Towards Automated Performance Bug Identification in Python

@article{Tsakiltsidis2016TowardsAP,
  title={Towards Automated Performance Bug Identification in Python},
  author={Sokratis Tsakiltsidis and Andriy V. Miranskyy and Elie Mazzawi},
  journal={ArXiv},
  year={2016},
  volume={abs/1607.08506}
}
  • Sokratis Tsakiltsidis, Andriy V. Miranskyy, Elie Mazzawi
  • Published in ArXiv 2016
  • Computer Science
  • Context : Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems. In this work we focused on early detection of performance bugs; our software under study was a real time system used in the advertisement / marketing domain. Goal : Find a simple and easy to implement solution, predicting performance bugs. Method : We built several models using four machine learning methods, commonly used for… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 45 REFERENCES

    Myths of Enterprise Python — PayPal Engineering Blog. https://www.paypal-engineering.com/2014/ 12/10/10-myths-of-enterprise-python/, last accessed 2016-05-14

    • M. Hashemi
    • 2016
    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Learning from Imbalanced Data

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    The WEKA data mining software: an update

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Security versus performance bugs: a case study on Firefox

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Continuous integration. http: //martinfowler.com/articles/continuousIntegration.html, last accessed 2016-01-07

    • M. Fowler, M. Foemmel
    • 2016
    VIEW 1 EXCERPT

    An Industrial Case Study on the Automated Detection of Performance Regressions in Heterogeneous Environments

    VIEW 1 EXCERPT

    CARAMEL: Detecting and Fixing Performance Problems That Have Non-Intrusive Fixes

    VIEW 1 EXCERPT

    Online Defect Prediction for Imbalanced Data

    VIEW 2 EXCERPTS

    corrgram: Plot a Correlogram, http://CRAN.R-project. org/package=corrgram, 2015, r package version 1.7

    • K. Wright
    • 2015
    VIEW 1 EXCERPT