The user-level semantic matching capability in MACSYMA

WPC '96. 4th Workshop on Program Comprehension, 1996

Techniques for Automatic Program Comprehension can play a crucial role in overcoming limitations of existing tools for the automatic parallelization of programs for distributedmemory architectures. Uses of a program recognition-based parallelization procedure could range from the automatic selection of a data distribution, via the automatic selection of sequences of optimizing transformations of the sequential code, via the code replacement with optimized parallel libraries, up to the automatic selection of the parallel execution model that is best suited to the algorithm to be parallelized and to the target parallel architecture. In this paper is presented the implementation of a prototype tool for the recognition of Parallelizable Algorithmic Patterns (PAP Recognizer), which has been integrated into the Vienna Fortran Compilation System, an interactive compilation system for scalable architectures. The distinctive features of the approach are discussed and the way the recognizer works is described with respect to a working example.

Cybernetics, 1977

1967

2009

This article is an excerpt from the recently released book, Programming with Mathematica: An Introduction by Paul Wellin © 2013 [1]. The book, which follows on the well-known An Introduction to Mathematica Programming, provides an exampledriven primer on the foundations of the Mathematica programming language. Strings are used across many disciplines to represent filenames, data, and other objects: linguists working with text data study representation, classification, and patterns involved in audio and text usage; biologists dealing with genomic data as strings are interested in sequence structure and assembly and perform extensive statistical analysis of their data; programmers operate on string data for such tasks as text search, file manipulation, and text processing. Strings are so ubiquitous that almost every modern programming language has a string datatype and dozens of functions for operating on and with strings. StringQ@"The magic words are squeamish ossifrage."D True Strings are also used to represent file names that you import and export. Import@"ExampleDataêocelot.jpg"D Strings are used as arguments, option values, and as the output to many functions. GenomeData@"SNORD107"D GGTTCATGATGACACAGGACCTTGTCTGAACATAATGATTTCAAAATTTGAGCTTAAAAÖ ATGACACTCTGAAATC StringQ@%D True In this chapter we will introduce the tools available for working with strings in Mathematica. We will begin with a look at the structure and syntax of strings, then move on to a discussion of the many high-level functions that are optimized for string manipulation. String patterns follow on the discussion of patterns in Chapter 4 and we will introduce an alternative syntax (regular expressions) that provides a very compact mechanism for working with strings. The chapter closes with several applied examples drawn from computer science (checksums) as well as bioinformatics (working with DNA sequences) and also word games (anagrams, blanagrams). ‡ 9.1. Structure and Syntax Strings are expressions consisting of a number of characters enclosed in quotes. The characters can be anything you can type from your keyboard, including uppercase and lowercase letters, numbers, punctuation marks, and spaces. For example, here is the standard set of printable Ascii characters.

Symmetry, 2018

In this paper, we propose a methodology for the step-by-step solution of problems, which can be incorporated into a computer algebra system. Our main aim is to show all the intermediate evaluation steps of mathematical expressions from the start to the end of the solution. The first stage of the methodology covers the development of a formal grammar that describes the syntax and semantics of mathematical expressions. Using a compiler generation tool, the second stage produces a parser from the grammar description. The parser is used to convert a particular mathematical expression into an Abstract Syntax Tree (AST), which is evaluated in the third stage by traversing al its nodes. After every evaluation of some nodes, which corresponds to an intermediate solution step of the related expression, the resulting AST is transformed into the corresponding mathematical expression and then displayed. Many other algebra-related issues such as simplification, factorization, distribution and substitution can be covered by the solution methodology. We currently focuses on the solutions of various problems associated with the subject of derivative, equations, single variable polynomials, and operations on functions. However, it can easily be extended to cover the other subjects of general mathematics.

SSRN Electronic Journal, 2019

Mathematics plays an important role in everybody's life. We mainly depend on calculators available in our electronic gadgets to solve mathematical equations. Calculators available in these gadgets are so advanced that it can solve most complex mathematical equations. Remembering the fact that almost all electronic gadgets are touch screen based now-a-days, developing a system that recognizes and solves mathematical equations from handwriting is a potential area of research. This work develops an automatic equation solver, which solves the mathematical equations written by different persons. Neural network approach is used for recognition of the symbols and alphabets. The system is able to recognise alphabets, all the numbers, mathematical symbols and some special symbols. The system is successful in solving polynomial equations of power up to degree 9, system of linear equations with 2 and 3 variables having finite, infinite and no solutions. The system gives a recognition accuracy of 90% out of the 60 equations tested.

Lecture Notes in Computer Science, 2002

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

Proceedings of the 29th Conference of the …, 2005

Proceedings of the second ACM symposium on Symbolic and algebraic manipulation - SYMSAC '71, 1971