1 / 15

Polynomial Manipulation Language

Polynomial Manipulation Language. COMS4115 PLT Project Presentation December 9, 2003. Team Members: Melinda Agyekum, Shezan Baig, Hari Kurup, Subadhra Sridharan. Presentation Overview. Introduction Background The PML Language Language Features Functions & Capabilities Architecture

cyndi
Download Presentation

Polynomial Manipulation Language

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Polynomial Manipulation Language COMS4115 PLT Project Presentation December 9, 2003 Team Members: Melinda Agyekum, Shezan Baig, Hari Kurup, Subadhra Sridharan

  2. Presentation Overview • Introduction • Background • The PML Language • Language Features • Functions & Capabilities • Architecture • Design • Testing • Conclusion • Future Work • Team Experience • Questions & Answers

  3. Background on Polynomials • What is A Polynomial? • Mathematical expression written as the sum of products of numbers and variables • Practical Applications • Missile trajectory • Effectiveness of a Drug • Weather Forecasting

  4. Introduction to PML • What is PML? • Symbolic Polynomial Manipulation Language • Benefits of PML? • Provides Flexible Manipulation of Polynomials • Algorithmic Customization • Applicable in a Variety of Fields

  5. Introduction to PML • Parts of a Polynomial • Coefficient  Int or Float • Ex. 4, 4.3, -100, 14.23, -24.5 • Variable  Character ( Single or Multiple ) • Upper Case Representation • Ex. X, XY, RST, V • Degree  Variable Raised to a Power • Ex. X^2, T^4Y^3

  6. Introduction to PML • Term  Any Combination of • Coefficient , Variable, Degree • Ex. 3X, 4^3Y, XY, 3, -4X^3 • Polynomial  Sum of Terms • Ex. 3X+ Y, 5Y^3-4Z, 3Z, -4X^3

  7. PML Data Types • Int, Float, Char, Term, Poly • TemrArray • An array which contains the terms of a polynomial • CharArray • Stores all variables of a multivariate polynomial • Identifiers • All variable represented in lower case

  8. Language Features • Arrays • termarray and chararray • Grows and shrinks dynamically. • No 'new' or 'malloc' required. • length() --> returns array length • Loops & Breaks: • 'while' and 'do-while' loops are supported • Body must be enclosed within a begin-end block • 'break' statement to jump out of a loop.

  9. Language Features • Functions • Begins with the keyword 'func' • func <return type> foo ( poly p ) • Body enclosed within 'begin – end ' block. • Can be overloaded • No prototyping required • A 'main' function is necessary • In-built Functions • Ex. degree(), coeff(), polyterm()

  10. Language Features • Modularity • Program can consist of multiple files • One file must contain 'main()' • Re-usability • Scope • Global • Local • External Scope

  11. PMLRuntimeEnvironment PMLCompilationUnit PMLFunction PMLVariable PMLStatement PMLExpression PMLMath Architecture Source Code Lexer (PML.g) Parser (PML.g) Walker (PMLWalker.g) Executer (Java Classes) - prints output

  12. PML Example

  13. Testing • Unit Testing • Test for parser, walker, backend classes • Integrated Testing • Test complete flow once integrated • Regression Testing • Make sure new features don't introduce bugs

  14. Conclusion • Future Work • Implementing • Logarithms, Trigonometric Functions, Polynomial Division with Symbolic Math • Team Experience • Effective Communication • Set Early Deadlines and Incremental Goals • Parallel Work and Division of Labor • CVS Repository

  15. Thanks for Your Attention! Any Questions?

More Related