Using parametric set constraints for locating errors in CLP programs

This paper introduces a framework of parametric descriptive directional types for constraint logic programming (CLP). It proposes a method for locating type errors in CLP programs and presents a prototype debugging tool. The main technique used is checking correctness of programs w.r.t. type specifications. The approach is based on a generalization of known methods for proving correctness of logic programs to the case of parametric specifications. Set-constraint techniques are used for formulating and checking verification conditions for (parametric) polymorphic type specifications. The specifications are expressed in a parametric extension of the formalism of term grammars. The soundness of the method is proved and the prototype debugging tool supporting the proposed approach is illustrated on examples. The paper is a substantial extension of the previous work by the same authors concerning monomorphic directional types.Comment: 64 pages, To appear in Theory and Practice of Logic Programmin

Combining Type Checking and Set Constraint Solving to Improve Automated Software Verification

In this paper we show how prescritive type checking and constraint solving can be combined to increase automation during software verification. We do so by defining a type system and implementing a typechecker for {log} (read `setlog'), a Constraint Logic Programming (CLP) language and satisfiability solver based on set theory. Hence, we proceed as follows: a) a type system for {log} is defined; b) the constraint solver is proved to be safe w.r.t. the type system; c) the implementation of a concrete typechecker is presented; d) the integration of type checking and set constraint solving to increase automation during software verification is discussed; and f) two industrial-strength case studies are presented where this combination is used with very good results

Automatic binding-related error diagnosis in logic programs

This paper proposes a diagnosis algorithm for locating a certain kind of errors in logic programs: variable binding errors that result in abstract symptoms during compile-time checking of assertions based on abstract interpretation. The diagnoser analyzes the graph generated by the abstract interpreter, which is a provably safe approximation of the program semantics. The proposed algorithm traverses this graph to find the point where the actual error originates (a reason of the symptom), leading to the point the error has been reported (the symptom). The procedure is fully automatic, not requiring any interaction with the user. A prototype diagnoser has been implemented and preliminary results are encouraging

A Practical Type Analysis for Verification of Modular Prolog Programs

Regular types are a powerful tool for computing very precise descriptive types for logic programs. However, in the context of real life, modular Prolog programs, the accurate results obtained by regular types often come at the price of efficiency. In this paper we propose a combination of techniques aimed at improving analysis efficiency in this context. As a first technique we allow optionally reducing the accuracy of inferred types by using only the types defined by the user or present in the libraries. We claim that, for the purpose of verifying type signatures given in the form of assertions the precision obtained using this approach is sufficient, and show that analysis times can be reduced significantly. Our second technique is aimed at dealing with situations where we would like to limit the amount of reanalysis performed, especially for library modules. Borrowing some ideas from polymorphic type systems, we show how to solve the problem by admitting parameters in type specifications. This allows us to compose new call patterns with some pre computed analysis info without losing any information. We argue that together these two techniques contribute to the practical and scalable analysis and verification of types in Prolog programs

Regular Rooted Graph Grammars

In dieser Arbeit wir ein pragmatischer Ansatz zur Typisierung, statischen Analyse und Optimierung von Web-Anfragespachen, speziell Xcerpt, untersucht. Pragmatisch ist der Ansatz in dem Sinne, dass dem Benutzer keinerlei Einschränkungen aus Entscheidbarkeits- oder Effizienzgründen auf modellierbare Typen gestellt werden. Effizienz und Entscheidbarkeit werden stattdessen, falls nötig, durch Vergröberungen bei der Typprüfung erkauft. Eine Typsprache zur Typisierung von Graph-strukturierten Daten im Web wird eingeführt. Modellierbare Graphen sind so genannte gewurzelte Graphen, welche aus einem Spannbaum und Querreferenzen aufgebaut sind. Die Typsprache basiert auf reguläre Baum Grammatiken, welche um typisierte Referenzen erweitert wurde. Neben wie im Web mit XML üblichen geordneten strukturierten Daten, sind auch ungeordnete Daten, wie etwa in Xcerpt oder RDF üblich, modellierbar. Der dazu verwendete Ansatz---ungeordnete Interpretation Regulärer Ausdrücke---ist neu. Eine operationale Semantik für geordnete wie ungeordnete Typen wird auf Basis spezialisierter Baumautomaten und sog. Counting Constraints (welche wiederum auf presburgerarithmetische Ausdrücke) basieren. Es wird ferner statische Typ-Prüfung und -Inferenz von Xcerpt Anfrage- und Konstrukttermen, wie auch Optimierung von Xcerpt Anfragen auf Basis von Typinformation eingeführt.This thesis investigates a pragmatic approach to typing, static analysis and static optimization of Web query languages, in special the Web query language Xcerpt. The approach is pragmatic in the sense, that no restriction on the types are made for decidability or efficiency reasons, instead precision is given up if necessary. Pragmatics on the dynamic side means to use types not only to ensure validity of objects operating on, but also influencing query selection based on types. A typing language for typing of graph structured data on the Web is introduced. The Graphs in mind are based on spanning trees with references, the typing languages is based on regular tree grammars with typed reference extensions. Beside ordered data in the spirit of XML, unordered data (i.e. in the spirit of the Xcerpt data model or RDF) can be modelled using regular expressions under unordered interpretation – this approach is new. An operational semantics for ordered and unordered types is given based on specialized regular tree automata and counting constraints (them again based on Presburger arithmetic formulae). Static type checking of Xcerpt query and construct terms is introduced, as well as optimization of Xcerpt query terms based on schema information

The ciao system

Abstract is not available