Benchmarks are heavily used in different areas of computer science to evaluate algorithms and tools. In program analysis and testing, open-source and commercial programs are routinely used as benchmarks to evaluate different aspects of algorithms and tools. Unfortunately, many of these programs are written by programmers who introduce different biases, not to mention that it is very difficult to find programs that can serve as benchmarks with high reproducibility of results. We propose a novel approach for generating random benchmarks for evaluating program analysis and testing tools. Our approach uses stochastic parse trees, where language grammar production rules are assigned probabilities that specify the frequencies with which instantiations of these rules will appear in the generated programs. We implemented our tool for Java and applied it to generate benchmarks with which we evaluated different program analysis and testing tools. Our tool was also implemented by a major software company for C++ and used by a team of developers to generate benchmarks that enabled them to reproduce a bug in less than four hours.