BlogForever D2.4: Weblog spider prototype and associated methodology

The purpose of this document is to present the evaluation of different solutions for capturing blogs, established methodology and to describe the developed blog spider prototype

Architecture internalisation in BIP

International audienceWe consider two approaches for building component-based systems, which we call respectively architecture-based and architecture-agnostic. The former consists in describing coordination constraints in a purely declarative manner through parametrizable glue operators; it provides higher abstraction level and, consequently, stronger correctness by construction. The latter uses simple fixed coordination primitives, which are spread across component behaviour; it is more error-prone, but allows performance optimisation. We study architecture internalisation leading from an architecture-based system to an equivalent architecture-agnostic one, focusing, in particular, on component-based systems described in BIP. BIP uses connectors for hierarchical composition of components. We study connector internalisation in three steps. 1) We introduce and study the properties of interaction expressions, which represent the combined information about all the effects of an interaction. We show that they are a very powerful tool for specifying and analysing structured interaction. 2) We formalize the connector semantics of BIP by using interaction expressions. The formalization proves to be mathematically rigorous and concise. 3) We introduce the T/B component model and provide a semantics preserving translation of BIP into this model. The translation is compositional that is, it preserves the structure of the source models. The results are illustrated by simple examples. A Java implementation is evaluated on two case studies

Combining type checking with model checking for system verification

Type checking is widely used in mainstream programming languages to detect programming errors at compile time. Model checking is gaining popularity as an automated technique for systematically analyzing behaviors of systems. My research focuses on combining these two software verification techniques synergically into one platform for the creation of correct models for software designs. This thesis describes two modeling languages ATS/PML and ATS/Veri that inherit the advanced type system from an existing programming language ATS, in which both dependent types of Dependent ML style and linear types are supported. A detailed discussion is given for the usage of advanced types to detect modeling errors at the stage of model construction. Going further, various modeling primitives with well-designed types are introduced into my modeling languages to facilitate a synergic combination of type checking with model checking. The semantics of ATS/PML is designed to be directly rooted in a well-known modeling language PROMELA. Rules for translation from ATS/PML to PROMELA are designed and a compiler is developed accordingly so that the SPIN model checker can be readily employed to perform checking on models constructed in ATS/PML. ATS/Veri is designed to be a modeling language, which allows a programmer to construct models for real-world multi-threaded software applications in the same way as writing a functional program with support for synchronization, communication, and scheduling among threads. Semantics of ATS/Veri is formally defined for the development of corresponding model checkers and a compiler is built to translate ATS/Veri into CSP# and exploit the state-of-the-art verification platform PAT for model checking ATS/Veri models. The correctness of such a transformational approach is illustrated based on the semantics of ATS/Veri and CSP#. In summary, the primary contribution of this thesis lies in the creation of a family of modeling languages with highly expressive types for modeling concurrent software systems as well as the related platform supporting verification via model checking. As such, we can combine type checking and model checking synergically to ensure software correctness with high confidence

Reprodutibilidade e reuso de experimentos em eScience : workflows, ontologias e scripts

Orientadores: Claudia Maria Bauzer Medeiros, Yolanda GilTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Scripts e Sistemas Gerenciadores de Workflows Científicos (SGWfC) são abordagens comumente utilizadas para automatizar o fluxo de processos e análise de dados em experimentos científicos computacionais. Apesar de amplamente usados em diversas disciplinas, scripts são difíceis de entender, adaptar, reusar e reproduzir. Por esta razão, diversas soluções têm sido propostas para auxiliar na reprodutibilidade de experimentos que utilizam ambientes baseados em scripts. Porém, estas soluções não permitem a documentação completa do experimento, nem ajudam quando outros cientistas querem reusar apenas parte do código do script. SGWfCs, por outro lado, ajudam na documentação e reuso através do suporte aos cientistas durante a modelagem e execução dos seus experimentos, que são especificados e executados como componentes interconectados (reutilizáveis) de workflows. Enquanto workflows são melhores que scripts para entendimento e reuso dos experimentos, eles também exigem documentação adicional. Durante a modelagem de um experimento, cientistas frequentemente criam variantes de workflows, e.g., mudando componentes do workflow. Reuso e reprodutibilidade exigem o entendimento e rastreamento da proveniência das variantes, uma tarefa que consome muito tempo. Esta tese tem como objetivo auxiliar na reprodutibilidade e reuso de experimentos computacionais. Para superar estes desafios, nós lidamos com dois problemas de pesquisas: (1) entendimento de um experimento computacional, e (2) extensão de um experimento computacional. Nosso trabalho para resolver estes problemas nos direcionou na escolha de workflows e ontologias como respostas para ambos os problemas. As principais contribuições desta tese são: (i) apresentar os requisitos para a conversão de experimentos baseados em scripts em experimentos reprodutíveis; (ii) propor uma metodologia que guia o cientista durante o processo de conversão de experimentos baseados em scripts em workflow research objects reprodutíveis. (iii) projetar e implementar funcionalidades para avaliação da qualidade de experimentos computacionais; (iv) projetar e implementar o W2Share, um arcabouço para auxiliar a metodologia de conversão, que explora ferramentas e padrões que foram desenvolvidos pela comunidade científica para promover o reuso e reprodutibilidade; (v) projetar e implementar o OntoSoft-VFF, um arcabouço para captura de informação sobre software e componentes de workflow para auxiliar cientistas a gerenciarem a exploração e evolução de workflows. Nosso trabalho é apresentado via casos de uso em Dinâmica Molecular, Bioinformática e Previsão do TempoAbstract: Scripts and Scientific Workflow Management Systems (SWfMSs) are common approaches that have been used to automate the execution flow of processes and data analysis in scientific (computational) experiments. Although widely used in many disciplines, scripts are hard to understand, adapt, reuse, and reproduce. For this reason, several solutions have been proposed to aid experiment reproducibility for script-based environments. However, they neither allow to fully document the experiment nor do they help when third parties want to reuse just part of the code. SWfMSs, on the other hand, help documentation and reuse by supporting scientists in the design and execution of their experiments, which are specified and run as interconnected (reusable) workflow components (a.k.a. building blocks). While workflows are better than scripts for understandability and reuse, they still require additional documentation. During experiment design, scientists frequently create workflow variants, e.g., by changing workflow components. Reuse and reproducibility require understanding and tracking variant provenance, a time-consuming task. This thesis aims to support reproducibility and reuse of computational experiments. To meet these challenges, we address two research problems: (1) understanding a computational experiment, and (2) extending a computational experiment. Our work towards solving these problems led us to choose workflows and ontologies to answer both problems. The main contributions of this thesis are thus: (i) to present the requirements for the conversion of script to reproducible research; (ii) to propose a methodology that guides the scientists through the process of conversion of script-based experiments into reproducible workflow research objects; (iii) to design and implement features for quality assessment of computational experiments; (iv) to design and implement W2Share, a framework to support the conversion methodology, which exploits tools and standards that have been developed by the scientific community to promote reuse and reproducibility; (v) to design and implement OntoSoft-VFF, a framework for capturing information about software and workflow components to support scientists manage workflow exploration and evolution. Our work is showcased via use cases in Molecular Dynamics, Bioinformatics and Weather ForecastingDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação2013/08293-7, 2014/23861-4, 2017/03570-3FAPES

Introduction in IND and recursive partitioning

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, and lists the manual pages for the routines and instructions on installation

Introduction to IND and recursive partitioning, version 1.0

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, lists the manual pages for the routines, and instructions on installation

Binary Disassembly Block Coverage by Symbolic Execution vs. Recursive Descent

This research determines how appropriate symbolic execution is (given its current implementation) for binary analysis by measuring how much of an executable symbolic execution allows an analyst to reason about. Using the S2E Selective Symbolic Execution Engine with a built-in constraint solver (KLEE), this research measures the effectiveness of S2E on a sample of 27 Debian Linux binaries as compared to a traditional static disassembly tool, IDA Pro. Disassembly code coverage and path exploration is used as a metric for determining success. This research also explores the effectiveness of symbolic execution on packed or obfuscated samples of the same binaries to generate a model-based evaluation of success for techniques commonly employed by malware. Obfuscated results were much higher than expected, which lead to the discovery that S2E was not actually handling the multiple executable memory regions present in unpacker runtime code. Three recommendations are made to address the shortcomings of S2E and allow it to process obfuscated samples correctly

Learning Human Behavior From Observation For Gaming Applications

The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. One focus has turned to adding more humanlike characteristics into computer game agents. Machine learning techniques are being used scarcely in games, although they do offer powerful means for creating humanlike behaviors in agents. The first person shooter (FPS), Quake 2, is an open source game that offers a multi-agent environment to create game agents (bots) in. This work attempts to combine neural networks with a modeling paradigm known as context based reasoning (CxBR) to create a contextual game observation (CONGO) system that produces Quake 2 agents that behave as a human player trains them to act. A default level of intelligence is instilled into the bots through contextual scripts to prevent the bot from being trained to be completely useless. The results show that the humanness and entertainment value as compared to a traditional scripted bot have improved, although, CONGO bots usually ranked only slightly above a novice skill level. Overall, CONGO is a technique that offers the gaming community a mode of game play that has promising entertainment value