algorithm for Java programs. The algorithm is based on the abstraction of points-to escape graphs, which characterize how local variables and elds in objects refer to other objects. Each points-to escape graph also contains escape information, which characterizes how objects allocated in one region of the program can escape to be accessed by another region. The algorithm is designed to analyze arbitrary regions of complete or incomplete programs, obtaining complete information for objects that do not escape the analyzed regions.

This paper addresses the problem of resolving virtual method and interface calls in Java bytecode. The main focus is on a new practical technique that can be used to analyze large applications. Our fundamental design goal was to develop a technique that can be solved with only one iteration, and thus scales linearly with the size of the program, while at the same time providing more accurate results than two popular existing linear techniques, class hierarchy analysis and rapid type analysis. We present two variations of our new technique, variable-type analysis and a coarser-grain version called declared-type analysis. Both of these analyses are inexpensive, easy to implement, and our experimental results show that they scale linearly in the size of the program. We have implemented our new analyses using the Soot framework, and we report on empirical results for seven benchmarks. We have used our techniques to build accurate call graphs for complete applications (including librarie...

this article, we describe approximation methods for computing interprocedural aliases for a program written in a language that includes pointers, reference parameters, and recursion. We present the following contributions:

In this paper we present a modular interprocedural pointer analysis algorithm based on access-paths for C programs. We argue that access paths can reduce the overhead of representing context-sensitive transfer functions and effectively distinguish non-recursive heap objects. And when the modular analysis paradigm is used together with other techniques to handle type casts and function pointers, we are able to handle significant programs like those in the SPECcint92 and SPECcint95 suites. We have implemented the algorithm and tested it on a Pentium II 450 PC running Linux. The observed resource consumption and performance improvement are very encouraging.

This paper shows that a type graph (obtained via polymorphic type inference) harbors explicit directional flow paths between functions. These flow paths arise from the instantiations of polymorphic types and correspond to call-return sequences in first-order programs. We show that flow information can be computed efficiently while considering only paths with well matched call-return sequences, even in the higher-order case. Furthermore, we present a practical algorithm for inferring type instantiation graphs and provide empirical evidence to the scalability of the presented techniques by applying them in the context of points-to analysis for C programs.

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference object field. This information has a wide variety of client applications in optimizing compilers and software engineering tools. In this paper we present a points-to analysis for Java based on Andersen's points-to analysis for C [5]. We implement the analysis by using a constraint-based approach which employs annotated inclusion constraints. Constraint annotations allow us to model precisely and efficiently the semantics of virtual calls and the flow of values through object fields. By solving systems of annotated inclusion constraints, we have been able to perform practical and precise points-to analysis for Java.

To function on programs written in languages such as C that make extensive use of pointers, automated software engineering tools require safe alias information. Existing alias-analysis techniques that are sufficiently efficient for analysis on large software systems may provide alias information that is too imprecise for tools that use it: the imprecision of the alias information may (1) reduce the precision of the information provided by the tools and (2) increase the cost of the tools. This paper presents a flow-insensitive, context-sensitive points-to analysis algorithm that computes alias information that is almost as precise as that computed by Andersen's algorithm -- the most precise flow- and contextinsensitive algorithm -- and almost as efficient as Steensgaard's algorithm -- the most efficient flow- and context-insensitive algorithm. Our empirical studies show that our algorithm scales to large programs better than Andersen's algorithm and show that flow-insensitive alias an...

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference object field. We present object sensitivity, a new form of context sensitivity for flow-insensitive points-to analysis for Java. The key idea of our approach is to analyze a method separately for each of the object names that represent runtime objects on which this method may be invoked. To ensure flexibility and practicality, we propose a parameterization framework that allows analysis designers to control the tradeo#s between cost and precision in the object-sensitive analysis.

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference objet field. Improving the precision of practical points-to analysis is important because points-to information has a wide variety of client applications in optimizing compilers and software engineering tools. In this paper we present object sensitivity, a new form of context sensitivity for flow-insensitive points-to analysis for Java. The key idea of our approach is to analyze a method separately for each of the objects on which this method is invoked. To ensure flexibility and practicality, we propose a parameterization framework that allows analysis designers to control the tradeoffs between cost and precision in the object-sensitive analysis.

During the past twenty-one years, over seventy-five papers and nine Ph.D. theses have been published on pointer analysis. Given the tomes of work on this topic one may wonder, "Haven't we solved this problem yet?" With input from many researchers in the field, this paper describes issues related to pointer analysis and remaining open problems.