Experimental setup

Experiments

• algorithm, problem (, preferences) | designs
• output(s)

InPUT

• spaces
• code mappings

Inter-Design Dependencies

• algorithm -> properties -> problem

Extended Experimental Context

• arbitrary files

Experiment Code Features

• setValue, getValue
• import/export

Adjust Implementation or Change Programming Language / Framework

Further Material

A more sophisticated program using InPUT for analysis purposes is the PerformanceAnalyzer project. This screencast offers a hands-on tutorial on how to make the PerformanceAnalyzer configurable by InPUT.

An advanced use case of InPUT for the configuration of genetic algorithms can be found here. It requires an understanding of experimental design and the separation of concerns (experimental scope vs. experiment, design types etc.) presented in these slides and in this article.