Multithreaded programming is notoriously difficult to get right. A key problem is non-determinism, which complicates debugging, testing, and reproducing errors. One way to simplify multithreaded programming is to enforce deterministic execution, but current deterministic systems for C/C++ are incomplete or impractical. These systems require program modification, do not ensure determinism in the presence of data races, do not work with generalpurpose multithreaded programs, or run up to 8.4 × slower than pthreads. This paper presents DTHREADS, an efficient deterministic multithreading system for unmodified C/C++ applications that replaces the pthreads library. DTHREADS enforces determinism in the face of data races and deadlocks. DTHREADS works by exploding multithreaded applications into multiple processes, with private, copy-on-write mappings to shared memory. It uses standard virtual memory protection to track writes, and deterministically orders updates by each thread. By separating updates from different threads, DTHREADS has the additional benefit of eliminating false sharing. Experimental results show that DTHREADS substantially outperforms a state-of-the-art deterministic runtime system, and for a majority of the benchmarks evaluated here, matches and occasionally exceeds the performance of pthreads. 1.

Concurrency bugs are caused by non-deterministic interleavings between shared memory accesses. Their effects propagate through data and control dependences until they cause software to crash, hang, produce incorrect output, etc. The lifecycle of a bug thus consists of three phases: (1) triggering, (2) propagation, and (3) failure. Traditional techniques for detecting concurrency bugs mostly focus on phase (1)—i.e., on finding certain structural patterns of interleavings that are common triggers of concurrency bugs, such as data races. This paper explores a consequence-oriented approach to improving the accuracy and coverage of state-space search and bug detection. The proposed approach first statically identifies potential failure sites in a program binary (i.e., it first considers a phase (3) issue). It then uses static slicing to identify critical read instructions that are highly likely to affect potential failure sites through control and data dependences (phase (2)). Finally, it monitors a single (correct) execution of a concurrent program and identifies suspicious interleavings that could cause an incorrect state to arise at a critical read and then lead to a software failure (phase (1)). ConSeq’s backwards approach, (3)→(2)→(1), provides advantages in bug-detection coverage and accuracy but is challenging to carry out. ConSeq makes it feasible by exploiting the empirical observation that phases (2) and (3) usually are short and occur within one thread. Our evaluation on large, real-world C/C++ applications shows that ConSeq detects more bugs than traditional approaches and has a much lower false-positive rate. D.2.5 [Testing and Debug-

Fixing software bugs has always been an important and timeconsuming process in software development. Fixing concurrency bugs has become especially critical in the multicore era. However, fixing concurrency bugs is challenging, in part due to nondeterministic failures and tricky parallel reasoning. Beyond correctly fixing the original problem in the software, a good patch should also avoid introducing new bugs, degrading performance unnecessarily, or damaging software readability. Existing tools cannot automate the whole fixing process and provide good-quality patches. We present AFix, a tool that automates the whole process of fixing one common type of concurrency bug: single-variable atomicity violations. AFix starts from the bug reports of existing bugdetection tools. It augments these with static analysis to construct a suitable patch for each bug report. It further tries to combine the patches of multiple bugs for better performance and code readability. Finally, AFix’s run-time component provides testing customized for each patch. Our evaluation shows that patches automatically generated by AFix correctly eliminate six out of eight real-world bugs and significantly decrease the failure probability in the other two cases. AFix patches never introduce new bugs and usually have similar performance to manually-designed patches.

Deterministic multithreading (DMT) eliminates many pernicious software problems caused by nondeterminism. It works by constraining a program to repeat the same thread interleavings, or schedules, when given same input. Despite much recent research, it remains an open challenge to build both deterministic and efficient DMT systems for general programs on commodity hardware. To deterministically resolve a data race, a DMT system must enforce a deterministic schedule of shared memory accesses, or memschedule, which can incur prohibitive overhead. By using schedules consisting only of synchronization operations, or sync-schedule, this overhead can be avoided. However, a sync-schedule is deterministic only for race-free programs, but most programs have races. Our key insight is that races tend to occur only within minor portions of an execution, and a dominant majority of the execution

Testing multithreaded programs is difficult as threads can interleave in a nondeterministic fashion. Untested interleavings can cause failures, but testing all interleavings is infeasible. Many interleaving exploration strategies for bug detection have been proposed, but their relative effectiveness and performance remains unclear as they often lack publicly available implementations and have not been evaluated using common benchmarks. We describe NeedlePoint, an open-source framework that allows selection and comparison of a wide range of interleaving exploration policies for bug detection proposed by prior work. Our experience with NeedlePoint indicates that priority-based probabilistic concurrency testing (the PCT algorithm) finds bugs quickly, but it runs only one thread at a time, which destroys parallelism by serializing executions. To address this problem we propose a parallel version of the PCT algorithm (PPCT). We show that the new algorithm outperforms the original by a factor of 5 × when testing parallel programs on an eight-core machine. We formally prove that parallel PCT provides the same probabilistic coverage guarantees as PCT. Moreover, PPCT is the first algorithm that runs multiple threads while providing coverage guarantees. D.2.5 [Software Engineer-

Abstract: The scalability of multithreaded applications on current multicore systems is hampered by the performance of critical sections, due in particular to the costs of access contention and cache misses. In this paper, we propose a new locking technique, Remote Core Locking (RCL) that aims to improve the performance of critical sections in legacy applications on multicore architectures. The idea of RCL is to replace lock acquisitions by optimized remote procedure calls to a dedicated server core. RCL limits the performance collapse observed with regular locks when many threads try to acquire a lock concurrently and removes the need to transfer lock-protected shared data to the core acquiring the lock: such data can typically remain in the server core's cache. Our microbenchmark shows that under high contention, RCL is always more e cient than the other state-of-the-art lock mechanisms, and a preliminary macrobenchmark evaluation shows performance gains on SPLASH-2 benchmarks (speedup up to 4.85) and on the Web cache application memcached (speedup up to 2.62). Key-words:

We conduct a comprehensive study of file-system code evolution. By analyzing eight years of Linux file-system changes across 5079 patches, we derive numerous new (and sometimes surprising) insights into the file-system development process; our results should be useful for both the development of file systems themselves as well as the improvement of bug-finding tools. 1