Race Condition Detection for Debugging Parallel Programs

这个项目的第一个目标是开发一个关于程序执行和竞争条件的形式化推理模型，允许精确定义不同类型的竞争条件，并证明和比较各种技术的特性。该模型将区分程序的实际行为、潜在行为和观察到的行为。第二个目标是开发动态技术，以便在有限的运行时间信息的约束下尽可能准确地检测竞争条件。这些技术通过定位程序错误的直接表现形式而不是由其他争用、不精确的运行时跟踪(导致虚假争用看起来像真实的)或隐式同步(由共享内存引用引起)所引起的那些争用来帮助程序员调试。这些技术分析观察到的行为，以保守地推测已经发生或可能发生的种族，以及在执行过程中不受任何其他种族影响的种族。这项研究的结果既是一种推理竞争条件并证明竞争条件检测技术的特性的理论，也是通过有效地定位那些对调试感兴趣的竞争条件来帮助程序员的技术。

The first objective of this project is to develop a formal model for reasoning about program executions and race conditions, allowing different types of race conditions to be precisely defined and properties of various techniques to be proven and compared. This model will distinguish between the program's actual behavior, its potential behavior, and its observed behavior. The second objective is to develop dynamic techniques for detecting race conditions as accurately as possible given the constraint of limited run-time information. These techniques aid the programmer in debugging by locating those races that are direct manifestations of program bugs and not artifacts caused by other races, imprecise run-time traces (causing false races to appear real), or implicit synchronization (caused by shared-memory references). These techniques analyze the observed behavior to conservatively speculate on races that either did occur or had the potential of occurring, and that were unaffected by any other race in the execution. The result of this research is both a theory in which to reason about race conditions and prove properties of techniques for race condition detection, and techniques that aid the programmer by efficiently locating those race conditions that are of interest for debugging.