In the field of search based software engineering, evolutionary testing is a very popular domain in which test cases are automatically generated for a given piece of code using evolutionary algorithms. The techniques used in this domain usually are hard to compare since there is no standard testbed. In this paper we propose an automatic program generator to solve this situation. The program generator is able to create Java programs with the desired features. In addition, we can ensure that all the branches in the programs are reachable, i.e. a 100% branch coverage is always possible. Thanks to this feature the research community can test and enhance their algorithms until a total coverage is achieved. The potential of the program generator is illustrated with an experimental study on a benchmark of 800 generated programs. We highlight the correlations between some static measures computed on the program and the code coverage when an evolutionary test case generator is used. In particular, we compare three techniques as the search engine for the test case generator: an Evolutionary Strategy, a Genetic Algorithm and a Random Search.