基于下推自动机的细粒度锁自动重构方法

针对粗粒度锁会严重影响并发程序的可伸缩性问题，提出一种面向细粒度锁的自动重构方法.该方法借助访问者模式分析、别名分析、负面效应分析等多种程序分析技术获取临界区代码的读写模式，然后使用下推自动机构建不同锁模式的识别方法，根据识别结果进行代码重构.与以往锁重构方法的不同之处在于，该方法考虑了锁降级模式，使重构适用性更广.基于此方法，在Eclipse JDT框架下，以插件的形式实现了自动重构工具FLock.在实验中，从重构个数、改变的代码行数、重构时间、准确性和重构后程序性能等方面对FLock进行了评估，并与已有的重构工具Relocker和CLOCK进行了对比.对HSQLDB，Jenkins和Cassandra等11个大型实际应用程序的重构结果表明：FLock共重构了1 757个内置监视器对象，每个程序重构平均用时17.5s.该重构工具可以有效地实现粗粒度锁到细粒度锁的转换，与手动重构相比，有效提升了细粒度锁的重构效率.

Automated Refactoring Approach for Fine-grained Lock Based on Pushdown Automaton

As coarse-grained locks have a negative impact on the scalability of concurrent programs, this study proposes an automatic refactoring approach to convert a coarse-grained lock into a fine-grained one. Several static analyses, such as visitor pattern analysis, alias analysis, and side-effect analysis are employed in this approach. The read and write pattern of a critical section is inferred by side effect analysis, and then a push down automaton is proposed to identify the read and write pattern. Finally, refactoring is conducted based on these results. An automatic tool FLock is implemented as the Eclipse plug-in. The proposed approach is evaluated by eleven open-source projects including HSQLDB, Jenkins, and Cassandra, by presenting results such as the number of refactored locks, changed lines of code, refactoring time, accuracy, program performance after refactoring. FLock is also compared with the existing tools Relocker and CLOCK. The experimental results show that a total of 1757 built-in monitors are refactored and each refactoring takes an average of 17.5 seconds. The experiments reveal that the proposed tool can help developers convert coarse-grained locks into fine-grained locks effectively.