This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library.

As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

The C programming language

This paper describes a programming system called Amber that permits a single application program to use a homogeneous network of computers in a uniform way, making the network appear to the application as an integrated multiprocessor. Amber is specifically designed for high performance in the case where each node in the network is a shared-memory multiprocessor.Amber shows that support for loosely-coupled multiprocessing can be efficiently realized using an object-based programming model. Amber programs execute in a uniform network-wide object space, with memory coherence maintained at the object level. Careful data placement and consistency control are essential for reducing communication overhead in a loosely-coupled system. Amber programmers use object migration primitives to control the location of data and processing.

The Amber system: parallel programming on a network of multiprocessors

It has been pointed out that inheritance and synchronization constraints in concurrent object systems often con ict with each other, resulting in inheritance anomaly where re-de nitions of inherited methods are necessary in order to maintain the integrity of concurrent objects. The anomaly is serious, as it could nullify the bene ts of inheritance altogether. Several proposals have been made for resolving the anomaly; however, we argue that those proposals su er from the incompleteness which allows room for counterexamples. We give an overview and the analysis of inheritance anomaly, and review several proposals for minimizing the unwanted e ect of this phenomenon. In particular, we propose (partial) solutions using (1) computational re ection, and (2) transactions in OOCP languages.

Analysis of inheritance anomaly in object-oriented concurrent programming languages

Distributed programming with shared data

This paper develops a methodology for compiling and executing irregular parallel programs. Such programs implement parallel operations whose size and work distribution depend on input data. We show a fundamental relationship between three quantities that characterize an irregular parallel computation: the total available parallelism, the optimal grain size, and the statistical variance of execution times for individual tasks. This relationship yields a dynamic scheduling algorithm that substantially reduces the overhead of executing irregular parallel operations.We incorporated this algorithm into an extended Fortran compiler. The compiler accepts as input a subset of Fortran D which includes blocked and cyclic decompositions and perfect alignment; it outputs Fortran 77 augmented with calls to library routines written in C. For irregular parallel operations, the compiled code gathers information about available parallelism and task execution time variance and uses this information to schedule the operation. On distributed memory architectures, the compiler encodes information about data access patterns for the runtime scheduling system so that it can preserve communication locality.We evaluated these compilation techniques using a set of application programs including climate modeling, circuit simulation, and x-ray tomography, that contain irregular parallel operations. The results demonstrate that, for these applications, the dynamic techniques described here achieve near-optimal efficiency on large numbers of processors. In addition, they perform significantly better, on these problems, than any previously proposed static or dynamic scheduling algorithm.

A dynamic scheduling method for irregular parallel programs

Sloop is a parallel language and environment that employs an object-oriented model for explicit parallel programming of MIMD multiprocessors. The Sloop runtime system transforms a network of processors into a virtual object space. A virtual object space contains a collection of objects that cooperate to solve a problem. Sloop encapsulates virtual object space semantics within the object type domain. This system-defined type provides an associative, asynchronous method by which one object gains access to another. It also provides an operation for specifying groups of objects that should, for efficiency, reside on the same physical processor, and supports exploitation of the topology of the underlying parallel machine. Domains also support the creation of indivisible objects, which provide implicit concurrency control. The encapsulation of these semantics within an object gives the programmer the power to construct an arbitrary hierarchy of virtual object spaces, facilitating debugging and program modularity. Sloop implementations are running on a bus-based multiprocessor, a hypercube multiprocessor, and on a heterogeneous network of workstations. The runtime system uses object relocation heuristics and coroutine scheduling to attain high performance.

Parallel programming in a virtual object space

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Parallel programming in a virtual object space