Toward a methodology to expose partially fixed concurrency bugs in modified multithreaded programs

Software transactional memory is an effective mechanism to avoid concurrency bugs in multithreaded programs. However, two problems hinder the adoption of such traditional systems in the wild world: high human cost for equipping programs with transaction functionality and low compatibility with I/O calls and conditional variables. This paper presents Convoider to solve these problems. By intercepting interthread operations and designating code among them as transactions in each thread, Convoider automatically transactionalizes target programs without any source code modification and recompiling. By saving/restoring stack frames and CPU registers on beginning/aborting a transaction, Convoider makes execution flow revocable. By turning threads into processes, leveraging virtual memory protection and customizing memory allocation/deallocation, Convoider makes memory manipulations revocable. By maintaining virtual file systems and redirecting I/O operations onto them, Convoider makes I/O effects revocable. By converting lock/unlock operations to no-ops, customizing signal/wait operations on condition variables, and committing memory changes transactionally, Convoider makes deadlocks, data races, and atomicity violations impossible. Experimental results show that Convoider succeeds in transparently transactionalizing twelve real-world applications with averagely incurring only 28% runtime overhead and perfectly avoid 94% of thirty-one concurrency bugs used in our experiments. This study can help efficiently transactionalize legacy multithreaded applications and effectively improve the runtime reliability of them.

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An Efficient Algorithm for On-the-Fly Data Race Detection Using an Epoch-Based Technique

Scientific Programming ◽

10.1155/2015/205827 ◽

2015 ◽

Vol 2015 ◽

pp. 1-14 ◽

Cited By ~ 6

Author(s):

Ok-Kyoon Ha ◽

Yong-Kee Jun

Keyword(s):

Efficient Algorithm ◽

Data Race ◽

Concurrency Bugs ◽

Data Race Detection ◽

Detection Algorithms ◽

Race Detection ◽

Multithreaded Programs ◽

Memory Overhead ◽

Data Races ◽

Vector Clocks

Data races represent the most notorious class of concurrency bugs in multithreaded programs. To detect data races precisely and efficiently during the execution of multithreaded programs, the epoch-based FastTracktechnique has been employed. However, FastTrackhas time and space complexities that depend on the maximum parallelism of the program to partially maintain expensive data structures, such as vector clocks. This paper presents an efficient algorithm, callediFT, that uses only the epochs of the access histories. Unlike FastTrack, our algorithm requiresO(1)operations to maintain an access history and locate data races, without any switching between epochs and vector clocks. We implement this algorithm on top of the Pin binary instrumentation framework and compare it with other on-the-fly detection algorithms, including FastTrack, which uses a state-of-the-art happens-before analysis algorithm. Empirical results using the PARSEC benchmark show thatiFT reduces the average runtime and memory overhead to 84% and 37%, respectively, of those of FastTrack.

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ASN: A Dynamic Barrier-Based Approach to Confirmation of Deadlocks from Warnings for Large-Scale Multithreaded Programs

IEEE Transactions on Parallel and Distributed Systems ◽

10.1109/tpds.2014.2307864 ◽

2015 ◽

Vol 26 (1) ◽

pp. 13-23 ◽

Cited By ~ 10

Author(s):

Yan Cai ◽

Changjiang Jia ◽

Shangru Wu ◽

Ke Zhai ◽

Wing Kwong Chan

Keyword(s):

Large Scale ◽

Multithreaded Programs

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Platform Independent Analysis of Probabilities on Multithreaded Programs

International Journal of Software Innovation ◽

10.4018/ijsi.2013070104 ◽

2013 ◽

Vol 1 (3) ◽

pp. 48-65

Author(s):

Yuting Chen

Keyword(s):

Operating System ◽

Static Analysis ◽

Main Idea ◽

Experimental Results ◽

Machine To Machine ◽

Concurrent Program ◽

Acceptable Accuracy ◽

Multithreaded Programs ◽

Independent Analysis ◽

And Performance

A concurrent program is intuitively associated with probability: the executions of the program can produce nondeterministic execution program paths due to the interleavings of threads, whereas some paths can always be executed more frequently than the others. An exploration of the probabilities on the execution paths is expected to provide engineers or compilers with support in helping, either at coding phase or at compile time, to optimize some hottest paths. However, it is not easy to take a static analysis of the probabilities on a concurrent program in that the scheduling of threads of a concurrent program usually depends on the operating system and hardware (e.g., processor) on which the program is executed, which may be vary from machine to machine. In this paper the authors propose a platform independent approach, called ProbPP, to analyzing probabilities on the execution paths of the multithreaded programs. The main idea of ProbPP is to calculate the probabilities on the basis of two kinds of probabilities: Primitive Dependent Probabilities (PDPs) representing the control dependent probabilities among the program statements and Thread Execution Probabilities (TEPs) representing the probabilities of threads being scheduled to execute. The authors have also conducted two preliminary experiments to evaluate the effectiveness and performance of ProbPP, and the experimental results show that ProbPP can provide engineers with acceptable accuracy.

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