基于数据流分析的软件容错策略

A DFA based Approach for Software Fault Tolerance

该文就软件容错中备查点与卷回机制展开深入讨论，提出一种基于数据流分析技术的软件容错新方法．首先对软件容错进行简介，指出数据错是一切控制系统软件失效的根源与最终表现以及对数据采取强有力的容错措施的必要性．然后将数据流分析技术应用于软件容错，通过求解程序变量的到达－定值数据流方程来静态地确定任何数据在任何引用点出错时的最小充分卷回，通过求解活跃变量的数据流方程来静态地确定程序在执行各个基本块时需动态保存的变量集合，得出最小充分卷回定理与备查点数据范围定理，从而解决了时间冗余容错途径中必须回答的两个基本问题．此外，还给出了恢复块定义有效的充分条件．最后，以电信系统为应用实例，介绍了该方法的一种具体实施．该方法在简单地扩展后可被广泛应用于各种容错软件的设计中．

In this paper, the checkpointing & rollback mechanism is studied deeply, and a new approach for SFT (software fault tolerance) is presented, which is based on the DFA (data flow analysis). The authors introduce the SFT technology at first, and point out that the peculiarity of data is the ultimate reason and also the final result of the software faults in control systems, so it is very necessary to adopt a powerful measure for data fault tolerance. Then, they discuss the applications of the DFA technique in the SFT in details, and give two theorems, one is for the minimal sufficient rollback point and another is for the checkpoint data set. Besides, they give the sufficient condition for the validation of the definition of a rollback block. They also use the telecommunication system as an example to illustrate the usage of this method. It is shown that only two checkpoints are needed to be maintained dynamically in their solution. The method presented in this paper can be used widely by extending simply.