The reliability of infrastructure software, such as operating systems and web servers, is often hampered by the mismanagement of resources, such as memory and network connections. The Vault programming language allows a programmer to describe resource management protocols that the compiler can statically enforce. Such a protocol can specify that operations must be performed in a certain order and that certain operations must be performed before accessing a given data object. Furthermore, Vault enforces statically that resources cannot be leaked. We validate the utility of our approach by enforcing protocols present in the interface between the Windows 2000 kernel and its device drivers.

We present a system for extending standard type systems with flow-sensitive type qualifiers. Users annotate their programs with type qualifiers, and inference checks that the annotations are correct. In our system only the type qualifiers are modeled flow-sensitively - the underlying standard types are unchanged, which allows us to obtain an efficient constraint-based inference algorithm that integrates flow-insensitive alias analysis, effect inference, and ideas from linear type systems to support strong updates. We demonstrate the usefulness of flow-sensitive type qualifiers by finding a number of new locking bugs in the Linux kernel.

This paper presents a new static type system for multi-threaded programs; well-typed programs in our system are guaranteed to be free of data races and deadlocks. Our type system allows programmers to partition the locks into a fixed number of equivalence classes and specify a partial order among the equivalence classes. The type checker then statically verifies that whenever a thread holds more than one lock, the thread acquires the locks in the descending order. Our system also allows...

This paper describes RacerX, a static tool that uses flowsensitive, interprocedural analysis to detect both race conditions and deadlocks. It is explicitly designed to find errors in large, complex multithreaded systems. It aggressively infers checking information such as which locks protect which operations, which code contexts are multithreaded, and which shared accesses are dangerous. It tracks a set of code features which it uses to sort errors both from most to least severe. It uses novel techniques to counter the impact of analysis mistakes. The tool is fast, requiring between 2-14 minutes to analyze a 1.8 million line system. We have applied it to Linux, FreeBSD, and a large commercial code base, finding serious errors in all of them.

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.

This paper presents a novel approach to bug-finding analysis and an implementation of that approach. Our goal is to find as many serious bugs as possible. To do so, we designed a flexible, easy-to-use extension language for specifying analyses and an efficent algorithm for executing these extensions. The language, metal, allows the users of our system to specify a broad class of analyses in terms that resemble the intuitive description of the rules that they check. The system, xgcc, executes these analyses efficiently using a context-sensitive, interprocedural 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.

Ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected interactions between concurrent threads. We focus on the fundamental non-interference property of atomicity and present a dynamic analysis for detecting atomicity violations. This analysis combines ideas from both Lipton’s theory of reduction and earlier dynamic race detectors such as Eraser. Experimental results demonstrate that this dynamic atomicity analysis is effective for detecting errors due to unintended interactions between threads. In addition, the majority of methods in our benchmarks are atomic, supporting our hypothesis that atomicity is a standard methodology in multithreaded programming. 1 The Need for Atomicity Multiple threads of control are widely used in software development because they help reduce latency and provide better utilization of multiprocessor machines. However, reasoning about the correctness of multithreaded code is complicated by the nondeterministic interleaving of threads and the potential for unexpected interference between concurrent threads. Since exploring all possible interleavings of the executions of the various threads is clearly impractical, methods for specifying and controlling the interference between concurrent threads are crucial for the development of reliable multithreaded software. Much previous work on controlling thread interference has focused on race conditions, which occur when two threads simultaneously access the same data variable, and at least one of the accesses is a write [1]. Unfortunately, the absence of race conditions is not sufficient to ensure the absence of errors due to unexpected interference between threads. As a concrete illustration of

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 article presents EXE, an effective bug-finding tool that automatically generates inputs that crash real code. Instead of running code on manually or randomly constructed input, EXE runs it on symbolic input initially allowed to be anything. As checked code runs, EXE tracks the constraints on each symbolic (i.e., input-derived) memory location. If a statement uses a symbolic value, EXE does not run it, but instead adds it as an input-constraint; all other statements run as usual. If code conditionally checks a symbolic expression, EXE forks execution, constraining the expression to be true on the true branch and false on the other. Because EXE reasons about all possible values on a path, it has much more power than a traditional runtime tool: (1) it can force execution down any feasible program path and (2) at dangerous operations (e.g., a pointer dereference), it detects if the current path constraints allow any value that causes a bug. When a path terminates or hits a bug, EXE automatically generates a test case by solving the current path constraints to find concrete values using its own co-designed constraint solver, STP. Because EXE’s constraints have no approximations, feeding this concrete input to an uninstrumented version of the checked code will cause it to follow the same path and hit the same bug (assuming deterministic code).