Incremental Analysis of

Global analyzers traditionally read and analyze the entire program at once, in a non-incremental way. However, there are many situations which are not well suited to this simple model and which instead require reanalysis of parts of a program which has already been analyzed. In these cases, it appears ineecient to perform the analysis of the program again from scratch, as needs to be done with current systems. We describe how the xpoint algorithms used in current generic analysis engines can be extended to support incremental analysis. The possible changes to a program are classiied into three types: addition, deletion, and arbitrary change. For each one of these, we provide one or more algorithms for identifying the parts of the analysis that must be recomputed and for performing the actual recompu-tation. The potential beneets and drawbacks of these algorithms are discussed. Finally, we present some experimental results obtained with an implementation of the algorithms in the PLAI generic abstract interpretation framework. The results show signiicant beneets when using the proposed incremental analysis algorithms.