Algorithm Diversity for Resilient Systems

Diversity can significantly increase the resilience of systems, by reducing the prevalence of shared vulnerabilities and making vulnerabilities harder to exploit. Work on software diversity for security typically creates variants of a program using low-level code transformations. This paper is the first to study algorithm diversity for resilience. We first describe how a method based on high-level invariants and systematic incrementalization can be used to create algorithm variants. Executing multiple variants in parallel and comparing their outputs provides greater resilience than executing one variant. To prevent different parallel schedules from causing variants' behaviors to diverge, we present a synchronized execution algorithm for DistAlgo, an extension of Python for high-level, precise, executable specifications of distributed algorithms. We propose static and dynamic metrics for measuring diversity. An experimental evaluation of algorithm diversity combined with implementation-level diversity for several sequential algorithms and distributed algorithms shows the benefits of algorithm diversity

Logic Programming Applications: What Are the Abstractions and Implementations?

This article presents an overview of applications of logic programming, classifying them based on the abstractions and implementations of logic languages that support the applications. The three key abstractions are join, recursion, and constraint. Their essential implementations are for-loops, fixed points, and backtracking, respectively. The corresponding kinds of applications are database queries, inductive analysis, and combinatorial search, respectively. We also discuss language extensions and programming paradigms, summarize example application problems by application areas, and touch on example systems that support variants of the abstractions with different implementations

On Fast Large-Scale Program Analysis in Datalog

Designing and crafting a static program analysis is challenging due to the complexity of the task at hand. Among the challenges are modelling the semantics of the input language, finding suitable abstractions for the analysis, and handwriting efficient code for the analysis in a traditional imperative language such as C++. Hence, the development of static program analysis tools is costly in terms of development time and resources for real world languages. To overcome, or at least alleviate the costs of developing a static program analysis, Datalog has been proposed as a domain specific language (DSL).With Datalog, a designer expresses a static program analysis in the form of a logical specification. While a domain specific language approach aids in the ease of development of program analyses, it is commonly accepted that such an approach has worse runtime performance than handcrafted static analysis tools. In this work, we introduce a new program synthesis methodology for Datalog specifications to produce highly efficient monolithic C++ analyzers. The synthesis technique requires the re-interpretation of the semi-naïve evaluation as a scaffolding for translation using partial evaluation. To achieve high-performance, we employ staged compilation techniques and specialize the underlying relational data structures for a given Datalog specification. Experimentation on benchmarks for large-scale program analysis validates the superior performance of our approach over available Datalog tools and demonstrates our competitiveness with state-of-the-art handcrafted tools

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

Evaluation of Datalog queries and its application to the static analysis of Java code

Two approaches for evaluating Datalog programs are presented: one based on boolean equation systems, and the other based on rewriting logic. The work is presented in the context of the static analysis of Java programs specified in Datalog.Feliú Gabaldón, MA. (2010). Evaluation of Datalog queries and its application to the static analysis of Java code. http://hdl.handle.net/10251/14016Archivo delegad

Optimización de programas Datalog basada en estrategias

Tarín Morales, F. (2011). Optimización de programas Datalog basada en estrategias. http://hdl.handle.net/10251/15639Archivo delegad