Concurrency

About: Concurrency is a research topic. Over the lifetime, 13042 publications have been published within this topic receiving 347118 citations.

Algebraic laws for nondeterminism and concurrency

Abstract: Since a nondeterministic and concurrent program may, in general, communicate repeatedly with its environment, its meaning cannot be presented naturally as an input/output function (as is often done in the denotational approach to semantics). In this paper, an alternative is put forth. First, a definition is given of what it is for two programs or program parts to be equivalent for all observers; then two program parts are said to be observation congruent if they are, in all program contexts, equivalent. The behavior of a program part, that is, its meaning, is defined to be its observation congruence class.The paper demonstrates, for a sequence of simple languages expressing finite (terminating) behaviors, that in each case observation congruence can be axiomatized algebraically. Moreover, with the addition of recursion and another simple extension, the algebraic language described here becomes a calculus for writing and specifying concurrent programs and for proving their properties.

A survey of program slicing techniques.

Abstract: A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest. Such a point of interest is referred to as a slicing criterion, and is typically specified by a location in the program in combination with a subset of the program’s variables. The task of computing program slices is called program slicing. The original definition of a program slice was presented by Weiser in 1979. Since then, various slightly different notions of program slices have been proposed, as well as a number of methods to compute them. An important distinction is that between a static and a dynamic slice. Static slices are computed without making assumptions regarding a program’s input, whereas the computation of dynamic slices relies on a specific test case. This survey presents an overview of program slicing, including the various general approaches used to compute slices, as well as the specific techniques used to address a variety of language features such as procedures, unstructured control flow, composite data types and pointers, and concurrency. Static and dynamic slicing methods for each of these features are compared and classified in terms of their accuracy and efficiency. Moreover, the possibilities for combining solutions for different features are investigated. Recent work on the use of compiler-optimization and symbolic execution techniques for obtaining more accurate slices is discussed. The paper concludes with an overview of the applications of program slicing, which include debugging, program integration, dataflow testing, and software maintenance.

Programming from specifications

Abstract: Providing a thorough treatment of most elementary programme development techniques, this revised edition covers topics such as procedures, parameters, recursion and data refinement, with the integration of specification, development and coding, based on ordinary (classical) logic. This second edition features: substantial restructuring of earlier material, streamlining the introduction of programming language features; simplified presentation of procedures, parameters and recursion; an expanded chapter on data refinement, giving the much simpler laws that specialize to functional abstractions; a new chapter on recursive types (trees etc) and appropriate control structures; and, following the original concluding case study, two completely new ones: "the recursive treatment of the largest rectangle under a histogram", and a specification and extended developnent of an electronic mail system (including limited concurrency).

Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems

Abstract: Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community. This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.