On the Computational Meaning of Axioms

An anti-realist theory of meaning suitable for both logical and proper axioms is investigated. As opposed to other anti-realist accounts, like Dummett-Prawitz verificationism, the standard framework of classical logic is not called into question. In particular, semantical features are not limited solely to inferential ones, but also computational aspects play an essential role in the process of determination of meaning. In order to deal with such computational aspects, a relaxation of syntax is shown to be necessary. This leads to a general kind of proof theory, where the objects of study are not typed objects like deductions, but rather untyped ones, in which formulas have been replaced by geometrical configurations

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

Semantics of logic programs with explicit negation

After a historical introduction, the bulk of the thesis concerns the study of a declarative semantics for logic programs. The main original contributions are: ² WFSX (Well–Founded Semantics with eXplicit negation), a new semantics for logic programs with explicit negation (i.e. extended logic programs), which compares favourably in its properties with other extant semantics. ² A generic characterization schema that facilitates comparisons among a diversity of semantics of extended logic programs, including WFSX. ² An autoepistemic and a default logic corresponding to WFSX, which solve existing problems of the classical approaches to autoepistemic and default logics, and clarify the meaning of explicit negation in logic programs. ² A framework for defining a spectrum of semantics of extended logic programs based on the abduction of negative hypotheses. This framework allows for the characterization of different levels of scepticism/credulity, consensuality, and argumentation. One of the semantics of abduction coincides with WFSX. ² O–semantics, a semantics that uniquely adds more CWA hypotheses to WFSX. The techniques used for doing so are applicable as well to the well–founded semantics of normal logic programs. ² By introducing explicit negation into logic programs contradiction may appear. I present two approaches for dealing with contradiction, and show their equivalence. One of the approaches consists in avoiding contradiction, and is based on restrictions in the adoption of abductive hypotheses. The other approach consists in removing contradiction, and is based in a transformation of contradictory programs into noncontradictory ones, guided by the reasons for contradiction

Um método supervisionado para encontrar variáveis discriminantes na análise de problemas complexos : estudos de caso em segurança do Android e em atribuição de impressora fonte

Orientadores: Ricardo Dahab, Anderson de Rezende RochaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A solução de problemas onde muitos componentes atuam e interagem simultaneamente requer modelos de representação nem sempre tratáveis pelos métodos analíticos tradicionais. Embora em muitos caso se possa prever o resultado com excelente precisão através de algoritmos de aprendizagem de máquina, a interpretação do fenómeno requer o entendimento de quais são e em que proporção atuam as variáveis mais importantes do processo. Esta dissertação apresenta a aplicação de um método onde as variáveis discriminantes são identificadas através de um processo iterativo de ranqueamento ("ranking") por eliminação das que menos contribuem para o resultado, avaliando-se em cada etapa o impacto da redução de características nas métricas de acerto. O algoritmo de florestas de decisão ("Random Forest") é utilizado para a classificação e sua propriedade de importância das características ("Feature Importance") para o ranqueamento. Para a validação do método, dois trabalhos abordando sistemas complexos de natureza diferente foram realizados dando origem aos artigos aqui apresentados. O primeiro versa sobre a análise das relações entre programas maliciosos ("malware") e os recursos requisitados pelos mesmos dentro de um ecossistema de aplicações no sistema operacional Android. Para realizar esse estudo, foram capturados dados, estruturados segundo uma ontologia definida no próprio artigo (OntoPermEco), de 4.570 aplicações (2.150 malware, 2.420 benignas). O modelo complexo produziu um grafo com cerca de 55.000 nós e 120.000 arestas, o qual foi transformado usando-se a técnica de bolsa de grafos ("Bag Of Graphs") em vetores de características de cada aplicação com 8.950 elementos. Utilizando-se apenas os dados do manifesto atingiu-se com esse modelo 88% de acurácia e 91% de precisão na previsão do comportamento malicioso ou não de uma aplicação, e o método proposto foi capaz de identificar 24 características relevantes na classificação e identificação de famílias de malwares, correspondendo a 70 nós no grafo do ecosistema. O segundo artigo versa sobre a identificação de regiões em um documento impresso que contém informações relevantes na atribuição da impressora laser que o imprimiu. O método de identificação de variáveis discriminantes foi aplicado sobre vetores obtidos a partir do uso do descritor de texturas (CTGF-"Convolutional Texture Gradient Filter") sobre a imagem scaneada em 600 DPI de 1.200 documentos impressos em 10 impressoras. A acurácia e precisão médias obtidas no processo de atribuição foram de 95,6% e 93,9% respectivamente. Após a atribuição da impressora origem a cada documento, 8 das 10 impressoras permitiram a identificação de variáveis discriminantes associadas univocamente a cada uma delas, podendo-se então visualizar na imagem do documento as regiões de interesse para uma análise pericial. Os objetivos propostos foram atingidos mostrando-se a eficácia do método proposto na análise de dois problemas em áreas diferentes (segurança de aplicações e forense digital) com modelos complexos e estruturas de representação bastante diferentes, obtendo-se um modelo reduzido interpretável para ambas as situaçõesAbstract: Solving a problem where many components interact and affect results simultaneously requires models which sometimes are not treatable by traditional analytic methods. Although in many cases the result is predicted with excellent accuracy through machine learning algorithms, the interpretation of the phenomenon requires the understanding of how the most relevant variables contribute to the results. This dissertation presents an applied method where the discriminant variables are identified through an iterative ranking process. In each iteration, a classifier is trained and validated discarding variables that least contribute to the result and evaluating in each stage the impact of this reduction in the classification metrics. Classification uses the Random Forest algorithm, and the discarding decision applies using its feature importance property. The method handled two works approaching complex systems of different nature giving rise to the articles presented here. The first article deals with the analysis of the relations between \textit{malware} and the operating system resources requested by them within an ecosystem of Android applications. Data structured according to an ontology defined in the article (OntoPermEco) were captured to carry out this study from 4,570 applications (2,150 malware, 2,420 benign). The complex model produced a graph of about 55,000 nodes and 120,000 edges, which was transformed using the Bag of Graphs technique into feature vectors of each application with 8,950 elements. The work accomplished 88% of accuracy and 91% of precision in predicting malicious behavior (or not) for an application using only the data available in the application¿s manifest, and the proposed method was able to identify 24 relevant features corresponding to only 70 nodes of the entire ecosystem graph. The second article is about to identify regions in a printed document that contains information relevant to the attribution of the laser printer that printed it. The discriminant variable determination method achieved average accuracy and precision of 95.6% and 93.9% respectively in the source printer attribution using a dataset of 1,200 documents printed on ten printers. Feature vectors were obtained from the scanned image at 600 DPI applying the texture descriptor Convolutional Texture Gradient Filter (CTGF). After the assignment of the source printer to each document, eight of the ten printers allowed the identification of discriminant variables univocally associated to each one of them, and it was possible to visualize in document's image the regions of interest for expert analysis. The work in both articles accomplished the objective of reducing a complex system into an interpretable streamlined model demonstrating the effectiveness of the proposed method in the analysis of two problems in different areas (application security and digital forensics) with complex models and entirely different representation structuresMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

The Significance of Evidence-based Reasoning for Mathematics, Mathematics Education, Philosophy and the Natural Sciences

In this multi-disciplinary investigation we show how an evidence-based perspective of quantification---in terms of algorithmic verifiability and algorithmic computability---admits evidence-based definitions of well-definedness and effective computability, which yield two unarguably constructive interpretations of the first-order Peano Arithmetic PA---over the structure N of the natural numbers---that are complementary, not contradictory. The first yields the weak, standard, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically verifiable Tarskian truth values to the formulas of PA under the interpretation. The second yields a strong, finitary, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically computable Tarskian truth values to the formulas of PA under the interpretation. We situate our investigation within a broad analysis of quantification vis a vis: * Hilbert's epsilon-calculus * Goedel's omega-consistency * The Law of the Excluded Middle * Hilbert's omega-Rule * An Algorithmic omega-Rule * Gentzen's Rule of Infinite Induction * Rosser's Rule C * Markov's Principle * The Church-Turing Thesis * Aristotle's particularisation * Wittgenstein's perspective of constructive mathematics * An evidence-based perspective of quantification. By showing how these are formally inter-related, we highlight the fragility of both the persisting, theistic, classical/Platonic interpretation of quantification grounded in Hilbert's epsilon-calculus; and the persisting, atheistic, constructive/Intuitionistic interpretation of quantification rooted in Brouwer's belief that the Law of the Excluded Middle is non-finitary. We then consider some consequences for mathematics, mathematics education, philosophy, and the natural sciences, of an agnostic, evidence-based, finitary interpretation of quantification that challenges classical paradigms in all these disciplines

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

The Significance of Evidence-based Reasoning in Mathematics, Mathematics Education, Philosophy, and the Natural Sciences

In this multi-disciplinary investigation we show how an evidence-based perspective of quantification---in terms of algorithmic verifiability and algorithmic computability---admits evidence-based definitions of well-definedness and effective computability, which yield two unarguably constructive interpretations of the first-order Peano Arithmetic PA---over the structure N of the natural numbers---that are complementary, not contradictory. The first yields the weak, standard, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically verifiable Tarskian truth values to the formulas of PA under the interpretation. The second yields a strong, finitary, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically computable Tarskian truth values to the formulas of PA under the interpretation. We situate our investigation within a broad analysis of quantification vis a vis: * Hilbert's epsilon-calculus * Goedel's omega-consistency * The Law of the Excluded Middle * Hilbert's omega-Rule * An Algorithmic omega-Rule * Gentzen's Rule of Infinite Induction * Rosser's Rule C * Markov's Principle * The Church-Turing Thesis * Aristotle's particularisation * Wittgenstein's perspective of constructive mathematics * An evidence-based perspective of quantification. By showing how these are formally inter-related, we highlight the fragility of both the persisting, theistic, classical/Platonic interpretation of quantification grounded in Hilbert's epsilon-calculus; and the persisting, atheistic, constructive/Intuitionistic interpretation of quantification rooted in Brouwer's belief that the Law of the Excluded Middle is non-finitary. We then consider some consequences for mathematics, mathematics education, philosophy, and the natural sciences, of an agnostic, evidence-based, finitary interpretation of quantification that challenges classical paradigms in all these disciplines

Contemporary Natural Philosophy and Philosophies - Part 2

Modern technology has eliminated barriers posed by geographic distances between people around the globe, making the world more interdependent. However, in spite of global collaboration within research domains, fragmentation among research fields persists and even escalates. Disintegrated knowledge has become subservient to the competition in the technological and economic race, leading in the direction chosen not by reason and intellect but rather by the preferences of politics and markets. To restore the authority of knowledge in guiding humanity, we have to reconnect its scattered isolated parts and offer an evolving and diverse but shared vision of objective reality connecting the sciences and other knowledge domains and informed by and in communication with ethical and esthetic thinking and being. This collection of articles responds to the second call from the journal Philosophies to build a new, networked world of knowledge with domain specialists from different disciplines interacting and connecting with the rest of the knowledge-producing and knowledge-consuming communities in an inclusive, extended natural-philosophic, human-centric manner. In this process of reconnection, scientific and philosophical investigations enrich each other, with sciences informing philosophies about the best current knowledge of the world, both natural and human-made, while philosophies scrutinize the ontological, epistemological, and methodological foundations of sciences