Declarative Debugging of Missing Answers for Maude

Declarative debugging is a semi-automatic technique that starts from an incorrect computation and locates a program fragment responsible for the error by building a tree representing this computation and guiding the user through it to find the error. Membership equational logic (MEL) is an equational logic that in addition to equations allows the statement of membership axioms characterizing the elements of a sort. Rewriting logic is a logic of change that extends MEL by adding rewrite rules, that correspond to transitions between states and can be nondeterministic. In this paper we propose a calculus that allows to infer normal forms and least sorts with the equational part, and sets of reachable terms through rules. We use an abbreviation of the proof trees computed with this calculus to build appropriate debugging trees for missing answers (results that are erroneous because they are incomplete), whose adequacy for debugging is proved. Using these trees we have implemented a declarative debugger for Maude, a high-performance system based on rewriting logic, whose use is illustrated with an example

Rule-Based Software Verification and Correction

The increasing complexity of software systems has led to the development of sophisticated formal Methodologies for verifying and correcting data and programs. In general, establishing whether a program behaves correctly w.r.t. the original programmer s intention or checking the consistency and the correctness of a large set of data are not trivial tasks as witnessed by many case studies which occur in the literature. In this dissertation, we face two challenging problems of verification and correction. Specifically, verification and correction of declarative programs, and the verification and correction of Web sites (i.e. large collections of semistructured data). Firstly, we propose a general correction scheme for automatically correcting declarative, rule-based programs which exploits a combination of bottom-up as well as topdown inductive learning techniques. Our hybrid hodology is able to infer program corrections that are hard, or even impossible, to obtain with a simpler,automatic top-down or bottom-up learner. Moreover, the scheme will be also particularized to some well-known declarative programming paradigm: that is, the functional logic and the functional programming paradigm. Secondly, we formalize a framework for the automated verification of Web sites which can be used to specify integrity conditions for a given Web site, and then automatically check whether these conditions are fulfilled. We provide a rule-based, formal specification language which allows us to define syntactic as well as semantic properties of the Web site. Then, we formalize a verification technique which detects both incorrect/forbidden patterns as well as lack of information, that is, incomplete/missing Web pages. Useful information is gathered during the verification process which can be used to repair the Web site. So, after a verification phase, one can also infer semi-automatically some possible corrections in order to fix theWeb site. The methodology is based on a novel rewritBallis, D. (2005). Rule-Based Software Verification and Correction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/194

Correctness and completeness of logic programs

We discuss proving correctness and completeness of definite clause logic programs. We propose a method for proving completeness, while for proving correctness we employ a method which should be well known but is often neglected. Also, we show how to prove completeness and correctness in the presence of SLD-tree pruning, and point out that approximate specifications simplify specifications and proofs. We compare the proof methods to declarative diagnosis (algorithmic debugging), showing that approximate specifications eliminate a major drawback of the latter. We argue that our proof methods reflect natural declarative thinking about programs, and that they can be used, formally or informally, in every-day programming.Comment: 29 pages, 2 figures; with editorial modifications, small corrections and extensions. arXiv admin note: text overlap with arXiv:1411.3015. Overlaps explained in "Related Work" (p. 21

PTL: A Model Transformation Language based on Logic Programming

In this paper we present a model transformation language based on logic programming. The language, called PTL (Prolog based Transformation Language), can be considered as a hybrid language in which ATL (Atlas Transformation Language)-style rules are combined with logic rules for defining transformations. ATL-style rules are used to define mappings from source models to target models while logic rules are used as helpers. The implementation of PTL is based on the encoding of the ATL-style rules by Prolog rules. Thus, PTL makes use of Prolog as a transformation engine. We have provided a declarative semantics to PTL and proved the semantics equivalent to the encoded program. We have studied an encoding of OCL (Object Constraint Language) with Prolog goals in order to map ATL to PTL. Thus a subset of PTL can be considered equivalent to a subset of ATL. The proposed language can be also used for model validation, that is, for checking constraints on models and transformations. We have equipped our language with debugging and tracing capabilities which help developers to detect programming errors in PTL rules. Additionally, we have developed an Eclipse plugin for editing PTL programs, as well as for debugging, tracing and validation. Finally, we have evaluated the language with several transformation examples as well as tested the performance with large models

Debugging Maude programs via runtime assertion checking and trace slicing

[EN] This is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Logical and Algebraic Methods in Programming, [VOL 85, ISSUE 5, (2016)] DOI 10.1016/j.jlamp.2016.03.001.In this paper we propose a dynamic analysis methodology for improving the diagnosis of erroneous Maude programs. The key idea is to combine runtime checking and dynamic trace slicing for automatically catching errors at runtime while reducing the size and complexity of the erroneous traces to be analyzed (i.e., those leading to states failing to satisfy some of the assertions). First, we formalize a technique that is aimed at automatically detecting deviations of the program behavior (symptoms) with respect to two types of user-defined assertions: functional assertions and system assertions. The proposed dynamic checking is provably sound in the sense that all errors flagged are definitely violations of the specifications. Then, upon eventual assertion violations we generate accurate trace slices that help identify the cause of the error. Our methodology is based on (i) a logical notation for specifying assertions that are imposed on execution runs; (ii) a runtime checking technique that dynamically tests the assertions; and (iii) a mechanism based on (equational) least general generalization that automatically derives accurate criteria for slicing from falsified assertions. Finally, we report on an implementation of the proposed technique in the assertion-based, dynamic analyzer ABETS and show how the forward and backward tracking of asserted program properties leads to a thorough trace analysis algorithm that can be used for program diagnosis and debugging. © 2016 Elsevier Inc. All rights reserved.This work has been partially supported by the EU (FEDER) and the Spanish MINECO under grants TIN2015-69175-C4-1-R and TIN2013-45732-C4-1-P, and by Generalitat Valenciana Ref. PROMETEOII/2015/013. F. Frechina was supported by FPU-ME grant AP2010-5681, and J. Sapiña was supported by FPI-UPV grant SP2013-0083 and mobility grant VIIT-3946.Alpuente Frasnedo, M.; Ballis, D.; Frechina, F.; Sapiña-Sanchis, J. (2016). Debugging Maude programs via runtime assertion checking and trace slicing. Journal of Logical and Algebraic Methods in Programming. 85(5):707-736. https://doi.org/10.1016/j.jlamp.2016.03.001S70773685

Synthesizing Iterators from Abstraction Functions

A technique for synthesizing iterators from declarative abstraction functions written in a relational logic specification language is described. The logic includes a transitive closure operator that makes it convenient for expressing reachability queries on linked data structures. Some optimizations, including tuple elimination, iterator flattening, and traversal state reduction, are used to improve performance of the generated iterators. A case study demonstrates that most of the iterators in the widely used JDK Collections classes can be replaced with code synthesized from declarative abstraction functions. These synthesized iterators perform competitively with the hand-written originals. In a user study the synthesized iterators always passed more test cases than the hand-written ones, were almost always as efficient, usually took less programmer effort, and were the qualitative preference of all participants who provided free-form comments

Interactive Simplifier Tracing and Debugging in Isabelle

The Isabelle proof assistant comes equipped with a very powerful tactic for term simplification. While tremendously useful, the results of simplifying a term do not always match the user's expectation: sometimes, the resulting term is not in the form the user expected, or the simplifier fails to apply a rule. We describe a new, interactive tracing facility which offers insight into the hierarchical structure of the simplification with user-defined filtering, memoization and search. The new simplifier trace is integrated into the Isabelle/jEdit Prover IDE.Comment: Conferences on Intelligent Computer Mathematics, 201