Given either a specification written in natural language or an input program, automated program generation techniques produce a program according to the given specification or by modifying the input program. Automated program generation is a powerful technique that can be used for finding bugs in software systems that take programs as input or fixing bugs in the input programs. However, most existing techniques focus on automated program generation for automated program repair or program synthesis. This talk introduces a different perspective of automated program generation where we will discuss our latest results on automated program generation for testing static program analyzers by designing different types of program transformations. We will also explore and rethink about the automated program generation problem from the tester perspective. The new perspective could have huge potential for the design of new genetic improvement techniques to improve programs for automated program generation.