Point To Information Research Articles

A Monadic Slicing Algorithm for a Program with Pointers

Program slicing is a family of program decomposition techniques.By introducing point-to analysis to the previous monadic slicing,the authors present and implement an approach of monadic slicing for a program with pointers.This approach obtains the point-to information through the data-flow iteration.Being different from the traditional methods,the point-to information and slicing are computed in the same phase in the method,by combining the forward monad slicing with data-flow iteration.Instead of recording point-to information for every statement,it is only needed to record the information for current analysis statements.So the method saves space without losing the precision.In addition,the approach also reserve the excellent properties of compositionality and language-flexibility from the original monadic slicing method.

Context sensitive symbolic pointer analysis

One of the bottlenecks in the recent movement of hardware synthesis from behavioral C programs is the difficulty in reasoning about runtime pointer values at compile time. The pointer analysis problem has been investigated in the compiler community for two decades and has yielded efficient, polynomial time algorithms for context-insensitive (CI) analysis. However, at the accuracy level for which hardware synthesis is desired, namely context and flow sensitive analysis, the time and space complexity of the best algorithms reported grow exponentially with program size. In this paper, we propose a new analysis technology to combat the inefficiency encountered in traditional algorithms. The key idea is to implicitly encode the pointer-to relation in the Boolean domain by Bryant's binary decision diagram, thereby capturing the procedure transfer function completely, compactly and canonically. With symbolic transfer functions, we can establish a common framework to perform both CI and context-sensitive (CS) pointer analysis efficiently. In addition, we propose a symbolic representation of the invocation graph, which can otherwise be exponentially large. In contrast to the classical frameworks, where CS point-to information of a procedure has to be obtained by the application of its transfer function exponentially many times, our method can obtain point-to information of all contexts in a single application. Our experimental evaluation on a wide range of C benchmarks indicates that our CS pointer analysis can be made almost as fast as its CI counterpart.

Symbolic pointer analysis revisited

Pointer analysis is a critical problem in optimizing compiler, parallelizing compiler, software engineering and most recently, hardware synthesis. While recent efforts have suggested symbolic method, which uses Bryant's Binary Decision Diagram as an alternative to capture the point-to relation, no speed advantage has been demonstrated for context-insensitive analysis, and results for context-sensitive analysis are only preliminary.In this paper, we refine the concept of symbolic transfer function proposed earlier and establish a common framework for both context-insensitive and context-sensitive pointer analysis. With this framework, our transfer function of a procedure can abstract away the impact of its callers and callees, and represent its point-to information completely, compactly and canonically. In addition, we propose a symbolic representation of the invocation graph, which can otherwise be exponentially large. In contrast to the classical frameworks where context-sensitive point-to information of a procedure has to be obtained by the application of its transfer function exponentially many times, our method can obtain point-to information of all contexts in a single application. Our experimental evaluation on a wide range of C benchmarks indicates that our context-sensitive pointer analysis can be made almost as fast as its context-insensitive counterpart.

A new approach to pointer analysis for assignments

Pointer analysis is a technique to identify at compile-time the potential values of the pointer expressions in a program, which promises significant benefits for optimizing and parallelizing compilers. In this paper, a new approach to pointer analysis for assignments is presented. In this approach, assignments are classified into three categories: pointer assignments, structure (union) assignments and normal assignments which don’t affect the point-to information. Pointer analyses for these three kinds of assignments respectively make up the integrated algorithm. When analyzing a pointer assignment, a new method called expression expansion is used to calculate both the left targets and the right targets. The integration of recursive data structure analysis into pointer analysis is a significant originality of this paper, which uniforms the pointer analysis for heap variables and the pointer analysis for stack variables. This algorithm is implemented in Agassiz, an analyzing tool for C programs developed by Institute of Parallel Processing, Fudan University Its accuracy and effectiveness are illustrated by experimental data.