Many legacy applications perform essential business functions; yet, due to a number of factors, modifying such applications in order to accommodate new business requirements can be troublesome. Such factors include: t...
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Many legacy applications perform essential business functions; yet, due to a number of factors, modifying such applications in order to accommodate new business requirements can be troublesome. Such factors include: the volume of code in a typical application, logical code structure that has deterio- rated as updates have accumulated over time, functional redundancy, code structure that reects the dated technology on which it was built, and scarce technical skills. We have argued that the consequent difculty of understanding and modify- ing legacy code can be ameliorated through the use of logical data models. In the Mastery project, we are developing both algorithms for extracting logical data models from legacy COBOL applications and software tools that use the generated models to query and transform the code from which the models are derived.
The problem of failure recovery for a distributed database system is more complex than that for a centrally controlled database system. If all the sites in a distributed system whose data are updated by a transaction...
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The problem of failure recovery for a distributed database system is more complex than that for a centrally controlled database system. If all the sites in a distributed system whose data are updated by a transaction are not up and available at the time of transaction execution, either the updates must be cancelled for all sites or the updates for the temporarily inaccessible site must be saved for later delivery. A resilient control scheme for a distributed database system is described. The notion of a resilient system holds that a transaction cannot be executed if some true copies required by the transaction are not available within the partition where the transaction is executing. System objectives include the elimination of lost transaction updates, where the user receives an acknowledgment but updates are not posted, and lost transaction output, where updates are posted but the user receives no acknowledgment. Figures.
Adata encoding is a formal counterpart of the “translation of a logical data structure into a physical storage structure". In this paper, both kinds of structures are represented by graphs; and an encoding is a ...
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Adata encoding is a formal counterpart of the “translation of a logical data structure into a physical storage structure". In this paper, both kinds of structures are represented by graphs; and an encoding is a type of embedding of the guest (logical structure) graph in the host (physical structure) graph. Thecost of an encoding is the average amount that the edges of the guest graph are stretched as they are replaced by paths in the host graph via the encoding; this “average” is weighted by an assignment of probabilities to the edges of the guest graph (called ausage pattern) that weights the edges according to their anticipated frequencies of *** paper continues the study begun in [13] of encodings of data structures in the leaves of complete trees. The major thrust of the paper is to show that tree-hosts do not accommodate tree-like guests as congenially as they do array-like guests. Specifically, we study two encodings of tree-guests in tree-hosts, and three usage patterns for the guests. One of these usage patterns can be accommodated with cost independent of the size of the guest by one of the encodings but not by the other; the second usage pattern engenders the complementary situation; and the third usage pattern resists size-independent cost not only on the part of the two encodings studied here but also on the part ofany encoding of trees into trees. We do, however, find a third encoding of trees in trees whose cost relative to this intransigent usage pattern is exponentially smaller than the costs of our two encodings and is, in fact, optimal in rate of *** by the demonstrated weaknesses of trees as hosts in data encodings, we introduce a new tree-like storage structure called adree; and we show that drees are quite congenial hosts for array-like and tree-like (and dree-like) *** the paper, demonstrations of size-independence in the costs of encodings are accompanied by proofs of the (asympotic) near-optimality of th
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