC), a gastrointestinal inflammatory (GI) disease that is the most common GI emergency in neonates. The data sets were particularly challenging for the DBN learning algorithm in that they contain gene expression measurements for relatively few time points, between which the sampling intervals are long. The aim of this study was, therefore, to evaluate the applicability of DBNs when learning genetic networks for the NEC disease, i.e. from the above-mentioned data sets, and use biological knowledge to assess the hypothesized gene interactions. From the results, it was concluded that the NEC gene expression data sets were not informative enough for effective derivation of genetic networks for the NEC disease with DBNs and Bayesian learning.

A goal of runtime monitoring is to observe software execution to determine whether it complies with its intended behavior. Monitoring allows one to analyze and recover from detected faults, providing prevention activities against catastrophic failure. Although runtime monitoring has been in use for so many years, there is renewed interest in its application largely because of the increasing complexity and ubiquitous nature of software systems. To address such a demand for runtime monitoring and behavioral analysis of software systems, we present RUMBA framework. It utilizes a synergy between static and dynamic analyses to evaluate whether a program behavior complies with specified properties during its execution. The framework is comprised of three steps, namely: i) Extracting Architecture where reverse engineering techniques are used to extract two meta-models of a Java system by utilizing UML-compliant and graph representations of the system model, ii) Seeding Objectives in which information required for filtering runtime events is obtained based on properties that are defined in OCL (Object Constraint Language) as specifications for the behavioral analysis, and iii) Runtime Monitoring and Analysis where behavior of the system is monitored according to the output of the previous stages, and then is analyzed based on the objective properties. The first and the second stages are static while the third one is dynamic. A prototype of our framework has been developed in Java programming language. We have performed a set of empirical studies on the proposed framework to assess the techniques introduced in this thesis. We have also evaluated the efficiency of the RUMBA framework in terms of processor and memory utilization for the case study applications.

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