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This operation is basic to every text processing system, and there is obvious interest in finding an efficient algorithm for this task. A specific feature of this problem is the presence of two arrays and a necessity to scan them simultaneously in such a way that the coordination of the two indices used to scan the arrays is determined by the data. e. a multibranch version of the WHILE loop. This fundamental and powerful control structure is described in Appendix C. We consider three string search algorithms: straight string search; an optimization of the straight search due to Knuth, Morris and Pratt,; and, finally, the algorithm of Boyer and Moor based on a revision of the basic idea of the straight search, which proves to be the most efficient of the three.

This requires an intermediate buffer in the form of a first-in-last-out queue (stack). NumberToChars *) REPEAT d[i] := x MOD 10; x := x DIV 10; INC(i) UNTIL x = 0; REPEAT DEC(i); Write(CHR(d[i] + ORD("0"))) UNTIL i = 0 Note. A consistent substitution of the constant 10 in these algorithms by a positive integer B will yield number conversion routines to and from representations with base B. A frequently used case is B = 16 (hexadecimal), because the involved multiplications and divisions can be implemented by simple shifts of the binary numbers.

In contrast to the first solution, this algorithm — like linear search — finds the matching element with the least index. 3 Table Search A search through an array is sometimes also called a table search, particularly if the keys are themselves structured objects, such as arrays of numbers or characters. The latter is a frequently encountered case; the character arrays are called strings or words. Let us define a type String as String = ARRAY M OF CHAR and let order on strings x and y be defined as follows: (x = y) ≡ (Aj: 0 ≤ j < M : xj = yj) (x < y) ≡ Ei: 0 ≤ i < N : ((Aj: 0 ≤ j < i : xj = yj) & (xi < yi)) In order to establish a match, we evidently must find all characters of the comparands to be equal.

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