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.

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.

We present a novel approach to dynamic datarace detection for multithreaded object-oriented programs. Past techniques for onthe -fly datarace detection either sacrificed precision for performance, leading to many false positive datarace reports, or maintained precision but incurred significant overheads in the range of 3# to 30#. In contrast, our approach results in very few false positives and runtime overhead in the 13% to 42% range, making it both efficient and precise. This performance improvement is the result of a unique combination of complementary static and dynamic optimization techniques.

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.

We extend Cyclone, a type-safe polymorphic language at the C level of abstraction, with threads and locks. Data races can violate type safety in Cyclone. An extended type system statically guarantees their absence by enforcing that thread-shared data is protected via locking and that threadlocal data does not escape the thread that creates it. The extensions interact smoothly with parametric polymorphism and region-based memory management. We present a formal abstract machine that models the need to prevent races, a polymorphic type system for the machine that supports thread-local data, and a corresponding type-safety result.

Object-oriented languages provide little support for encapsulating objects. Reference semantics allows objects to escape their defining scope. The pervasive aliasing that ensues remains a major source of software defects. This paper introduces Kacheck/J a tool for inferring object encapsulation properties in large Java programs. Our goal is to develop practical tools to assist software engineers, thus we focus on simple and scalable techniques. Kacheck/J is able to infer confinement for Java classes. A class and its subclasses are confined if all of their instances are encapsulated in their defining package. This simple property can be used to identify accidental leaks of sensitive objects. The analysis is scalable and efficient; Kacheck/J is able to infer confinement on a corpus of 46,000 classes (115 MB) in 6 minutes. 1.

We present a new classification system for aspect-oriented programs. This system characterizes the interactions between aspects and methods and identifies classes of interactions that enable modular reasoning about the crosscut program. We argue that this system can help developers structure their understanding of aspect-oriented programs and promotes their ability to reason productively about the consequences of crosscutting a program with a given aspect. We have designed and implemented a program analysis system that automatically classifies interactions between aspects and methods and have applied this analysis to a set of benchmark programs. We found that our analysis is able to 1) identify interactions with desirable properties (such as lack of interference), 2) identify potentially problematic interactions (such as interference caused by the aspect and the method both writing the same field), and 3) direct the developer’s attention to the causes of such interactions.

analysis for multithreaded programs. The algorithm uses a new abstraction called parallel interaction graphs to analyze the interactions between threads and extract precise points-to, escape, and action ordering information for objects accessed by multiple threads. The analysis is compositional, analyzing each method or thread once to extract a parameterized analysis result that can be specialized for use in any context. It is also capable of analyzing programs that use the unstructured form of multithreading present in languages such as Java and standard threads packages such as POSIX threads.

We present a new pointer and escape analysis. Instead of analyzing the whole program, the algorithm incrementally analyzes only those parts of the program that may deliver useful results. An analysis policy monitors the analysis results to direct the incremental investment of analysis resources to those parts of the program that o#er the highest expected optimization return.

This paper presents extensions to Steensgaard's and Andersen's algorithms to handle Java features. Without careful consideration, the handling of these features may affect the correctness, precision, and efficiency of these algorithms. The paper also presents the results of empirical studies. These studies compare the precision and efficiency of these two algorithms and evaluate the effectiveness of handling Java features using alternative approaches. The studies also evaluate the impact of the points-to information provided by these two algorithms on client analyses that use the information.