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The success of AlphaGo Zero shows that a computer can learn to play a complicated board game without relying on the knowledge from human players. We observe that designing a distributed protocol is similar to playing board games to some extent: when determining the next action to take, they both want to ensure they can win even when a smart opponent tries to drive the game/protocol to the worst case. In this work, we explore whether we can apply similar techniques to learn a distributed protocol with zero knowledge. Towards this goal, we model the process in a distributed protocol as a state machine, and further rely on model checking to validate the correctness of the learned state machine. With this approach, we successfully learned a correct atomic commit protocol with three processes, and upon that, we further discuss future work. 

Database applications frequently use weaker isolation levels, such as Read Committed, for better performance, which may lead to bugs that do not happen under Serializable. Although a number of works have proposed methods to identify such isolation-related bugs, the difficulty of analyzing reported bugs is often underestimated, since these bugs often involve multiple complicated transactions interleaved in a specific order and they often require users' feedback to improve the accuracy of bug analysis. This paper presents IsoBugView, a tool to visualize isolation bugs and incorporate users' feedback: to address the challenge that a complicated bug may include much information and thus is hard to present, IsoBugView displays a high-level overview of the bug first and displays further information of individual pieces if the developer needs further investigation. To incorporate users' feedback, IsoBugView embeds hook functions into the backend analysis tool to preprocess a dependency graph and postprocess a found cycle and further allows a user to apply predefined hook functions in its graphic user interface. Our experience shows that IsoBugView has greatly improved our productivity of analyzing isolation bugs.