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User-Guided Dynamic Data Race Detection.

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Τίτλος: User-Guided Dynamic Data Race Detection.
Συγγραφείς: Metzger, Markus1 markus.t.metzger@intel.com, Tian, Xinmin xinmin.tian@intel.com, Tedeschi, Walfred1 walfred.tedeschi@intel.com
Πηγή: International Journal of Parallel Programming. Apr2015, Vol. 43 Issue 2, p159-179. 21p.
Θεματικοί όροι: *Computer software development, *Workflow, *Dynamic programming, Threads (Computer programs), Debugging
Περίληψη: Multi-threaded programming is part of mainstream software development. It adds several issues not present on serial applications. Among the issues an important one is data races, i.e. the unsynchronized access of data by multiple threads. They are particularly hard to debug since they typically occur sporadically and often invisibly corrupt the internal state. Generally, the tool used to identify those kinds of issues is a data race analyzer. Due to the subtlety of data race bugs, the user at this point would already have tried to understand the problem using an application debugger. Debuggers offer a variety of features to analyze and modify the execution state of programs. Such features are typically not offered by data race analyzers. Integrating a data race analyzer into a debugger would improve the user workflow. This is usually prohibited by the huge performance overhead of a whole-program data race analysis. We propose in this work a method to reduce the overhead by allowing the user to define the scope of the analysis. A sufficiently narrow scope reduces the performance overhead to less than 5 $$\times $$ , thus allowing its integration into a debugger. Defining the analysis scope fits naturally into the debugger workflow of focusing on one problem at a time. The work here presented has been implemented in a commercial debugger product. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  – Url: https://dx.doi.org/doi:10.1007/s10766-013-0296-z
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  Data: User-Guided Dynamic Data Race Detection.
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  Data: <searchLink fieldCode="AR" term="%22Metzger%2C+Markus%22">Metzger, Markus</searchLink><relatesTo>1</relatesTo><i> markus.t.metzger@intel.com</i><br /><searchLink fieldCode="AR" term="%22Tian%2C+Xinmin%22">Tian, Xinmin</searchLink><i> xinmin.tian@intel.com</i><br /><searchLink fieldCode="AR" term="%22Tedeschi%2C+Walfred%22">Tedeschi, Walfred</searchLink><relatesTo>1</relatesTo><i> walfred.tedeschi@intel.com</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Parallel+Programming%22">International Journal of Parallel Programming</searchLink>. Apr2015, Vol. 43 Issue 2, p159-179. 21p.
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– Name: Abstract
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  Data: Multi-threaded programming is part of mainstream software development. It adds several issues not present on serial applications. Among the issues an important one is data races, i.e. the unsynchronized access of data by multiple threads. They are particularly hard to debug since they typically occur sporadically and often invisibly corrupt the internal state. Generally, the tool used to identify those kinds of issues is a data race analyzer. Due to the subtlety of data race bugs, the user at this point would already have tried to understand the problem using an application debugger. Debuggers offer a variety of features to analyze and modify the execution state of programs. Such features are typically not offered by data race analyzers. Integrating a data race analyzer into a debugger would improve the user workflow. This is usually prohibited by the huge performance overhead of a whole-program data race analysis. We propose in this work a method to reduce the overhead by allowing the user to define the scope of the analysis. A sufficiently narrow scope reduces the performance overhead to less than 5 $$\times $$ , thus allowing its integration into a debugger. Defining the analysis scope fits naturally into the debugger workflow of focusing on one problem at a time. The work here presented has been implemented in a commercial debugger product. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10766-013-0296-z
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 159
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      – SubjectFull: Computer software development
        Type: general
      – SubjectFull: Workflow
        Type: general
      – SubjectFull: Dynamic programming
        Type: general
      – SubjectFull: Threads (Computer programs)
        Type: general
      – SubjectFull: Debugging
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      – TitleFull: User-Guided Dynamic Data Race Detection.
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              Text: Apr2015
              Type: published
              Y: 2015
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