Master's Papers and Projects

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Browsing Master's Papers and Projects by Author "Abrams, Marc"

Now showing 1 - 3 of 3
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    CATY: an ASN.1-C++ translator in support of distributed object-oriented applications
    Long, Wendy (Virginia Tech, 1994-04-15)
    When heterogeneous computers exchange data over a network, they must agree on a common interpretation of the data. The OSI suite of protocols includes a standard notation, Abstract Syntax Notation One (ASN.1), for describing the structure ("abstract syntax") of data. Previous work has shown that C++ is a good language for work with layered network architectures and specifically with ASN.1: the inheritance and polymorphism features of C++ are nicely suited for work with layered protocols, which can be seen and used in object-oriented terms; a C++ class hierarchy, designed to capture the language concepts of ASN.1, successfully separates the abstract syntax (or application level) from the encoding used during transfer (the "transfer syntax" at presentation level); and the class construct and scoping rules of C++ and the design of the class hierarchy much better preserve the structure and content of ASN.1 than do past attempts with C. This report presents CATV (Class-oriented ASN.1 Translator, Yacc-based), a translator from ASN.1 to a corresponding C++ abstract syntax class hierarchy. It is shown in this report that the translations produced by CATV are preferable to those produced by other translators based on the following criteria: preservation of names and types, consistent access to elements, support of modularity and subtypes, resolution of forward references, flexibility of encoding, and generality of use. Furthermore, it is shown that CATV has better throughput than PEPSY, an ASN.1 to C translator from ISODE.
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    A data analysis software tool for the visual simulation environment
    Tuglu, Ali (Virginia Tech, 1995)
    The objective of the research described herein is to develop a prototype data analysis software tool integrated within the Visual Simulation Environment (VSE). The VSE is an integrated set of software tools that provide computer-aided assistance throughout the development life cycle of visual discrete-event simulation models. Simulation input and output data analyses are commonly needed in simulation studies. A software tool performing such data analysis is required within the VSE to provide automated support for input data modeling and output data analysis phases of the model development life cycle. The VSE DataAnalyzer provides general statistics. histograms, confidence intervals, and randomness tests for the data sets. It can also create C modules for generating random variates based on a collected set of data. Furthermore, the VSE DataAnalyzer possesses the basic file management, editing, printing, and formatting functionalities as well as a complete help feature. It has been used in a senior-level Simulation and Modeling course, and the feedback from the students has been positive. New functionalities can easily be added to the VSE DataAnalyzer due to its object-oriented software structure. The VSE DataAnalyzer is yet another software tool created to provide more comprehensive automated support throughout the visual simulation model development.
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    The development of a CHAID-based model for CHITRA93
    Cadiz, Horacio T. (Virginia Tech, 1994-02-14)
    The complexity of the behavior of parallel and distributed programs is the major reason for the difficulties in the analysis and diagnosis of their performance. Complex systems such as these have frequently been studied using models as abstractions of such systems. By capturing only the details of the system which are considered essential, a model is a replica of the complex system which is simpler and easier to understand than the real system. CHITRA92, the second generation of the performance analysis tool CHITRA, builds a continuous time semi-Markov chain to model program behavior. However, this model is limited to representing relationships between states which are only immediate predecessors or successors of each other. This project introduces and implements a new empirical model of the behavior of software programs which is able to represent dependencies between nonsequential program states. The implementation combines deterministic and probabilistic modeling and is based on the Chi Automatic Interaction Detection (CHAID) statistical technique designed for investigating categorical data. The empirical model, constructed by analyzing an ensemble of program execution sequences, is stochastic and non-Markovian in the form of an N -step Transition Matrix. The algorithm is integrated as one of the modeling subsystems of CHITRA93, the third generation of CHITRA.