Download Formal Methods in Databases and Software Engineering: by Anthony J. Bonner, Michael Kifer (auth.), V. S. Alagar PhD, PDF

By Anthony J. Bonner, Michael Kifer (auth.), V. S. Alagar PhD, Laks V. S. Lakshmanan PhD, F. Sadri PhD (eds.)

Logic and object-orientation have emerge as well-known as being one of the strongest paradigms for modeling info structures. The time period "information platforms" is used right here in a truly normal context to indicate database platforms, software program improvement structures, wisdom­ base platforms, facts aid platforms, disbursed platforms and reactive structures. essentially the most vigorously researched themes universal to all details structures is "formal modeling". a sublime high-level abstraction appropriate to either software area and procedure area techniques will continually result in a process layout from "outside in"; that's, the aggregation of rules is round real-life items approximately which the approach is to be designed. Formal equipment \yhen utilized with this view in brain, in particular in the course of early levels of process improvement, may end up in a proper reasoning at the meant homes, therefore revealing procedure flaws that would rather be chanced on a lot later. good judgment in numerous kinds and semantics is getting used to version databases and their transactions; it's also used to specify concurrent, allotted, real-time, and reactive structures. ,The concept of "object" is valuable to the modeling of item­ orientated databases, in addition to object-oriented layout and courses in software program engineering. either database and software program engineering groups have certainly made vital contributions to formalisms in line with common sense and items. it's priceless bringing jointly the guidelines constructed by way of the 2 groups in isolation, and targeting integrating their universal strengths.

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Additional info for Formal Methods in Databases and Software Engineering: Proceedings of the Workshop on Formal Methods in Databases and Software Engineering, Montreal, Canada, 15–16 May 1992

Sample text

Four cases can be considered: (i) implication rules for descriptors (IRDs) in which both P and Q belong to 'P(V) 44 (ii) implication rules for objects (IROs) in which both P and Q belong to P(O) (iii) discriminant rules for objects (DROs) where P E P(V) and Q E P(O) (iv) discriminant rules for descriptors (DRDs) where P E P(O) and Q E P(V). For space limitations we shall only give definitions for implication rules and show how to determine them. 1 Implication rules We define implication rules (IR) as ones such that P and Q are both subsets of either 0 or V.

The system RX [2] is one of the early works in knowledge discovery. It uses artificial intelligence techniques to guide the statistical analysis of medical collected data. Borgida and Williamson [3] uses machine learning techniques to detect and accommodate exceptional information that may occur in a database. The IXL (Induction on Extremely Large databases) system [16,24] combines machine learning and statistics to extract patterns and rules from large databases. Cai et al [4] presents an induction algorithm which extracts classification and characterization rules from relational databases by performing a step by step generalization on individual attributes.

Michie, editors, Machine Intelligence, volume 4. Edinburgh University Press, 1974. Reprinted in Readings in Artificial Intelligence, 1981, Tioga Publ. Co. [13] S. Naqvi anq R. Krishnamurthy. Database updates in logic programming. In ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pages 251-262, March 1988. J. Nilsson. Principles of Artificial Intelligence. Tioga Publ. , Paolo Alto, CA, 1980. [15] R. Reiter. Formalizing database evolution in the situation calculus. In Con/.

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