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 become well-known as being one of the strongest paradigms for modeling details structures. The time period "information structures" is used right here in a truly normal context to indicate database structures, software program improvement structures, wisdom­ base platforms, evidence help structures, disbursed structures and reactive platforms. essentially the most vigorously researched issues universal to all details structures is "formal modeling". a chic high-level abstraction appropriate to either software area and process area options will constantly result in a procedure layout from "outside in"; that's, the aggregation of principles is round real-life gadgets 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 procedure improvement, can result in a proper reasoning at the meant houses, hence revealing process flaws that will rather be came across 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, dispensed, real-time, and reactive platforms. ,The suggestion 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 definitely made very important contributions to formalisms in keeping with good judgment and items. it really is valuable bringing jointly the tips built by way of the 2 groups in isolation, and targeting integrating their universal strengths.

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Extra 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

Example text

Q E 1; do Temp:= Pnf*({x*}) 49 If Temp = 0 then E' := E' u {P-+Q} else If Temp C P then E':= E' u {(P - Temp)-+Temp} endIf endIf endFor Step (3) Generate the rules from the filter C'(a) For each node N = (X,X',X") E C'(a) do If X i- 0 and X" i- 0 and X' i- X" then E':= E' u {X"-+(X' - X")} endIf endFor return(E') end Complexity analysis The first and last steps take 0(11011) time. Step 2 needs at most II~II iterations, and more precisely 111'11 iterations because there are at most as many existence rules as descriptors.

This was the second problem on our list in the previous section, and hence we will call it problem P2. Algorithm P2-SUM Given an extended relation r = {t1@z1,t2@Z2, •.. ) Theorem 3: Algorithm P2-SUM correctly calculates the expected value of sumA(r). Proof: The expected value of sumA(r), by definition, is L sumA(rOO(Q» x P(Q) (8) Q~S where S is the set of information sources, rOO is the function represented by r (hence rOO(Q) is the regular relation in the alternate world of r corresponding to Q ~ S, and P(Q) is the probability associated with Q (and with r*(Q».

X Dn x Dr. We usually write t@u to denote a tuple on the extended scheme 26 R, where t is the value of the tuple corresponding to the regular attributes A 1 , ••• , An, and u is the value of the tuple corresponding to the source attribute I. We call t a pure tuple, and u is the source vector corresponding to t. A relation instance (relation for short) r on the scheme R is a set of tuples on R. A source vector u for a tuple t@u identifies sources that contribute to t. Intuitively, t is valid if all sources having a +1 entry in u are correct, and all those having a -1 entry in u are incorrect.

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