Abstract: Aim To provide a general algorithm template for automatic generation of decision trees, making the designers of the decision tree algorithms be able to use this template to evaluate the new algorithms for solving specific decision problems. Methods The general template is initialized by the algorithm designers' own fomula edited in the intelligent editor provided by this paper or the built in algorithms, thus the continuous attributes are discretized. The unknown attributes and the noise data are processed with probability, the pre pruning and post pruning are used to prune the decision tree. Results and Conclusion Using this template, the new algorithms can be tested on different decision problems in the interactive graphic environment provided by this system.