77,820 research outputs found

    Dynamic Data-Race Detection Through the Fine-Grained Lens

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    Data races are among the most common bugs in concurrency. The standard approach to data-race detection is via dynamic analyses, which work over executions of concurrent programs, instead of the program source code. The rich literature on the topic has created various notions of dynamic data races, which are known to be detected efficiently when certain parameters (e.g., number of threads) are small. However, the fine-grained complexity of all these notions of races has remained elusive, making it impossible to characterize their trade-offs between precision and efficiency. In this work we establish several fine-grained separations between many popular notions of dynamic data races. The input is an execution trace ? with ? events, ? threads and ? locks. Our main results are as follows. First, we show that happens-before HB races can be detected in O(?? min(?, ?)) time, improving over the standard O(?? ?) bound when ? = o(?). Moreover, we show that even reporting an HB race that involves a read access is hard for 2-orthogonal vectors (2-OV). This is the first rigorous proof of the conjectured quadratic lower-bound in detecting HB races. Second, we show that the recently introduced synchronization-preserving races are hard to detect for 3-OV and thus have a cubic lower bound, when ? = ?(?). This establishes a complexity separation from HB races which are known to be strictly less expressive. Third, we show that lock-cover races are hard for 2-OV, and thus have a quadratic lower-bound, even when ? = 2 and ? = ?(log ?). The similar notion of lock-set races is known to be detectable in O(?? ?) time, and thus we achieve a complexity separation between the two. Moreover, we show that lock-set races become hitting-set (HS)-hard when ? = ?(?), and thus also have a quadratic lower bound, when the input is sufficiently complex. To our knowledge, this is the first work that characterizes the complexity of well-established dynamic race-detection techniques, allowing for a rigorous comparison between them

    SmartTrack: Efficient Predictive Race Detection

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    Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur performance costs that are acceptable for regular in-house testing, but miss races detectable from the analyzed execution. Predictive analyses detect more data races in an analyzed execution than FastTrack detects, but at significantly higher performance cost. This paper presents SmartTrack, an algorithm that optimizes predictive race detection analyses, including two analyses from prior work and a new analysis introduced in this paper. SmartTrack's algorithm incorporates two main optimizations: (1) epoch and ownership optimizations from prior work, applied to predictive analysis for the first time; and (2) novel conflicting critical section optimizations introduced by this paper. Our evaluation shows that SmartTrack achieves performance competitive with FastTrack-a qualitative improvement in the state of the art for data race detection.Comment: Extended arXiv version of PLDI 2020 paper (adds Appendices A-E) #228 SmartTrack: Efficient Predictive Race Detectio

    Cultural modulation of face and gaze scanning in young children

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    Previous research has demonstrated that the way human adults look at others’ faces is modulated by their cultural background, but very little is known about how such a culture-specific pattern of face gaze develops. The current study investigated the role of cultural background on the development of face scanning in young children between the ages of 1 and 7 years, and its modulation by the eye gaze direction of the face. British and Japanese participants’ eye movements were recorded while they observed faces moving their eyes towards or away from the participants. British children fixated more on the mouth whereas Japanese children fixated more on the eyes, replicating the results with adult participants. No cultural differences were observed in the differential responses to direct and averted gaze. The results suggest that different patterns of face scanning exist between different cultures from the first years of life, but differential scanning of direct and averted gaze associated with different cultural norms develop later in life
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