Localizing Defects in Multithreaded Programs by Mining Dynamic Call Graphs

Writing multithreaded software for multicore computers confronts many developers with the difficulty of finding parallel programming errors. In the past, most parallel debugging techniques have concentrated on finding race conditions due to wrong usage of synchronization constructs. A widely unexplored issue, however, is that a wrong usage of non-parallel programming constructs may also cause wrong parallel application behavior. This paper presents a novel defect-localization technique for multithreaded shared-memory programs that is based on analyzing execution anomalies. Compared to race detectors that report just on wrong synchronization, this method can detect a wider range of defects affecting parallel execution. It works on a condensed representation of the call graphs of multithreaded applications and employs data-mining techniques to locate a method containing a defect. Our results from controlled application experiments show that we found race conditions, but also other programming errors leading to incorrect parallel program behavior. On average, our approach reduced in our benchmark the amount of code to be inspected to just 7.1% of all methods

Lightweight Analysis of Object Interactions

The state of the practice in object-oriented software development has moved beyond reuse of code to reuse of conceptual structures such as design patterns. This paper draws attention to some difficulties that need to be solved if this style of development is to be supported by formal methods. In particular, the centrality of object interactions in many designs mak es traditional reasoning less useful, since classes cannot be treated fruitfully in isolation from one another. We propose some ideas towards dealing with these issues: a relational model of heap structure capable of expressing sharing and mutual influence between objects; a declarative specification style that work in the presence of collaboration; and a tool-supported constraint analysis to expose problems in a diagram that captures, at a design level, a pattern of interaction. We illustrate these ideas with an example tak en from a program used in the formatting of this paper

FRESA: A Frequency-Sensitive Sampling-Based Approach for Data Race Detection

Part 1: Session 1: Parallel Programming and AlgorithmsInternational audienceConcurrent programs are difficult to debug due to the inherent concurrence and indeterminism. One of the problems is race conditions. Previous work on dynamic race detection includes fast but imprecise methods that report false alarms, and slow but precise ones that never report false alarms. Some researchers have combined these two methods. However, the overhead is still massive. This paper exploits the insight that full record on detector is unnecessary in most cases. Even prior sampling method has something to do to reduce overhead with precision guaranteed. That is, we can use a frequency-sensitive sampling approach. With our model on sampling dispatch, we can drop most unnecessary detection overhead. Experiment results on DaCapo benchmarks show that our heuristic sampling race detector is performance-faster and overhead-lower than traditional race detectors with no loss in precision, while never reporting false alarms

CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs

Abstract. Active testing has recently been introduced to effectively test concurrent programs. Active testing works in two phases. It first uses predictive off-the-shelf static or dynamic program analyses to identify potential concurrency bugs, such as data races, deadlocks, and atomicity violations. In the second phase, active testing uses the reports from these predictive analyses to explicitly control the underlying scheduler of the concurrent program to accurately and quickly discover real concurrency bugs, if any, with very high probability and little overhead. In this paper, we present an extensible framework for active testing of Java programs. The framework currently implements three active testers based on data races, atomic blocks, and deadlocks.

A lightweight and portable approach to making concurrent failures reproducible

Abstract. Concurrent programs often exhibit bugs due to unintended interferences among the concurrent threads. Such bugs are often hard to reproduce because they typically happen under very specific interleaving of the executing threads. Basically, it is very hard to fix a bug (or software failure) in concurrent programs without being able to reproduce it. In this paper, we present an approach, called ConCrash, that automatically and deterministically reproduces concurrent failures by recording logical thread schedule and generating unit tests. For a given bug (failure), ConCrash records the logical thread scheduling order and preserves object states in memory at runtime. Then, ConCrash reproduces the failure offline by simply using the saved information without the need for JVM-level or OS-level support. To reduce the runtime performance overhead, ConCrash employs a static data race detection technique to report potential possible race conditions, and only instruments such places. We implement the ConCrash approach in a prototype tool for Java and experimented on a number of multi-threaded Java benchmarks. As a result, we successfully reproduced a number of real concurrent bugs (e.g., deadlocks, data races and atomicity violation) within an acceptable overhead.

Dependent types for program understanding

Abstract. Weakly-typed languages such as Cobol often force programmers to represent distinct data abstractions using the same low-level physical type. In this paper, we describe a technique to recover implicitlydefined data abstractions from programs using type inference. We present a novel system of dependent types which we call guarded types, a pathsensitive algorithm for inferring guarded types for Cobol programs, and a semantic characterization of correct guarded typings. The results of our inference technique can be used to enhance program understanding for legacy applications, and to enable a number of type-based program transformations.