Pattern matching for definite summation in Maple

The proposed project is to design and implement a pattern matching based method for definite symbolic summation in. To remain competitive, Maple’s symbolic computation capabilities, which are one of its strengths, need to be improved constantly. This includes the ability to symbolically evaluate definite sums. Closed forms for definite sums are important in many applications, e.g., special functions, combinatorics, as well as first- and second-year university analysis courses, and even particle physics. Since new algorithms for symbolic summation that target more general classes of inputs are high effort to implement, and the benefits of doing so are not so clear, a pattern matching based approach seems like the quickest way to extend Maple’s symbolic summation capabilities, closing the gap between Maple’s integration capabilities (which already uses pattern matching) and summation capabilities (that are mostly pure algorithmic).

Faculty Supervisor:

Eugene Zima

Student:

Partner:

Maplesoft

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Waterloo

Program: