Justified Belief Change

Justification Logic is a framework for reasoning about evidence and justification. Public Announcement Logic is a framework for reasoning about belief changes caused by public announcements. This paper develops JPAL, a dynamic justification logic of public announcements that corresponds to the modal theory of public announcements due to Gerbrandy and Groeneveld. JPAL allows us to reason about evidence brought about by and changed by Gerbrandy--Groeneveld-style public announcements.

Mondrian: An Agile Visualization Framework

Data visualization is the process of representing data as pictures to support reasoning about the underlying data. For the interpretation to be as easy as possible, we need to be as close as possible to the original data. As most visualization tools have an internal meta-model, which is different from the one for the presented data, they usually need to duplicate the original data to conform to their meta-model. This leads to an increase in the resources needed, increase which is not always justified. In this work we argue for the need of having an engine that is as close as possible to the data and we present our solution of moving the visualization tool to the data, instead of moving the data to the visualization tool. Our solution also emphasizes the necessity of reusing basic blocks to express complex visualizations and allowing the programmer to script the visualization using his preferred tools, rather than a third party format. As a validation of the expressiveness of our framework, we show how we express several already published visualizations and describe the pros and cons of the approach.

Automated design of self-stabilization

Self-stabilization is a property of a distributed system such that, regardless of the legitimacy of its current state, the system behavior shall eventually reach a legitimate state and shall remain legitimate thereafter. The elegance of self-stabilization stems from the fact that it distinguishes distributed systems by a strong fault tolerance property against arbitrary state perturbations. The difficulty of designing and reasoning about self-stabilization has been witnessed by many researchers; most of the existing techniques for the verification and design of self-stabilization are either brute-force, or adopt manual approaches non-amenable to automation. In this dissertation, we first investigate the possibility of automatically designing self-stabilization through global state space exploration. In particular, we develop a set of heuristics for automating the addition of recovery actions to distributed protocols on various network topologies. Our heuristics equally exploit the computational power of a single workstation and the available parallelism on computer clusters. We obtain existing and new stabilizing solutions for classical protocols like maximal matching, ring coloring, mutual exclusion, leader election and agreement. Second, we consider a foundation for local reasoning about self-stabilization; i.e., study the global behavior of the distributed system by exploring the state space of just one of its components. It turns out that local reasoning about deadlocks and livelocks is possible for an interesting class of protocols whose proof of stabilization is otherwise complex. In particular, we provide necessary and sufficient conditions – verifiable in the local state space of every process – for global deadlock- and livelock-freedom of protocols on ring topologies. Local reasoning potentially circumvents two fundamental problems that complicate the automated design and verification of distributed protocols: (1) state explosion and (2) partial state information. Moreover, local proofs of convergence are independent of the number of processes in the network, thereby enabling our assertions about deadlocks and livelocks to apply on rings of arbitrary sizes without worrying about state explosion.

Practical, Pluggable Types for a Dynamic Language

Most languages fall into one of two camps: either they adopt a unique, static type system, or they abandon static type-checks for run-time checks. Pluggable types blur this division by (i) making static type systems optional, and (ii) supporting a choice of type systems for reasoning about different kinds of static properties. Dynamic languages can then benefit from static-checking without sacrificing dynamic features or committing to a unique, static type system. But the overhead of adopting pluggable types can be very high, especially if all existing code must be decorated with type annotations before any type-checking can be performed. We propose a practical and pragmatic approach to introduce pluggable type systems to dynamic languages. First of all, only annotated code is type-checked. Second, limited type inference is performed on unannotated code to reduce the number of reported errors. Finally, external annotations can be used to type third-party code. We present Typeplug, a Smalltalk implementation of our framework, and report on experience applying the framework to three different pluggable type systems.

Enriching Reverse Engineering with Annotations

Much of the knowledge about software systems is implicit, and therefore difficult to recover by purely automated techniques. Architectural layers and the externally visible features of software systems are two examples of information that can be difficult to detect from source code alone, and that would benefit from additional human knowledge. Typical approaches to reasoning about data involve encoding an explicit meta-model and expressing analyses at that level. Due to its informal nature, however, human knowledge can be difficult to characterize up-front and integrate into such a meta-model. We propose a generic, annotation-based approach to capture such knowledge during the reverse engineering process. Annotation types can be iteratively defined, refined and transformed, without requiring a fixed meta-model to be defined in advance. We show how our approach supports reverse engineering by implementing it in a tool called Metanool and by applying it to (i) analyzing architectural layering, (ii) tracking reengineering tasks, (iii) detecting design flaws, and (iv) analyzing features.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

Soziales und moralisches Denken von Kindern über den Ein- und Ausschluss behinderter Kinder

Die Studie untersucht, wie 70 Kindergartenkinder im Vergleich zu 71 Fünft- und Sechstklässler über Situationen denken, in welchen sich ein Protagonist für die Wahl eines behinderten oder nicht behinderten Kindes in seine Gruppe entscheiden musste. Die Situationen wurden nach Behinderungsform des behinderten Kindes (geistig behindert, körperbehindert) und nach Gruppenaktivität (schulisch, sozial, sportlich) variiert. Die Kinder sollten die Wahl des Protagonisten vorhersagen und die Wahl begründen. Die älteren Kinder berücksichtigten in ihren Überlegungen stärker den situativen Kontext als die jüngeren Kinder. Allerdings erwarteten sie weniger häufig den Einschluss des geistig behinderten Kindes als den Einschluss des körperbehinderten Kindes. Die Ergebnisse der Studie werden vor dem Hintergrund von Forschung zur Entwicklung sozialen und moralischen Denkens über Ein- und Ausschluss diskutiert.

Apes’ tracking of objects and collections

Recent research suggests that great apes are less vulnerable to cohesion violations than human infants are. In contrast to human infants, apes successfully track nonsolid substances or split solid objects through occlusion (Cacchione & Call, 2010a; Cacchione, Hrubesch, & Call, 2012, 2013). The present study aims to investigate whether the lower vulnerability of great apes to cohesion violations also manifests when they are tracking collections. While even very young human infants appreciate the continuous existence of solid bound objects, they fail to show similar intuitions when tracking collections of objects (Chiang & Wynn, 2000). In a manual search task inspired by recent infant research, we tested whether humans’ closest relatives, the great apes, showed a similar contrast in their reasoning about single solid objects and objects within collections. The results suggest that, in contrast to human infants, great apes appreciate the continuous existence of objects within collections and successfully track them through occlusion. This confirms the view that great apes are generally less vulnerable to cohesion violations than human infants.

The Moldable Inspector: a framework for domain-specific object inspection

Answering run-time questions in object-oriented systems involves reasoning about and exploring connections between multiple objects. Developer questions exercise various aspects of an object and require multiple kinds of interactions depending on the relationships between objects, the application domain and the differing developer needs. Nevertheless, traditional object inspectors, the essential tools often used to reason about objects, favor a generic view that focuses on the low-level details of the state of individual objects. This leads to an inefficient effort, increasing the time spent in the inspector. To improve the inspection process, we propose the Moldable Inspector, a novel approach for an extensible object inspector. The Moldable Inspector allows developers to look at objects using multiple interchangeable presentations and supports a workflow in which multiple levels of connecting objects can be seen together. Both these aspects can be tailored to the domain of the objects and the question at hand. We further exemplify how the proposed solution improves the inspection process, introduce a prototype implementation and discuss new directions for extending the Moldable Inspector.

Hydrologic models for emergency decision support using Bayesian networks

In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited number sensors) and partial knowledge about the structure and behavior of the river basin. This is a case of reasoning about a complex dynamic system with uncertainty and real-time constraints where bayesian networks can be used to provide an effective support. In this paper we describe a solution with spatio-temporal bayesian networks to be used in a context of emergencies produced by river floods. In the paper we describe first a set of types of causal relations for hydrologic processes with spatial and temporal references to represent the dynamics of the river basin. Then we describe how this was included in a computer system called SAIDA to provide assistance to operators in charge of control in a river basin. Finally the paper shows experimental results about the performance of the model.

Efficient negation using abstract interpretation

While negation has been a very active área of research in logic programming, comparatively few papers have been devoted to implementation issues. Furthermore, the negation-related capabilities of current Prolog systems are limited. We recently presented a novel method for incorporating negation in a Prolog compiler which takes a number of existing methods (some modified and improved by us) and uses them in a combined fashion. The method makes use of information provided by a global analysis of the source code. Our previous work focused on the systematic description of the techniques and the reasoning about correctness and completeness of the method, but provided no experimental evidence to evalúate the proposal. In this paper, we report on an implementation, using the Ciao Prolog system preprocessor, and provide experimental data which indicates that the method is not only feasible but also quite promising from the efficiency point of view. In addition, the tests have provided new insight as to how to improve the proposal further. Abstract interpretation techniques are shown to offer important improvements in this application.

Efficient implementation of general negation using abstract interpretation

While negation has been a very active área of research in logic programming, comparatively few papers have been devoted to implementation issues. Furthermore, the negation-related capabilities of current Prolog systems are limited. We recently presented a novel method for incorporating negation in a Prolog compiler which takes a number of existing methods (some modified and improved) and uses them in a combined fashion. The method makes use of information provided by a global analysis of the source code. Our previous work focused on the systematic description of the techniques and the reasoning about correctness and completeness of the method, but provided no experimental evidence to evalúate the proposal. In this paper, after proposing some extensions to the method, we provide experimental data which indicates that the method is not only feasible but also quite promising from the efficiency point of view. In addition, the tests have provided new insight as to how to improve the proposal further. Abstract interpretation techniques (in particular those included in the Ciao Prolog system preprocessor) have had a significant role in the success of the technique.

Change-Impact driven Agile Architecting.

Software architecture is a key factor to scale up Agile Software Development ASD in large softwareintensive systems. Currently, software architectures are more often approached through mechanisms that enable to incrementally design and evolve software architectures aka. agile architecting. Agile architecting should be a light-weight decision-making process, which could be achieved by providing knowledge to assist agile architects in reasoning about changes. This paper presents the novel solution of using change-impact knowledge as the main driver for agile architecting. The solution consists of a Change Impact Analysis technique and a set of models to assist agile architects in the change -decision-making- process by retrieving the change-impact architectural knowledge resulting from adding or changing features iteration after iteration. To validate our approach, we have put our solution into practice by running a project of a metering management system in electric power networks in an i-smart software factory.

Derivación deductiva de programas funcionales con patrones

Una de las dificultades principales en el desarrollo de software es la ausencia de un marco conceptual adecuado para su estudio. Una propuesta la constituye el modelo transformativo, que entiende el desarrollo de software como un proceso iterativo de transformación de especificaciones: se parte de una especificación inicial que va transformándose sucesivamente hasta obtener una especificación final que se toma como programa. Este modelo básico puede llevarse a la práctica de varias maneras. En concreto, la aproximación deductiva toma una sentencia lógica como especificación inicial y su proceso transformador consiste en la demostración de la sentencia; como producto secundario de la demostración se deriva un programa que satisface la especificación inicial. La tesis desarrolla un método deductivo para la derivación de programas funcionales con patrones, escritos en un lenguaje similar a Hope. El método utiliza una lógica multigénero, cuya relación con el lenguaje de programación es estudiada. También se identifican los esquemas de demostración necesarios para la derivación de funciones con patrones, basados en la demostración independiente de varias subsentencias. Cada subsentencia proporciona una subespecificación de una ecuación del futuro programa a derivar. Nuestro método deductivo está inspirado en uno previo de Zohar Manna y Richard Waldinger, conocido como el cuadro deductivo, que deriva programas en un lenguaje similar a Lisp. El nuevo método es una modificación del cuadro de estos autores, que incorpora géneros y permite demostrar una especificación mediante varios cuadros. Cada cuadro demuestra una subespecificación y por tanto deriva una ecuación del programa. Se prevén mecanismos para que los programas derivados puedan contener definiciones locales con patrones y variables anónimas y sinónimas y para que las funciones auxiliares derivadas no usen variables de las funciones principales. La tesis se completa con varios ejemplos de aplicación, un mecanismo que independentiza el método del lenguaje de programación y un prototipo de entorno interactivo de derivación deductiva. Categorías y descriptores de materia CR D.l.l [Técnicas de programación]: Programación funcional; D.2.10 [Ingeniería de software]: Diseño - métodos; F.3.1 [Lógica y significado de los programas]: Especificación, verificación y razonamiento sobre programas - lógica de programas; F.3.3 [Lógica y significado de los programas]: Estudios de construcciones de programas - construcciones funcionales; esquemas de programa y de recursion; 1.2.2 [Inteligencia artificial]: Programación automática - síntesis de programas; 1.2.3 [Inteligencia artificial]: Deducción y demostración de teoremas]: extracción de respuesta/razón; inducción matemática. Términos generales Programación funcional, síntesis de programas, demostración de teoremas. Otras palabras claves y expresiones Funciones con patrones, cuadro deductivo, especificación parcial, inducción estructural, teorema de descomposición.---ABSTRACT---One of the main difficulties in software development is the lack of an adequate conceptual framework of study. The transformational model is one such proposal that conceives software development as an iterative process of specifications transformation: an initial specification is developed and successively transformed until a final specification is obtained and taken as a program. This basic model can be implemented in several ways. The deductive approach takes a logical sentence as the initial specification and its proof constitutes the transformational process; as a byproduct of the proof, a program which satisfies the initial specification is derived. In the thesis, a deductive method for the derivation of Hope-like functional programs with patterns is developed. The method uses a many-sorted logic, whose relation to the programming language is studied. Also the proof schemes necessary for the derivation of functional programs with patterns, based on the independent proof of several subsentences, are identified. Each subsentence provides a subspecification of one equation of the future program to be derived. Our deductive method is inspired on a previous one by Zohar Manna and Richard Waldinger, known as the deductive tableau, which derives Lisp-like programs. The new method incorporates sorts in the tableau and allows to prove a sentence with several tableaux. Each tableau proves a subspecification and therefore derives an equation of the program. Mechanisms are included to allow the derived programs to contain local definitions with patterns and anonymous and synonymous variables; also, the derived auxiliary functions cannot reference parameters of their main functions. The thesis is completed with several application examples, i mechanism to make the method independent from the programming language and an interactive environment prototype for deductive derivation. CR categories and subject descriptors D.l.l [Programming techniques]: Functional programming; D.2.10 [Software engineering]: Design - methodologies; F.3.1 [Logics and meanings of programa]: Specifying and verifying and reasoning about programs - logics of programs; F.3.3 [Logics and meanings of programs]: Studies of program constructs - functional constructs; program and recursion schemes; 1.2.2 [Artificial intelligence]: Automatic programming - program synthesis; 1.2.3 [Artificial intelligence]: Deduction and theorem proving - answer/reason extraction; mathematical induction. General tenas Functional programming, program synthesis, theorem proving. Additional key words and phrases Functions with patterns, deductive tableau, structural induction, partial specification, descomposition theorem.

Evaluating knowledge-based approaches to the multilingual extension of a temporal expression normalizer

The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from one language to a new one. Provided sufficient annotated data, machine learning algorithms allow to minimize the costs of such knowledge transfer but, up to date, proved to be ineffective for some specific tasks. Among these, the recognition and normalization of temporal expressions still remains out of their reach. Focusing on this task, and still adhering to the rule-based framework, this paper presents a bunch of experiments on the automatic porting to Italian of a system originally developed for Spanish. Different automatic rule translation strategies are evaluated and discussed, providing a comprehensive overview of the challenge.