Interprocedural Alias Analysis Research Articles

A schema for interprocedural modification side-effect analysis with pointer aliasing

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 MOD C 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; 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 trade-offs. This first comparative implementation of MOD C analyses offers insight into the differences between flow-/context-sensitive and flow-/context-insensitive analyses. The analysis cost versus precision trade-offs in side-effect information obtained are 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 MOD C ( FSAlias ) for procedures and calls is in the range of 20% more precise than MOD C ( FIAlias ); however, the performance was found to be at least an order of magnitude slower than MOD C ( FIAlias ).

Interprocedural pointer alias analysis

We present practical approximation methods for computing and representing interprocedural aliases for a program written in a language that includes pointers, reference parameters, and recursion. We present the following contributions: (1) a framework for interprocedural pointer alias analysis that handles function pointers by constructing the program call graph while alias analysis is being performed; (2) a flow-sensitive interprocedural pointer alias analysis algorithm; (3) a flow-insensitive interprocedural pointer alias analysis algorithm; (4) a flow-insensitive interprocedural pointer alias analysis algorithm that incorporates kill information to improve precision; (5) empirical measurements of the efficiency and precision of the three interprocedural alias analysis algorithms.

Partial evaluation for program comprehension

Program comprehension is the most tedious and time consuming task of software maintenance, an important phase of the software life cycle. This is particularly true while maintaining scientific application programs that have been written in Fortran for decades and that are still vital in various domains even though more modern languages are used to implement their user interfaces. Very often, programs have evolved as their application domains increase continually and have become very complex due to extensive modifications. This generality in programs is implemented by input variables whose value does not vary in the context of a given application. Thus, it is very interesting for the maintainer to propagate such information, that is to obtain a simplified program, which behaves like the initial one when used according to the restriction. We have adapted partial evaluation for program comprehension. Our partial evaluator performs mainly two tasks: constant propagation and statements simplification. It includes an interprocedural alias analysis. As our aim is program comprehension rather than optimization, there are two main differences with classical partial evaluation. We do not change the original

Interprocedural may-alias analysis for pointers

Existing methods for alias analysis of recursive pointer data structures are based on two approximation techniques: k-limiting , and store-based (or equivalently location or region-based) approximations, which blur distinction between elements of recursive data structures. Although notable progress in inter-procedural alias analysis has been recently accomplished, very little progress in the precision of analysis of recursive pointer data structures has been seen since the inception of these approximation techniques by Jones and Muchnick a decade ago. As a result, optimizing, verifying and parallelizing programs with pointers has remained difficult. We present a new parametric framework for analyzing recursive pointer data structures which can express a new natural class of alias information not accessible to existing methods. The key idea is to represent alias information by pairs of symbolic access paths which are qualified by symbolic descriptions of the positions for which the alias pair holds. Based on this result, we present an algorithm for interprocedural may-alias analysis with pointers which on numerous examples that occur in practice is much more precise than recently published algorithms [CWZ90, He90, LR92, CBC93].

Interprocedural alias analysis: Implementation and empirical results

AbstractWe report our experiences with the implementation of InterProcedural Alias Analysis (IPA) for Fortran. Implicit aliasing caused by reference parameter passing can be uncovered in a program with multiple compilation units by interprocedural analysis. For scalar objects and for full arrays, the IPA processor described here finds all alias relations. For indexed array elements and partial arrays, conservative assumptions must still be made in the absence of precise knowledge about the subscripts. IPA has been integrated into nascent, the front‐end of a Fortran translator under development at the Oregon Graduate Institute (OGI). This report explains the goals and limitations of alias analysis for conventional procedural languages with reference parameters, shows in detail the actual design and implementation of IPA, and provides algorithmic and speed improvements over the best previously known aliasing algorithms. Empirical results gathered during the analysis of large Fortran programs are also listed and discussed.