Amortized Dynamic Cell-Probe Lower Bounds from Four-Party Communication

This paper develops a new technique for proving amortized, randomized cell-probe lower bounds on dynamic data structure problems. We introduce a new randomized nondeterministic four-party communication model that enables "accelerated", error-preserving simulations of dynamic data structures. We use this technique to prove an $\Omega(n(\log n/\log\log n)^2)$ cell-probe lower bound for the dynamic 2D weighted orthogonal range counting problem (2D-ORC) with $n/\mathrm{poly}\log n$ updates and $n$ queries, that holds even for data structures with $\exp(-\tilde{\Omega}(n))$ success probability. This result not only proves the highest amortized lower bound to date, but is also tight in the strongest possible sense, as a matching upper bound can be obtained by a deterministic data structure with worst-case operational time. This is the first demonstration of a "sharp threshold" phenomenon for dynamic data structures. Our broader motivation is that cell-probe lower bounds for exponentially small success facilitate reductions from dynamic to static data structures. As a proof-of-concept, we show that a slightly strengthened version of our lower bound would imply an $\Omega((\log n /\log\log n)^2)$ lower bound for the static 3D-ORC problem with $O(n\log^{O(1)}n)$ space. Such result would give a near quadratic improvement over the highest known static cell-probe lower bound, and break the long standing $\Omega(\log n)$ barrier for static data structures

Conformal structures of static vacuum data

In the Cauchy problem for asymptotically flat vacuum data the solution-jets along the cylinder at space-like infinity develop in general logarithmic singularities at the critical sets at which the cylinder touches future/past null infinity. The tendency of these singularities to spread along the null generators of null infinity obstructs the development of a smooth conformal structure at null infinity. For the solution-jets arising from time reflection symmetric data to extend smoothly to the critical sets it is necessary that the Cotton tensor of the initial three-metric h satisfies a certain conformally invariant condition (*) at space-like infinity, it is sufficient that h be asymptotically static at space-like infinity. The purpose of this article is to characterize the gap between these conditions. We show that with the class of metrics which satisfy condition (*) on the Cotton tensor and a certain non-degeneracy requirement is associated a one-form $\kappa$ with conformally invariant differential $d\kappa$. We provide two criteria: If $h$ is real analytic, $\kappa$ is closed, and one of it integrals satisfies a certain equation then h is conformal to static data near space-like infinity. If h is smooth, $\kappa$ is asymptotically closed, and one of it integrals satisfies a certain equation asymptotically then h is asymptotically conformal to static data at space-like infinity.Comment: 68 pages, typos corrected, references and details adde

Static data structures

Las computadoras son máquinas dedicadas al manejo de información. Esta información se estructura de forma adecuada para obtener un rendimiento razonable en su memorización, tratamiento y recuperación. En este tema comenzamos estudiando el concepto de dato lógico, describiendo algunos de los tipos de datos más usuales. A continuación, estudiaremos algunas estructuras de datos utilizadas en programación, en sistemas operativos, o en el diseño físico de computadoras. Cuando utilizamos una computadora para resolver un problema debemos hacer una abstracción de la información y de las magnitudes que influyen en ella.Computers are machines dedicated to handling information. This information is structured properly to get a reasonable return on their storage, treatment and recovery. This topic began studying the concept of logical data, describing some of the most common types of data. Then we study some data structures used in programming, operating systems, or the physical design of computers. When we use a computer to solve a problem we must make an abstraction of information and variables that influence it

Data-flow Analysis of Programs with Associative Arrays

Dynamic programming languages, such as PHP, JavaScript, and Python, provide built-in data structures including associative arrays and objects with similar semantics-object properties can be created at run-time and accessed via arbitrary expressions. While a high level of security and safety of applications written in these languages can be of a particular importance (consider a web application storing sensitive data and providing its functionality worldwide), dynamic data structures pose significant challenges for data-flow analysis making traditional static verification methods both unsound and imprecise. In this paper, we propose a sound and precise approach for value and points-to analysis of programs with associative arrays-like data structures, upon which data-flow analyses can be built. We implemented our approach in a web-application domain-in an analyzer of PHP code.Comment: In Proceedings ESSS 2014, arXiv:1405.055

Dynamic Data Structures for Document Collections and Graphs

In the dynamic indexing problem, we must maintain a changing collection of text documents so that we can efficiently support insertions, deletions, and pattern matching queries. We are especially interested in developing efficient data structures that store and query the documents in compressed form. All previous compressed solutions to this problem rely on answering rank and select queries on a dynamic sequence of symbols. Because of the lower bound in [Fredman and Saks, 1989], answering rank queries presents a bottleneck in compressed dynamic indexing. In this paper we show how this lower bound can be circumvented using our new framework. We demonstrate that the gap between static and dynamic variants of the indexing problem can be almost closed. Our method is based on a novel framework for adding dynamism to static compressed data structures. Our framework also applies more generally to dynamizing other problems. We show, for example, how our framework can be applied to develop compressed representations of dynamic graphs and binary relations

Sawja: Static Analysis Workshop for Java

Static analysis is a powerful technique for automatic verification of programs but raises major engineering challenges when developing a full-fledged analyzer for a realistic language such as Java. This paper describes the Sawja library: a static analysis framework fully compliant with Java 6 which provides OCaml modules for efficiently manipulating Java bytecode programs. We present the main features of the library, including (i) efficient functional data-structures for representing program with implicit sharing and lazy parsing, (ii) an intermediate stack-less representation, and (iii) fast computation and manipulation of complete programs