Abstract. Partial evaluation of logic programs which contain impure predicates poses non-trivial challenges. Impure predicates include those which produce side-effects, raise errors (or exceptions), and those whose truth value varies according to the degree of instantiation of arguments 4. In particular, non-leftmost unfolding steps can produce incorrect results since the independence of the computation rule no longer holds in the presence of impure predicates. Existing proposals allow non-leftmost unfolding steps, but at the cost of accuracy: bindings and failure are not propagated backwards to predicates which are potentially impure. In this work we propose a partial evaluation scheme which substantially reduces the situations in which such backpropagation has to be avoided. With this aim, our partial evaluator takes into account the information about purity of predicates expressed in terms of assertions. This allows achieving some optimizations which are not feasible using existing partial evaluation techniques. We argue that our proposal goes beyond existing ones in that it is a) accurate, since the classification of pure vs impure is done at the level of atoms instead of predicates, b) extensible, as the information about purity can be added to programs using assertions without having to modify the partial evaluator itself, and c) automatic, since (backwards) analysis can be used to automatically infer the required assertions. Our approach has been implemented in the context of CiaoPP, the abstract interpretation-based preprocessor of the Ciao logic programming system. 1

The aim of many program transformers is to improve efficiency while preserving program meaning. Correctness issues have been dealt with extensively. However, very little attention has been paid to formally establish the improvements achieved by these transformers. In this work, we introduce the scheme of a narrowing-driven partial evaluator enhanced with abstract costs. They are "abstract" in the sense that they measure the number of basic operations performed during a computation rather than actual execution times. Thus, we have available a setting in which one can discuss the effects of the program transformer in a precise framework and, moreover, to quantify these effects. Our scheme may serve as a basis to develop speedup analyses and cost-guided transformers. An implementation of the cost-augmented specializer has been undertaken, which demonstrates the practicality of our approach.

Abstract. State of the art analyzers in the Logic Programming (LP) paradigm are nowadays mature and sophisticated. They allow inferring a wide variety of global properties including termination, bounds on resource consumption, etc. The aim of this work is to automatically transfer the power of such analysis tools for LP to the analysis and verification of Java bytecode (jvml). In order to achieve our goal, we rely on well-known techniques for meta-programming and program specialization. More precisely, we propose to partially evaluate a jvml interpreter implemented in LP together with (an LP representation of) a jvml program and then analyze the residual program. Interestingly, at least for the examples we have studied, our approach produces very simple LP representations of the original jvml programs. This can be seen as a decompilation from jvml to high-level LP source. By reasoning about such residual programs, we can automatically prove in the CiaoPP system some non-trivial properties of jvml programs such as termination, run-time error freeness and infer bounds on its resource consumption. We are not aware of any other system which is able to verify such advanced properties of Java bytecode. 1

Reasoning about Java bytecode (JBC) is complicated due to its unstructured control-flow, the use of three-address code combined with the use of an operand stack, etc. Therefore, many static analyzers and model checkers for JBC first convert the code into a higher-level representation. In contrast to traditional decompilation, such representation is often not Java source, but rather some intermediate language which is a good input for the subsequent phases of the tool. Interpretive decompilation consists in partially evaluating an interpreter for the compiled language (in this case JBC) written in a high-level language w.r.t. the code to be decompiled. There have been proofs-of-concept that interpretive decompilation is feasible, but there remain important open issues when it comes to decompile a real language such as JBC. This paper presents, to the best of our knowledge, the first modular scheme to enable interpretive decompilation of a realistic programming language to a high-level representation, namely of JBC to Prolog. We introduce two notions of optimality which together require that decompilation does not generate code more than once for each program point. We demonstrate the impact of our modular approach and optimality issues on a series of realistic benchmarks. Decompilation times and decompiled program sizes are linear with the size of the input bytecode program. This demonstrates empirically the scalability of modular decompilation of JBC by partial evaluation.

. In this paper, we describe a binding-time analysis (BTA) for a statically typed and strongly moded pure logic programming language, in casu Mercury. Binding-time analysis is the key concept in achieving o-line program specialisation: the analysis starts from a description of the program's input available for specialisation, and propagates this information throughout the program, deriving directives for when and how to perform specialisation. 1

We consider the problem of specializing constraint logic programs w.r.t. constrained queries. We follow a transformational approach based on rules and strategies. The use of the rules ensures that the specialized program is equivalent to the initial program w.r.t. a given constrained query. The strategies guide the application of the rules so to derive an efficient specialized program. In this paper we address various issues concerning the development of an automated transformation strategy. In particular, we consider the problems of when and how we should unfold, replace constraints, introduce generalized clauses, and apply the contextual constraint replacement rule. We propose a solution to these problems by adapting to our framework various techniques developed in the field of constraint programming, partial evaluation, and abstract interpretation. In particular, we use: (i) suitable solvers for simplifying constraints, (ii) well-quasi-orders for ensuring the termination...

Recent research suggests that the goal of fully automatic and reliable program generation for a broad range of applications is coming nearer to feasibility. However, several interesting and challenging problems remain to be solved before it becomes a reality. Solving them is also necessary, if we hope ever to elevate software engineering from its current state (a highly-developed handiwork) into a successful branch of engineering, capable of solving a wide range of new problems by systematic, well-automated and well-founded methods.

Generic functions are defined by induction on the structural representation of types. As a consequence, by defining just a single generic operation, one acquires this operation over any particular type. An instance on a specific type is generated by interpretation of the type's structure. A direct translation leads to extremely ine#cient code that involves many conversions between types and their structural representations. In this

The current state of the art for ensuring finite unfolding of logic programs consists of a number of online techniques where unfolding decisions are made at specialisation time. Introduction of a static termination analysis phase into a partial deduction algorithm permits unfolding decisions to be made offline, before the actual specialisation phase itself. This separation improves specialisation time and facilitates the automatic construction of compilers and compiler generators. The main contribution of this paper is

The paper contributes the proof of termination of an experimental supercompiler HOSC dealing with higher-order functions.