The correctness of compilers is instrumental in the safety and reliability of other software systems, as bugs in compilers can produce executables that do not reflect the intent of programmers. Such errors are difficult to identify and debug. Random test program generators are commonly used in testing compilers, and they have been effective in uncovering bugs. However, the problem of guiding these test generators to produce test programs that are more likely to find bugs remains challenging. In this paper, we use the code snippets in the bug reports to guide the test generation. The main idea of this work is to extract insights from the bug reports about the language features that are more prone to inadequate implementation and using the insights to guide the test generators. We use the GCC C compiler to evaluate the effectiveness of this approach. In particular, we first cluster the test programs in the GCC bugs reports based on their features. We then use the centroids of the clusters to compute configurations for Csmith, a popular test generator for C compilers. We evaluated this approach on eight versions of GCC and found that our approach provides higher coverage and triggers more miscompilation failures than the state-of-the-art test generation techniques for GCC.