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Browsing by Author "Boldery, Dave B."

Now showing 1 - 4 of 4
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    Documentation Production under Next Generation Technologies
    Nance, Richard E.; Keller, Benjamin J.; Boldery, Dave B. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1989)
    This paper describes the development of the Abstraction Refinement Model as a basis for linking the development and maintenance tasks in software systems. Documentation is critical in both efforts, and the reliance on development documentation during maintenance is characterized by the model and through a characterization of the development documentation requirement stipulated under DoD-STD-2167A. The Abstraction Refinement Model enables a coherent characterization of the reverse engineering requirements generally caused by a faulty or inadequately documented development process. Within the context of the model, the Automated Document Design System (ADDS) is characterized, and the system is evaluated with regard to its current capabilities versus future potential. A set of recommendations regarding ADDS concludes the report.
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    Documentation Production under Next Generation Technologies
    Nance, Richard E.; Keller, Benjamin J.; Boldery, Dave B. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1989)
    This report describes the development of the Abstraction Refinement Model as a basis for linking the development and maintenance tasks in software systems. Documentation is critical in both efforts, and the reliance on development documentation during maintenance is characterized by the model and through a characterization of the development documentation requirement stipulated under DoD-STD2167A. The Abstraction Refinement Model enables a coherent characterization of the reverse engineering requirements generally caused by a faulty or inadequately documented development process. Within the context of the model, the Automated Documentation Design System (ADDS) is characterized, and the system is evaluated with regard to its current capabilities versus future potential. A set of recommendations regarding ADDS concludes the report.
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    The Elevation Pyramid
    Shaffer, Clifford A.; Boldery, Dave B. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1990)
    The elevation pyramid, a pyramid-based representation for storing gridded elevation data, is described. Associated with the root of the pyramid is the corresponding grid's minimum elevation and range. The elevation value for a specified grid pixel is calculated by transversing a path from the pyramid root to the corresponding leaf node. As the transversal proceeds, the minimum and range values are refined by interpreting the codes stored at each node along the path. At the leaf level, the final minimum value equals the associated elevation value. We present results from experiments using 2,3 and 4 bit code words. For the two bit code, since the total number of nodes in the pyramid is 4/3 the number of pixels required for the bottom level of the pyramid, the amortized storage cost is less than 3 bits per pixel, regardless of vertical resolution. This corresponds to a 5:1 compression rate for a 16 bit gridded elevation data. The elevation pyramid is most appropriate for efficient secondary storage archival, such as on a CD-ROM. It allows efficient retrieval of complete elevation data from any sub-region, at multiple scales, within the entire elevation database. This is a lossless encoding when the difference between sibling pixels is not "too great." Rapid changes in elevation between adjacent pixels will be smoothed. Most data sets contain relatively few pixels that cannot be encoded by the techniques studied. Such pixels can be efficiently stored in an auxiliary table if perfec reconstruction is required. "Elevation" pyramids can be used to store any 2D surface or 3D density data.
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    The elevation pyramid: a method for compressing elevation data
    Boldery, Dave B. (Virginia Tech, 1990-02-19)
    A quadtree-like representation for storing gridded elevation data is described. In its simplest form, the data structure is a pyramid with each node containing a two bit code. The root of the pyramid has associated with it the minimum elevation for the grid and the range (the greatest power of 2 less than or equal to the difference between the minimum and maximum elevation values). Any specified elevation value is determined by traversing a path from the root to a leaf node. As the traversal proceeds, the minimum and range values are refined by interpreting the codes stored at each node along the path. At the leaf level, the final minimum value equals the associated elevation value. Since the total number of nodes in the pyramid is 4/3 the number of elevation grid cells, the amortized storage cost is less than 3 bits per grid cell. When the difference between elevation values is not "too great", this basic representation is quite effective. For data where greater elevation differences occur between neighboring cells, this basic method is modified to improve the representation, but at a cost in storage. Our method is most appropriate for efficient secondary storage archival, such as on CD-ROM. It also allows efficient retrieval of complete elevation data from any subregion, at multiple scales, within the entire elevation database.