visual studio

Demo: Unit Testing in Visual Studio (C#)

Introduction

In this post, a demonstration on how to perform unit testing in Microsoft Visual Studio is covered. The demo is structured as follows:

  • create a console app with accompanying c sharp classes, and
  • perform unit testing on the methods used in the created classes.

In writing a program, implementing unit testing is a key step. The unit test project can be thought of as a document which can be used to understand the functionality and expected outcomes of the code. It is good practice to test the methods used in a program to check that the program delivers the expected results, and in performing the tests errors in the code can be picked up and corrected.

It often occurs that in the production process, a program needs to be extended. In extending the program, the results from one method should not alter the functioning/outcome of other methods. When unit testing is in place, errors can easily be picked up if it were the case that adding new code altered the outcome of existing working code. In this way, the existing working code is validated again when new code is added to the project. Using unit testing therefore serves as an important quality check of a program in the production process. Continue reading

Compiling LevmarSharp (Visual Studio 2010)

Prerequisites:

-Visual Studio 2010

-levmar 2.6 (http://users.ics.forth.gr/~lourakis/levmar/)

-levmarsharp (https://github.com/AvengerDr/LevmarSharp)


For a recent research project we needed to solve an optimization problem. In specific we were trying to reproduce the results in the paper “A Generalized Procedure for Building Trees for the Short Rate and its Application to Determining Market Implied Volatility Functions” by Hull and White. In the paper it is described how a lattice can be constructed and calibrated to market. The calibration is essentially an optimization problem where the difference between the discount factors (or interest rates) observed in the market and the discounts generated in the model is made as small as possible by varying the model parameters.

Continue reading