## A Schema for Interprocedural Modification Side-Effect Analysis With Pointer Aliasing (2001)

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Venue: | In Proceedings of the SIGPLAN '93 Conference on Programming Language Design and Implementation |

Citations: | 131 - 13 self |

### BibTeX

@INPROCEEDINGS{Ryder01aschema,

author = {Barbara G. Ryder and William A. Landi and Philip A. Stocks and Sean Zhang and Rita Altucher},

title = {A Schema for Interprocedural Modification Side-Effect Analysis With Pointer Aliasing},

booktitle = {In Proceedings of the SIGPLAN '93 Conference on Programming Language Design and Implementation},

year = {2001},

pages = {56--67}

}

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### Abstract

The first interprocedural modification side-effects analysis for C (MOD_C) that obtains better than worst-case precision on programs with general-purpose pointer usage is presented with empirical results. The analysis consists of an algorithm schema corresponding to a family of MODC algorithms with two independent phases: one for determining pointer-induced aliases and a subsequent one for propagating interprocedural side effects. These MOD_C algorithms are parameterized by the aliasing method used. The empirical results compare the performance of two dissimilar MOD_C algorithms: MOD_C(FSAlias) uses a flow-sensitive, calling-context-sensitive interprocedural alias analysis [LR92]; MOD_C(FIAlias) uses a flow-insensitive, calling-context-insensitive alias analysis which is much faster, but less accurate. These two algorithms were profiled on 45 programs ranging in size from 250 to 30,000 lines of C code, and the results demonstrate dramatically the possible cost-precision tradeoffs. This first comparative implementation of MODC analyses offers insight into the differences between flow-/context-sensitive and flow-/context-insensitive analyses. The analysis cost versus precision tradeoffs in side-effect information obtained is reported. The results show surprisingly that the precision of flow-sensitive side-effect analysis is not always prohibitive in cost, and that the precision of flow-insensitive analysis is substantially better than worst-case estimates and seems sufficient for certain applications. On average MODC (FSAlias) for procedures and calls is in the range of 20% more precise than MODC (F IAlias); however, the performance was found to be at least an order of magnitude slower than MODC (F IAlias).