SciSmalltalk - Solving Ordinary Differential Equations in Smalltalk

Mentor: Serge Stinckwich
Second mentor:
Level: Intermediate
Submitted proposal to Melange: Natalia Moskovchuk
Invited students: , Natalia Moskovchuk
Students interested: (very), Siddharth Bhatia(very), Natalia Moskovchuk(very), Krutarth Patel(very), Mariano Sanchez(very), Pooja Varambally(very), Clara Allende, Jean-Baptiste Beuzelin, Hamza Nouri, Nirbhai Singh, Sergij Skytyba, Saad Touhbi, Abhishek Tyagi


SciSmalltalk is a new Smalltalk project, similar to existing scientific libraries like NumPy, SciPy for Python or SciRuby for Ruby. SciSmalltalk already provide basic functionalities under MIT licence: complex and quaternions extensions, random number generator, fuzzy algorithms, LAPACK linear algebra package, Didier Besset's
numerical methods, ... We want to extend SciSmalltalk to solve ODE (Ordinary Differential Equations). SciSmalltalk is available here: https://github.com/SergeStinckwich/SciSmalltalk

Technical Details

The development of this project is to be done in Pharo Smalltalk, but the code could be portable to other Smalltalk flavors. We want to build a library of ODE solvers that take care about performance without sacryifing flexibility. OdeInt could be used as an example to develop a Smalltalk library: http://headmyshoulder.github.com/odeint-v2/index.html. The student will need to have basic knowledge about differential equations and numerical algorithms. Units tests should also be provided.

Benefits to the Student

The student will help the Smalltalk community in a very concrete way. The student will learn to design well-designed code with tests.

Benefits to the Community

Having a basic ODE library is very important if we want to develop Smalltalk in new domains like robotics, high performance computing, computer vision, bio-computing, .... The lack of numeric librairies hamper the use of the Smalltalk in a scientific context at the moment.

Updated: 22.4.2013