Functions, types and expressions programming languages and their operational semantics compilation partial evaluation of a flow chart languages partial evaluation of a first-order functional languages the view from Olympus partial evaluation of the Lambda calculus partial evaluation of prolog aspects of Similix - a partial evaluator for a subset of scheme partial evaluation of C applications of partial evaluation termination of partial evaluation program analysis more general program transformation guide to the literature the self-applicable scheme specializer.

Partial evaluation and automatic program generation

ly, this program guesses nondeterministically the correct permutation via permutation(Xs,Ys), and ordered checks that the permutation is actually ordered. Operationally, the behavior is as follows. A query involving sort is reduced to a query involving permutation and ordered. A failure-driven loop ensues. A permutation of the list is generated by permutation and tested by ordered. If the permuted list is not ordered, the execution backtracks to the permutation goal, which generates another permutation to be tested. Eventually an ordered permutation is generated and the computation terminates. Permutation sort is a highly inefficient sorting algorithm, requiring time super-exponential in the size of the list to be sorted. Pushing the tester into the generator, however, leads to a reasonable algorithm. The generator for permutation sort, permutation, selects an arbitrary element and recursively permutes the rest of the list. The tester, ordered, verifies that the first two elements of the permutation are in order, then recursively checks the rest. If we view the combined recursive permutation and ordered goals as a recursive sorting process, we have the basis for insertion sort, Program 3.21. To sort a list, sort the tail of the list and insert the head of the list into its correct place in the order. The arbitrary selection of an element has been replaced by choosing the first element. Another example of the advantage of intertwining generating and testing can be seen with programs solving the N queens problem. The N queens problem requires the placement of N pieces on an Nby-N rectangular board so that no two pieces are on the same line: horizontal, vertical, or diagonal. The original formulation called for 8 queens to be placed on a chessboard, and the criterion of not being on the same line corresponds to two queens not attacking each other under the rules of chess. Hence the problem's name. 253 Nondeterministic Programming

The art of Prolog

Breakfast has been labeled the most important meal of the day, but are there data to support this claim? We summarized the results of 47 studies examining the association of breakfast consumption with nutritional adequacy (nine studies), body weight (16 studies), and academic performance (22 studies) in children and adolescents. Breakfast skipping is highly prevalent in the United States and Europe (10% to 30%), depending on age group, population, and definition. Although the quality of breakfast was variable within and between studies, children who reported eating breakfast on a consistent basis tended to have superior nutritional profiles than their breakfast-skipping peers. Breakfast eaters generally consumed more daily calories yet were less likely to be overweight, although not all studies associated breakfast skipping with overweight. Evidence suggests that breakfast consumption may improve cognitive function related to memory, test grades, and school attendance. Breakfast as part of a healthful diet and lifestyle can positively impact children's health and well-being. Parents should be encouraged to provide breakfast for their children or explore the availability of a school breakfast program. We advocate consumption of a healthful breakfast on a daily basis consisting of a variety of foods, especially high-fiber and nutrient-rich whole grains, fruits, and dairy products.

Breakfast Habits, Nutritional Status, Body Weight, and Academic Performance in Children and Adolescents

http://user.it.uu.se/~jarst116/slides/week4.pdf

Graph-Based Algorithms for Boolean Function Manipulation

interpretation is a theory of semantics approximation that is used for the construction of semantic-based program analysis algorithms (sometimes called “data flow analysis”), the comparison of formal semantics (e.g., construction of a denotational semantics from an operational one), design of proof methods, etc.

Automatic program analysers are used for determining statistically conservative approximations of dynamic properties of programs. Such properties of the run-time behavior of programs are useful for debugging (e.g., type inference), code optimization (e.g., compile-time garbage collection, useless occur-check elimination), program transformation (e.g., partial evaluation, parallelization), and even program correctness proofs (e.g., termination proof).

After a few simple introductory examples, we recall the classical framework for abstract interpretation of programs. Starting from a ground operational semantics formalized as a transition system, classes of program properties are first encapsulated in collecting semantics expressed as fixpoints on partial orders representing concrete program properties. We consider invariance properties characterizing descendants of the initial states (corresponding to top/down or forward analyses), ascendant states of the final states (corresponding to bottom/up or backward analyses) as well as a combination of the two. Then we choose specific approximate abstract properties to be gathered about program behaviors and express them as elements of a poset of abstract properties. The correspondence between concrete and abstract properties is established by a concretization and abstraction function that is a Galois connection formalizing the loss of information. We can then constructively derive the abstract program properties from the collecting semantics by a formal computation leading to a fixpoint expression in terms of abstract operators on the domain of abstract properties. The design of the abstract interpreter then involves the choice of a chaotic iteration strategy to solve this abstract fixpoint equation. We insist on the compositional design of this abstract interpreter, which is formalized by a series of propositions for designing Galois connections (such as Moore families, decomposition by partitioning, reduced product, down-set completion, etc.). Then we recall the convergence acceleration methods using widening and narrowing allowing for the use of very expressive infinite domains of abstract properties.

We show that this classical formal framework can be applied in extenso to logic programs. For simplicity, we use a variant of SLD-resolution as the ground operational semantics. The first example is groundness analysis, which is a variant of Mellish mode analysis. It is extended to a combination of top/down and bottom/up analyses. The second example is the derivation of constraints among argument sizes, which involves an infinite abstract domain requiring the use of convergence accelaration methods. We end up with a short thematic guide to the literature on abstract interpretation of logic programs.

Abstract interpretation and application to logic programs

In this tutorial the specialisation of declarative logic programs is presented. The main correctness results are given, and the outline of a basic algorithm for partial evaluation of a logic program with respect to a goal. The practical considerations of gaining efficiency (and not losing any) are discussed. A renaming scheme for performing structure specialisation is then described, and illustrated on a well-known string matching example. The basic algorithm is enhanced by incorporating abstract interpretation. A two-phase specialisation is then described and illustrated, in which partial evaluation is followed by the detection and removal of useless clauses. This is shown for the specialisation of a proof procedure for first order logic. The specialisation of meta programs is very important in logic programming, and the ground representation for object programs has to be handled. Some techniques for doing this are described. Comparisons are made in the tutorial to similar work in other programming languages, and the similarities and differences between them and logic program specialisation is discussed.

Tutorial on specialisation of logic programs

Breakfast cereal and caffeinated coffee: Effects on working memory, attention, mood and cardiovascular function.

A practical procedure for computing a regular approximation of a logic program is given. Regular approximations are useful in a variety of tasks in debugging, program specialisation and compile-time optimisation. The algorithm shown here incorporates optimisations taken from deductive database fixpoint algorithms and efficient bottom-up abstract interpretation techniques. Frameworks for defining regular approximations have been put forward in the past, but the emphasis has usually been on theoretical aspects. Our results contribute mainly to the development of effective analysis tools that can be applied to large programs. Precision of the approximation can be greatly improved by applying query-answer transformations to a program and a goal, thus capturing some argument dependency information. A novel technique is to use transformations based on computation rules other than left-to-right to improve precision further. We give performance results for our procedure on a range of programs.

/pdf/fast-and-precise-regular-approximations-of-logic-programs-1lmw4k8gj2.pdf

Fast and precise regular approximations of logic programs

An experiment was carried out to examine the effects of 40 mg of caffeine given in different drinks (coffee, water, tea, cola) on mood and performance. One hundred and forty-four volunteers were randomly assigned to one of the groups formed by combining the caffeine/placebo and drinks conditions. Following a baseline session measuring mood and different aspects of performance, the volunteers were given their drink and then carried out another test session 1 h later. Administration of the caffeine/placebo was double-blind. The results showed that those given caffeine reported greater alertness and anxiety at the end of the test session, as well as improved performance on choice reaction time tasks involving focused attention and categoric search, a semantic memory task and a delayed recognition memory task. The effect of the caffeine was not modified by the nature of the drink in which it was given. Overall, these results show that a dose of caffeine typical of the level found in commercial products can improve alertness and performance efficiency.

Effects of a low dose of caffeine given in different drinks on mood and performance

In this paper a method is proposed for carrying out analysis of imperative programs. We achieve this by writing down the language semantics as a declarative program (a constraint logic program, in the approach shown here). We propose an effective style of writing operational semantics suitable for analysis which we call one-state small-step semantics. Through controlled partial evaluation we are able to generate residual programs where the relationship between imperative statements and predicates is straightforward. Then we use a static analyser for constraint logic programs on the residual program. The analysis results are interpreted through program points associating predicates in the partially evaluated interpreter to statements in its corresponding imperative program. We used an analyser that allows us to determine linear equality, inequality and disequality relations among the variables of a program without user-provided inductive assertions or human interaction. The proposed method intends to serve as a framework for the analysis of programs in any imperative language. The tools required are a partial evaluator and a static analyser for the declarative language.

John P. Gallagher

Papers

Tutorial on specialisation of logic programs

Breakfast cereal and caffeinated coffee: Effects on working memory, attention, mood and cardiovascular function.

Fast and precise regular approximations of logic programs

Effects of a low dose of caffeine given in different drinks on mood and performance

Analysis of Imperative Programs through Analysis of Constraint Logic Programs