This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object can be removed. We introduce a new program abstraction for escape analysis, the connection graph, that is used to establish reachability rela-tionships between objects and object references. We show that the connection graph can be summarized for each method such that the same summary information may be used effectively in different calling contexts. We present an interprocedural al-gorithm that uses the above property to efficiently compute the connection graph and identify the non-escaping objects for methods and threads. The experimental results, from a proto-type implementation of our framework in the IBM High Per-formance Compiler for Java, are very promising. The percent-age of objects that may be allocated on the stack exceeds 70% of all dynamically created objects in three out of the ten bench-marks (with a median of 19%), 11 % to 92 % of all lock oper-ations are eliminated in those ten programs (with a median of 5 l%), and the overall execution time reduction ranges from 2 % to 23 % (with a median of 7%) on a 333 MHz PowerPC workstation with 128 MB memory. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advant-age and that copies bear this notice and the full citation on the first page.

This paper presents the first scalable context-sensitive, inclusionbased pointer alias analysis for Java programs. Our approach to context sensitivity is to create a clone of a method for every context of interest, and run a context-insensitive algorithm over the expanded call graph to get context-sensitive results. For precision, we generate a clone for every acyclic path through a program’s call graph, treating methods in a strongly connected component as a single node. Normally, this formulation is hopelessly intractable as a call graph often has 10 14 acyclic paths or more. We show that these exponential relations can be computed efficiently using binary decision diagrams (BDDs). Key to the scalability of the technique is a context numbering scheme that exposes the commonalities across contexts. We applied our algorithm to the most popular applications available on Sourceforge, and found that the largest programs, with hundreds of thousands of Java bytecodes, can be analyzed in under 20 minutes. This paper shows that pointer analysis, and many other queries and algorithms, can be described succinctly and declaratively using Datalog, a logic programming language. We have developed a system called bddbddb that automatically translates Datalog programs into highly efficient BDD implementations. We used this approach to develop a variety of context-sensitive algorithms including side effect analysis, type analysis, and escape analysis.

...programs; any well-typed program in our system is free of data races. Our type system is significantly more expressive than previous such type systems. In particular, our system lets programmers write generic code to implement a class, then create different objects of the same class that have different protection mechanisms. This flexibility enables programmers to reduce the number of unnecessary synchronization operations in a program without risking data races. We also support default types which reduce the burden of writing the extra type annotations. Our experience indicates that our system provides a promising approach to make multithreaded programs more reliable and efficient.

This paper presents a novel interprocedural, flow-sensitive, and context-sensitive pointer analysis algorithm for multithreaded programs that may concurrently update shared pointers. For each pointer and each program point, the algorithm computes a conservative approximation of the memory locations to which that pointer may point. The algorithm correctly handles a full range of constructs in multithreaded programs, including recursive functions, function pointers, structures, arrays, nested structures and arrays, pointer arithmetic, casts between pointer variables of different types, heap and stack allocated memory, shared global variables, and thread-private global variables. We have implemented the algorithm in the SUIF compiler system and used the implementation to analyze a sizable set of multithreaded programs written in the Cilk multithreaded programming language. Our experimental results show that the analysis has good precision and converges quickly for our set of Cilk programs.

Systematic state-space exploration is a powerful technique for veri cation of concurrent software systems. Most work in this area deals with manually-constructed models of those systems. We propose a framework for applying state-space exploration to multi-threaded distributed systems written in standard programming languages. It generalizes Godefroid's work on VeriSoft, which does not handle multi-threaded systems, and Bruening's work on ExitBlockRW, which does not handle distributed (multi-process) systems. Unlike ExitBlockRW, our search algorithms incorporate powerful partial-order methods, guarantee detection of deadlocks, and guarantee detection of violations of the locking discipline used to avoid race conditions in accesses to shared variables. 1

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.

Containment of objects is a natural concept that has been poorly supported in object-oriented programming languages. For a predefined set of ownership contexts, this paper presents a type system that enforces certain containment relationships for run-time objects. A fixed ordering relationship is presumed between the owners. The formalisation of ownership types has developed from our work with flexible alias protection together with an investigation of structural properties of object graphs based on dominator trees. Our general ownership type system permits fresh ownership contexts to be created at run-time. Here we present a simplified system in which the ownership contexts are predefined. This is powerful enough to express and enforce constraints about a system's high-level structure. Our formal system is presented in an imperative variant of the object calculus. We present type preservation and soundness results. Furthermore we highlight how these type theoretic results establish a containment invariant for objects, in which access to contained objects is only permitted via their owners. In effect, the predefined ownership ordering restricts the permissible inter-object reference structure.

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.

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.

A compiler for multi-threaded object-oriented programs needs information about the sharing of objects for a variety of reasons: to implement optimizations, to issue warnings, to add instrumentation to detect access violations that occur at runtime. An Object Use Graph (OUG) statically captures accesses from different threads to objects. An OUG extends the Heap Shape Graph (HSG), which is a compile-time abstraction for runtime objects (nodes) and their reference relations (edges). An OUG specifies for a specific node in the HSG a partial order of events relevant to the corresponding runtime object(s). Relevant events include read and write access, object escape, thread start and join. OUGs have been implemented...