When users experience a software failure, they have the option of submitting a bug report and provide information about the failure and how it happened. If the bug report contains enough information, developers can then try to recreate the issue and investigate it, so as to eliminate its causes. Unfortunately, the number of bug reports filed by users is typically large, and the tasks of analyzing bug reports and reproducing the issues described therein can be extremely time consuming. To help make this process more efficient, in this paper we propose Yakusu, a technique that uses a combination of program analysis and natural language processing techniques to generate executable test cases from bug reports. We implemented Yakusu for Android apps and performed an empirical evaluation on a set of over 60 real bug reports for different real-world apps. Overall, our technique was successful in 59.7% of the cases, which means that for a majority of the bug reports, developers would not have to study the report to reproduce the issue described, as they could simply use the test cases automatically generated by Yakusu. Furthermore, in many of the remaining cases, Yakusu was unsuccessful due to limitations that are not inherent in the approach and that can be addressed in future work.