Programming paradigms

Ron Ambrosio Internet-Scale Data Acquisition and Control Systems — Programming Paradigm Challenges, Paper presented at the conference, Creating An Expanded DER Industry, November 28-30, 2001, Loews L Enfant Plaza Hotel, Washington, DC. 

Parallel programming paradigms and environments differ in many aspects. These variations arise from at least four factors ... 

The Linda model supports many different parallel programming paradigms. At its simplest, the distributed-data environment offers an improvement over raw message passing by promoting an uncoupled programming style. This is because the synchronization of processes resulting from access to distributed data is minimal. However, arbitrarily complex shared and distributed data structures may be created. 

The programming paradigms applicable to scientific programming have often followed the developments in the field of software engineering. Some of the major paradigms applicable for scientific programming are briefly described in Table 2.2. 

TABLE 2.2 Overview of Some of the Main Programming Paradigms and Approaches Applicable to Scientific Programming... 

Chapter 3 provides a concise summary on technical design, programming paradigms, and development tools for expert systems. 

Rule-based programming is one of the most commonly used techniques for developing expert systems. In this programming paradigm, rules are used to represent heuristics, which specify a set of actions to be performed for a given situation. A rule is composed of an if-portion and a then-portion. The if-portion of a rule is a series of patterns that specify the facts, or data, that cause the rule to be applicable. The process of matching facts to patterns is called pattern matching. 

Declarative Programming is a programming paradigm that describes computations by specifying explicit objectives rather than the procedure on how to achieve them. Examples are SQL, PROLOG XSLT (see also Imperative Programming). 

Imperative Programming is a programming paradigm that describes computation as sequential statements that change a program state. Examples are FORTRAN, Pascal, C, and Visual Basic (see also Declarative Programming). 

Abstract data types have been established in computer science for many years (2). Indeed they are at the heart of the object-oriented programming paradigm. However, their use in scientific programming has been limited -probably because, prior to FORTRAN 90, FORTRAN provided no direct... 

We can also solve this recursion problem more traditionally using a procedural approach. The recursion in this case is buried within a "Do" loop, which is the classic structure in the procedural programming paradigm. The "Do" loop is placed within a Module function to keep all the variable names localized ... 

Object technology undoubtedly facilitates re-use to a greater extent than previous programming paradigms. This is clear from the widespread existence and use of application frameworks and large component libraries. It is likely that without object technology, it would not have been economic to develop many of today s complex and powerful commercial applications. 

In this Section a reverse engineering tool was described. The GUISURFER tool enables extraction of different behavioural models from application s source code. The tool is flexible, indeed the same techniques has already been applied to extract similar models from different programming paradigm. 

SISD machines call for the concept of sequential programming in which a program consists of a list of instructions to be executed one after the other. Although such machines may now work so fast that they appear to be executing more than one instruction at a time, the sequential programming paradigm still remains for most techniques and tools for software development, including sound synthesis. 

As far as sound synthesis is concerned, parallel supercomputing is commonly associated with the possibility of breaking the speed limits imposed by SISD machines. However much faster sequential computers become, parallel computing will still offer interesting programming paradigms for the development of new synthesis techniques. From a composer s perspective, it is this latter aspect of parallel computing that excites interest. 

Two main approaches are used to build parallel supercomputers SIMD (for Single Instruction Multiple Data) and MIMD (for Multiple Instructions Multiple Data). Whilst the former employs many processors simultaneously to execute the same program on different data, the latter employs several processors to execute different instructions on different data. Both approaches underpin different programming paradigms and have their own strengths and weaknesses. 

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