Static correction of Maude programs with assertions

[Otros] In this paper, we present a novel transformation method for Maude programs featuring both automatic program diagnosis and correction. The input of our method is a reference specification of the program behavior that is given in the form of assertions together with an overly general program whose execution might violate the assertions. Our correction technique translates into a refined program in which every computation is also a computation in that satisfies the assertions of . The technique is first formalized for topmost rewrite theories, and then we generalize it to larger classes of rewrite theories that support nested structured configurations. Our technique copes with infinite space states and does not require the knowledge of any failing run. We report experiments that assess the effectiveness of assertion-driven correction.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economia y Competitividad under grant TIN2015-69175-C4-1-R, and by Generalitat Valenciana PROMETEOII/2015/013 and PROMETEO/2019/098Alpuente Frasnedo, M.; Ballis, D.; Sapiña-Sanchis, J. (2019). Static correction of Maude programs with assertions. Journal of Systems and Software. 153:64-85. https://doi.org/10.1016/j.jss.2019.03.061S648515

Imposing Assertions in Maude via Program Transformation

[EN] Program transformation is widely used for producing correct mutations of a given program so as to satisfy the user's intent that can be expressed by means of some sort of specification (e.g. logical assertions, functional specifications, reference implementations, summaries, examples). This paper describes an automated correction methodology for Maude programs that is based on program transformation and can be used to enforce a safety policy, given by a set A of system assertions, in a Maude program R that might disprove some of the assertions. The outcome of the technique is a safe program refinement R' of R in which every computation is a good run, i.e., it satisfies the assertions in A. Furthermore, the transformation ensures that no good run of R is removed from R'. Advantages of this correction methodology can be summarized as follows. A fully automatic program transformation featuring both program diagnosis and repair that preserves all executability requirements. A simple logical notation to declaratively express invariant properties and other safety constraints through assertions. No dynamic information is required to infer program fixes: the methodology is static and does not need to collect any error symptom at runtime.This work has been partially supported by the EU (FEDER) and the Spanish MINECO under grant RTI2018-094403-B-C32, and by Generalitat Valenciana under grant PROMETEO/2019/098.Alpuente Frasnedo, M.; Ballis, D.; Sapiña-Sanchis, J. (2019). Imposing Assertions in Maude via Program Transformation. MethodsX. 6:2577-2583. https://doi.org/10.1016/j.mex.2019.10.035S25772583

Spectrum-Based Fault Localization in Model Transformations

Model transformations play a cornerstone role in Model-Driven Engineering (MDE), as they provide the essential mechanisms for manipulating and transforming models. The correctness of software built using MDE techniques greatly relies on the correctness of model transformations. However, it is challenging and error prone to debug them, and the situation gets more critical as the size and complexity of model transformations grow, where manual debugging is no longer possible. Spectrum-Based Fault Localization (SBFL) uses the results of test cases and their corresponding code coverage information to estimate the likelihood of each program component (e.g., statements) of being faulty. In this article we present an approach to apply SBFL for locating the faulty rules in model transformations. We evaluate the feasibility and accuracy of the approach by comparing the effectiveness of 18 different stateof- the-art SBFL techniques at locating faults in model transformations. Evaluation results revealed that the best techniques, namely Kulcynski2, Mountford, Ochiai, and Zoltar, lead the debugger to inspect a maximum of three rules to locate the bug in around 74% of the cases. Furthermore, we compare our approach with a static approach for fault localization in model transformations, observing a clear superiority of the proposed SBFL-based method.Comisión Interministerial de Ciencia y Tecnología TIN2015-70560-RJunta de Andalucía P12-TIC-186

Inferring Safe Maude Programs with \uc1TAME

In this paper, we present \atame, an assertion-based program specialization tool for the multi-paradigm language Maude. The program specializer \atame\ takes as input a set \cA of system assertions that model the expected program behavior plus a Maude program \cR to be specialized that might violate some of the assertions in \cA. The outcome of the tool is a safe program refinement \cR' of \cR in which every computation is a good run, i.e., it satisfies the assertions in \cA. The specialization technique encoded in \atame\ is fully automatic and ensures that no good run of \cR is removed from \cR', while the number of bad runs is reduced to zero. We demonstrate the tool capabilities by specializing an overly general nondeterministic dam controller to fulfill a safety policy given by a set of system assertions

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

Rewriting Logic Techniques for Program Analysis and Optimization

Esta tesis propone una metodología de análisis dinámico que mejora el diagnóstico de programas erróneos escritos en el lenguaje Maude. La idea clave es combinar técnicas de verificación de aserciones en tiempo de ejecución con la fragmentación dinámica de trazas de ejecución para detectar automáticamente errores en tiempo de ejecución, al tiempo que se reduce el tamaño y la complejidad de las trazas a analizar. En el caso de violarse una aserción, se infiere automáticamente el criterio de fragmentación, lo que facilita al usuario identificar rápidamente la fuente del error. En primer lugar, la tesis formaliza una técnica destinada a detectar automáticamente eventuales desviaciones del comportamiento deseado del programa (síntomas de error). Esta técnica soporta dos tipos de aserciones definidas por el usuario: aserciones funcionales (que restringen llamadas a funciones deterministas) y aserciones de sistema (que especifican los invariantes de estado del sistema). La técnica de verificación dinámica propuesta es demostrablemente correcta en el sentido de que todos los errores señalados definitivamente delatan la violación de las aserciones. Tras eventuales violaciones de aserciones, se generan automáticamente trazas fragmentadas (es decir, trazas simplificadas pero igualmente precisas) que ayudan a identificar la causa del error. Además, la técnica también sugiere una posible reparación para las reglas implicadas en la generación de los estados erróneos. La metodología propuesta se basa en (i) una notación lógica para especificar las aserciones que se imponen a la ejecución; (ii) una técnica de verificación aplicable en tiempo de ejecución que comprueba dinámicamente las aserciones; y (iii) un mecanismo basado en la generalización (ecuacional) menos general que automáticamente obtiene criterios precisos para fragmentar trazas de ejecución a partir de aserciones falsificadas. Por último, se presenta una implementación de la técnica propuesta en la herramienta de análisis dinámico basado en aserciones ABETS, que muestra cómo es posible combinar el trazado de las propiedades asertadas del programa para obtener un algoritmo preciso de análisis de trazas que resulta útil para el diagnóstico y la depuración de programas.This thesis proposes a dynamic analysis methodology for improving the diagnosis of erroneous Maude programs. The key idea is to combine runtime assertion 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 that fail to satisfy the assertions). In the event of an assertion violation, the slicing criterion is automatically inferred, which facilitates the user to rapidly pinpoint the source of the error. First, a technique is formalized that aims at automatically detecting anomalous deviations of the intended program behavior (error symptoms) by using assertions that are checked at runtime. This technique supports two types of user-defined assertions: functional assertions (which constrain deterministic function calls) and system assertions (which specify system state invariants). The proposed dynamic checking is provably sound in the sense that all errors flagged definitely signal a violation of the specifications. Then, upon eventual assertion violations, accurate trace slices (i.e., simplified yet precise execution traces) are generated automatically, which help identify the cause of the error. Moreover, the technique also suggests a possible repair for the rules involved in the generation of the erroneous states. The proposed 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, an implementation of the proposed technique is presented in the assertion-based, dynamic analyzer ABETS, which shows 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.Esta tesi proposa una metodologia d'anàlisi dinàmica que millora el diagnòstic de programes erronis escrits en el llenguatge Maude. La idea clau és combinar tècniques de verificació d'assercions en temps d'execució amb la fragmentació dinàmica de traces d'execució per a detectar automàticament errors en temps d'execució, alhora que es reduïx la grandària i la complexitat de les traces a analitzar. En el cas de violar-se una asserció, s'inferix automàticament el criteri de fragmentació, la qual cosa facilita a l'usuari identificar ràpidament la font de l'error. En primer lloc, la tesi formalitza una tècnica destinada a detectar automàticament eventuals desviacions del comportament desitjat del programa (símptomes d'error). Esta tècnica suporta dos tipus d'assercions definides per l'usuari: assercions funcionals (que restringixen crides a funcions deterministes) i assercions de sistema (que especifiquen els invariants d'estat del sistema). La tècnica de verificació dinàmica proposta és demostrablement correcta en el sentit que tots els errors assenyalats definitivament delaten la violació de les assercions. Davant eventuals violacions d'assercions, es generen automàticament traces fragmentades (és a dir, traces simplificades però igualment precises) que ajuden a identificar la causa de l'error. A més, la tècnica també suggerix una possible reparació de les regles implicades en la generació dels estats erronis. La metodologia proposada es basa en (i) una notació lògica per a especificar les assercions que s'imposen a l'execució; (ii) una tècnica de verificació aplicable en temps d'execució que comprova dinàmicament les assercions; i (iii) un mecanisme basat en la generalització (ecuacional) menys general que automàticament obté criteris precisos per a fragmentar traces d'execució a partir d'assercions falsificades. Finalment, es presenta una implementació de la tècnica proposta en la ferramenta d'anàlisi dinàmica basat en assercions ABETS, que mostra com és possible combinar el traçat cap avant i cap arrere de les propietats assertades del programa per a obtindre un algoritme precís d'anàlisi de traces que resulta útil per al diagnòstic i la depuració de programes.Sapiña Sanchis, J. (2017). Rewriting Logic Techniques for Program Analysis and Optimization [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/94044TESI

A partial evaluation methodology for optimizing rewrite theories incrementally

Partial evaluation (PE) is a branch of computer science that achieves code optimization via specialization. This article describes a PE methodology for optimizing rewrite theories that encode concurrent as well as nondeterministic systems by means of the Maude language. The main advantages of the proposed methodology can be summarized as follows: • An automatic program optimization technique for rewrite theories featuring several PE criteria that support the specialization of a broad class of rewrite theories. • An incremental partial evaluation modality that allows the key specialization components to be encapsulated at the desired granularity level to facilitate progressive refinements of the specialization. • All executability theory requirements are preserved by the PE transformation. Also the transformation ensures the semantic equivalence between the original rewrite theory and the specialized theory under rather mild conditions

Logic-based techniques for program analysis and specification synthesis

La Tesis investiga técnicas ágiles dentro del paradigma declarativo para dar solución a dos problemas: el análisis de programas y la inferencia de especificaciones a partir de programas escritos en lenguajes multiparadigma y en lenguajes imperativos con tipos, objetos, estructuras y punteros. Respecto al estado actual de la tesis, la parte de análisis de programas ya está consolidada, mientras que la parte de inferencia de especificaciones sigue en fase de desarrollo activo. La primera parte da soluciones para la ejecución de análisis de punteros especificados en Datalog. En esta parte se han desarrollado dos técnicas de ejecución de especificaciones en dicho lenguaje Datalog: una de ellas utiliza resolutores de sistemas de ecuaciones booleanas, y la otra utiliza la lógica de reescritura implementada eficientemente en el lenguaje Maude. La segunda parte desarrolla técnicas de inferencia de especificaciones a partir de programas. En esta parte se han desarrollado dos métodos de inferencia de especificaciones. El primer método se desarrolló para el lenguaje lógico-funcional Curry y permite inferir especificaciones ecuacionales mediante interpretación abstracta de los programas. El segundo método está siendo desarrollado para lenguajes imperativos realistas, y se ha aplicado a un subconjunto del lenguaje de programación C. Este método permite inferir especificaciones en forma de reglas que representan las distintas relaciones entre las propiedades que el estado de un programa satisface antes y después de su ejecución. Además, estas propiedades son expresables en términos de las abstracciones funcionales del propio programa, resultando en una especificación de muy alto nivel y, por lo tanto, de más fácil comprensión.Feliú Gabaldón, MA. (2013). Logic-based techniques for program analysis and specification synthesis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/33747TESI