Code Commentary and Automatic Refactorings using Feedback from Multiple Compilers

  • Nicklas Bo Jensen, Christian W. Probst, and Sven Karlsson. Code Commentary and Automatic Refactorings using Feedback from Multiple Compilers. In Proceedings of the Swedish Workshop on Multicore Computing (MCC), Lund, Sweden, 2014.
    [BibTeX] [Abstract] [Download PDF]

    Optimizing compilers are essential to the performance of parallel programs on multi-core systems. It is attractive to expose parallelism to the compiler letting it do the heavy lifting. Unfortunately, it is hard to write code that compilers are able to optimize aggressively and therefore tools exist that can guide programmers with refactorings allowing the compilers to optimize more aggressively. We target the problem with many false positives that these tools often generate, where the amount of feedback can be overwhelming for the programmer. Our approach is to use a filtering scheme based on feedback from multiple compilers and show how we are able to filter out 87.6% of the comments by only showing the most promising comments.

    @InProceedings{2014-11-JENSEN-2,
    author = {Nicklas Bo Jensen and Christian W. Probst and Sven Karlsson},
    title = {{Code Commentary and Automatic Refactorings using Feedback from Multiple Compilers}},
    booktitle = {{Proceedings of the Swedish Workshop on Multicore Computing (MCC)}},
    date = {2014-11-27/2014-11-28},
    address = {Lund, Sweden},
    url = {http://orbit.dtu.dk/en/publications/code-commentary-and-automatic-refactorings-using-feedback-from-multiple-compilers(47725fbb-1c72-47fa-a167-32ae319d5a0d).html},
    abstract = {Optimizing compilers are essential to the performance of parallel programs on multi-core systems. It is attractive to expose parallelism to the compiler letting it do the heavy lifting. Unfortunately, it is hard to write code that compilers are able to optimize aggressively and therefore tools exist that can guide programmers with refactorings allowing the compilers to optimize more aggressively. We target the problem with many false positives that these tools often generate, where the amount of feedback can be overwhelming for the programmer. Our approach is to use a filtering scheme based on feedback from multiple compilers and show how we are able to filter out 87.6% of the comments by only showing the most promising comments.},
    year = {2014}
    }

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