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.

This paper presents a static race detection analysis for multithreaded Java programs. Our analysis is based on a formal type system that is capable of capturing many common synchronization patterns. These patterns include classes with internal synchronization, classes that require client-side synchronization, and thread-local classes. Experience checking over 40,000 lines of Java code with the type system demonstrates that it is an effective approach for eliminating races conditions. On large examples, fewer than 20 additional type annotations per 1000 lines of code were required by the type checker, and we found a number of races in the standard Java libraries and other test programs. 1

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.

Ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected and nondeterministic interactions between threads. Previous work addressed this problem by devising tools for detecting race conditions, a situation where two threads simultaneously access the same data variable, and at least one of the accesses is a write. However, verifying the absence of such simultaneous-access race conditions is neither necessary nor sufficient to ensure the absence of errors due to unexpected thread interactions. We propose that a stronger non-interference property is required, namely atomicity. Atomic methods can be assumed to execute serially, without interleaved steps of other threads. Thus, atomic methods are amenable to sequential reasoning techniques, which significantly simplifies both formal and informal reasoning about program correctness. This paper presents a type system for specifying and verifying the atomicity of methods in multithreaded Java programs. The atomic type system is a synthesis of Lipton’s theory of reduction and type systems for race detection. We have implemented this atomic type system for Java and used it to check a variety of standard Java library classes. The type checker uncovered subtle atomicity violations in classes such as java.lang.String and java.lang.String-Buffer that cause crashes under certain thread interleavings.

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.

...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.

The JalapeÃño Dynamic Optimizing Compiler is a key component of the JalapeÃño Virtual Machine, a new Java Virtual Machine (JVM) designed to support efficient and scalable execution of Java applications on SMP server machines. This paper describes the design of the JalapeÃño Optimizing Compiler, and the implementation results that we have obtained thus far. To the best of our knowledge, this is the first dynamic optimizing compiler for Java that is being used in a JVM with a compile-only approach to program execution.

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.

Abstract. Java programs perform many synchronization operations on data structures. Some of these synchronizations are unnecessary; in particular, if an object is reachable only by a single thread, concurrent access is impossible and no synchronization is needed. We describe a flow-insensitive, context-sensitive data-flow analysis that finds such situations and a global optimizing transformation that eliminates synchronizations on these objects. For every program in our suite of ten Java benchmarks consisting of SPECjvm98 and others, our system optimizes over 90 % of the alias sets containing at least one synchronized object. As a result, the dynamic frequency of synchronizations is reduced by up to 99%. For two benchmarks that perform synchronizations very frequently, this optimization leads to speedups of 36 % and 20%, respectively. 1.

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.