New PDF release: Advances in Computers, Vol. 15

By Morris Rubinoff, Marshall C. Yovits

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Additional info for Advances in Computers, Vol. 15

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F2. 20. Programming knowledge for program synthesis. We will again return to our canonical example to illustrate this method. In this case, the input specihation will be I: A ( i ) is an integer for i= 1, 2, 3, . . , N , and N > 0. The output specification will be G: ~ ~(i) =SUM. ~ , TheAproblem is to find B such that I { B j G and after some searching the system will find (hopefully) the goal reduction tree of Fig. 21. Each subgoal is found using rules or transformations available to the system and the subgoals at the bottom of the tree are achieved using frame information and/or the theorem prover.

17. Looping program associated with the inductive argument (from Manna and Wddinger, 1971). and looping constructions can be built from proofs of theorems. A combination of these abilities leads to a totally general programming ability. Some of the original papers describe the synthesis of complicated programs that involve all of these constructions. The next section will describe a different type of formalism for program synthesis, which uses formal logic techniques. 18. The column sum routine.

11) Find a program that executes each required sequence of operations Si when given its associated input Xi. 1. Further suppose that it is known that in these instructions op 1always refers to a location in X and op 2 to a location in Y. Then step I would start looking for the desired sequence S of instructions that convert X = ( 9 4 7) to Y = (20). Step I might actually begin enumerating the set of all possible such sequences : start, halt start, move X ( l ) Y(1), halt start, move X (2) Y (1), halt start, moveX(1) Y(1), + X(2) Y(1), + X(3) Y(1), halt The last such sequence given does successfully convert the example X to Y completing Step I.

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