HeuristicLab is an extensible framework for evolutionary and heuristic algorithms that are independent of prototypes. It has a feature-rich and convenient GUI. You can pause/continue algorithms, load and save algorithms and problem to/from the disk. You can perform batch execution of experiments and algorithms. It features an experiment designer to execute and create multiple test runs, HeuristicLab Hive for distributed and parallel distribution of experiments and graphical algorithm designer to modify and create algorithms. It enables comparison and interactive and graphical analysis of results and parameters, easy integration of algorithms, problems and new operators through plug-in based architecture and parallel execution of experiments and algorithms on multi-core systems. It includes export charts in different image formats, flexible, generic and extensible data and algorithm model, copy/paste result tables to other applications, generic interface to couple with other applications, benchmark problems, optimization knowledge base and export of GP trees to LaTeX, MATLAB and other formats.