H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....computation trees, and as a consequence, it is often the case that we cannot reduce the nondeterminism of the programs. This weakness of partial deduction is demonstrated in Section 3.3 where we revisit the familiar problem of looking for occurrences of a pattern in a string. It has been shown in [11, 13, 15] that by partial deduction of a string matching program, we may derive a deterministic nite automaton (DFA, for short) similarly to what is done by the Knuth Morris Pratt algorithm [21] However, in [11, 13, 15] the string matching program to which partial deduction is applied, is deterministic. ....

....problem of looking for occurrences of a pattern in a string. It has been shown in [11, 13, 15] that by partial deduction of a string matching program, we may derive a deterministic nite automaton (DFA, for short) similarly to what is done by the Knuth Morris Pratt algorithm [21] However, in [11, 13, 15] the string matching program to which partial deduction is applied, is deterministic. We show that by applying partial deduction to a nondeterministic version of the matching program, one cannot derive a specialized program which is deterministic, and thus, one cannot get a program which ....

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H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.

....specialized pattern matcher for a given pattern. In this example we de ne a general matching relation between strings which is expressed as a constraint logic program. Our derivation generalizes the derivations of the Knuth Morris Pratt matcher [19] which were presented, among others, in [10 12, 15, 23, 24]. As in the case of that matcher, we derive a program which behaves like a deterministic nite automaton with transitions labelled by constraints, rather than symbols of the strings. We improve over the derivations of specialized pattern matchers presented in [10 12, 15, 24] because we start from ....

....among others, in [10 12, 15, 23, 24] As in the case of that matcher, we derive a program which behaves like a deterministic nite automaton with transitions labelled by constraints, rather than symbols of the strings. We improve over the derivations of specialized pattern matchers presented in [10 12, 15, 24] because we start from a nondeterministic speci cation of the matcher, while in those papers the initial programs are deterministic. As already mentioned, the improvement over [23] is that we now deal with a general pattern matcher presented as a constraint logic program. In our example we de ....

H. Fujita. An algorithm for partial evaluation with constraints. Tech. Memo. 0367, ICOT, Tokyo, Japan, 1987.

....specialized pattern matcher for a given pattern. In this example we de ne a more general matching relation between strings which is expressed as a constraint logic program. Our derivation generalizes the derivations of the Knuth Morris Pratt matcher which were presented, among others, in [8], 9] 10] 13] 19] 20] As in the case of that matcher, we derive a program which is a deterministic nite automaton with transitions labelled by constraints, rather than symbols of the strings. We improve over the derivations of specialized pattern matchers presented in [8] 9] 10] ....

....among others, in [8] 9] 10] 13] 19] 20] As in the case of that matcher, we derive a program which is a deterministic nite automaton with transitions labelled by constraints, rather than symbols of the strings. We improve over the derivations of specialized pattern matchers presented in [8], 9] 10] 13] 20] because we start from a nondeterministic speci cation of the matcher, while in those papers the initial programs are deterministic. As already mentioned, the improvement over [19] is that we now deal with a general pattern matcher presented as a constraint logic program. ....

H. Fujita. An algorithm for partial evaluation with constraints. Tech. Memo. 0367, ICOT, Tokyo, Japan, 1987.

....trees, and as a consequence, it is often the case that we cannot reduce the nondeterminism of the programs. This weakness of partial evaluation is demonstrated in Section 2.2 where we revisit the familiar problem of looking for occurrences of a pattern in a string. It has been shown in [8, 10, 12] that by partial evaluation of a string matching program, we may derive a deterministic nite automaton, similarly to what is done by the Knuth Morris Pratt algorithm [16] However, in [8, 10, 12] the string matching program to which partial evaluation is applied, is deterministic. We show that by ....

....revisit the familiar problem of looking for occurrences of a pattern in a string. It has been shown in [8, 10, 12] that by partial evaluation of a string matching program, we may derive a deterministic nite automaton, similarly to what is done by the Knuth Morris Pratt algorithm [16] However, in [8, 10, 12] the string matching program to which partial evaluation is applied, is deterministic. We show that by the partial evaluation of a nondeterministic version of the matching program, one cannot derive a specialized program which is deterministic, and thus, one cannot get a program which corresponds ....

[Article contains additional citation context not shown here]

H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.

....a program for searching a pattern in a string and a speci c pattern P , we want to derive a specialized program for searching the pattern P in any given string. A general, deterministic program Match for matching strings in fa; bg is the following one. It is a variant of the ones presented in [73, 74]. match(P; S) match1(P; S; P; S) match1( X;Y; Z) match1( CjPs ] CjSs ] P; S) match1(Ps ; Ss ; P; S) match1( ajPs ] bjSs ] P; CjS] match1(P; S; P; S) match1( bjPs ] ajSs ] P; CjS] match1(P; S; P; S) Suppose that we want to specialize this program Match w.r.t. the goal ....

H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.

....from an abstract interpretation was proposed in [18] The renaming method we used to flatten calls and remove redundant structures has been suggested elsewhere, but to our knowledge our presentation is the most general. Similar renamings have been incorporated into partial evaluators in [15] [7], and recently related ideas were presented in [3] 7.1 Extensions of the Method The transformation is very generally applicable because it is simple. In general the presence of cuts, non logical built ins and side effects hampers its extension by more powerful transformation methods. However ....

Fujita, H.; An Algorithm for Partial Evaluation with Constraints; ICOT Technical Memorandum, TM-0484, August 1987.

....Benkerimi and Lloyd, 1990; Bruynooghe et al. 1992; Gallagher, 1991; Martens et al. 1992; Gallagher, 1993 ] Some of them require generalization steps and the use of abstract interpretations. Other techniques for partial evaluation and program specialization are based on the unfold fold rules [ Fujita, 1987; Bossi et al. 1990; Sahlin, 1993; Bossi and Cocco, 1993; Prestwich, 1993a; Proietti and Pettorossi, 1993 ] By using those techniques, given a program P and a query G, we introduce a new predicate newp defined by the clause D. newp(X 1 ; Xn ) G where X 1 ; Xn are the ....

H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.

....program often gives significant optimisation, especially of space usage. Secondly, a theoretical advantage is that the concept of independence is not needed (as defined in [20] and incorporated in the algorithm in [1] Other partial evaluation systems have included similar renaming methods (e.g. [6], 24] 1] the use of renaming definitions in SP clarifies and standardises the various notions of renaming. 7.4 Results SP has been applied to a number of examples discussed in the literature. A selection of results appears in Appendix A. It appears to perform at least as well on most ....

....be expanded in some cases. Furthermore, SP s results are obtained without departing from the SLDNF framework. The well known example of the Knuth Morris Pratt string matching transformation is handled, for instance, although other researchers have used constraints to process this example [30] [6]. SP makes no attempt to handle cuts, side effects and other non declarative aspects of Prolog, as is done by Mixtus [25] SP is not yet self applicable, since the SP system is not written declaratively. This remains an important goal; an effort will shortly be made to rewrite SP in a declarative ....

Fujita, H.; An Algorithm for Partial Evaluation with Constraints; ICOT Technical Memorandum, TM-0484, August 1987.

.... deduction, and indeed it is possible to derive a program which behaves like the deterministic finite automaton generated by the Knuth MorrisPratt string matching algorithm by applying the standard strategy for partial deduction to a general string matching program like the one of Figure 2(A) [5, 6]. A) B) by standard partial deduction match(P; S) match1(P; S; P; S) match1( X;Y; Z) match1( AjPs] AjSs] P; S) match1(Ps; Ss ; P; S) match1( AjPs] BjSs] P; CjS] A 6= B; match1(P; S; P; S) pd match(S) m1(S) m1( ajS] m2(S) m1( XjS] a 6= X; m1(S) m2( ajS] ....

H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, Tokyo, Japan, 1987.

....some concrete instances of Algorithm 3.24, and briefly discuss their operation on a particularly interesting example. 3. 3 A challenging example Some well known examples from the literature require polyvariance in order to achieve the best results, including the pattern matching programs match ([9]) and contains ( 18] Good results for these can be reproduced in our framework, although global termination is not a significant problem in partial deduction of these programs. In this subsection, we discuss an example for which both polyvariance and global termination are important ....

....methods immediately computing concrete partial deductions, the work in this paper offers a useful setting for providing flexible global control, while ensuring termination. Much of the (early) work in partial evaluation of logic programs, not within the framework established in [23] see e.g. [9], 31] while allowing polyvariance, addresses termination only casually, or relies on user provided annotations. For a recent example of work within the latter strand, see [19] However, approaches aiming at full automation, and relying on online methods, must include an automatic mechanism to ....

H. Fujita. An algorithm for partial evaluation with constraints. Technical Report TR-258, ICOT, Tokyo, Japan, 1987.

....[BjTs] P; XjT] A = B match1(Ps; Ts; P; XjT] match1(P; T; P; T) We do not obtain a KMP algorithm using the unfolding method presented so far because we do not use the information that the test has failed in the elsebranch. This problem can been solved in several ways. For instance in [5], 20] constraints similar to A 6= B are propagated. The SP system presented in [7] derives a KMP algorithm by left propagation of bindings and the execution of ground not s. In this case the non ground negative literals play the role of the constraints and the left propagation of bindings takes ....

H. Fujita. An algorithm for partial evaluation with constraints. Technical Memorandum TM-0367, ICOT, 1987.

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