2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) 2016
DOI: 10.1109/icis.2016.7550866
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A case study on the misclassification of software performance issues in an issue tracking system

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Cited by 5 publications
(3 citation statements)
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“…Similar research to ours is bug classification (Maalej and Nabil 2015;Herzig et al 2013;Ohira et al 2016). Some research targets emerging applications, such as TensorFlow bugs (Zhang et al 2018) and Blockchain bugs (Wan et al 2017), while others target distributed systems such as node change bugs (Lu et al 2019) and concurrency bugs (Lu et al 2008).…”
Section: Software Bugs and Classificationmentioning
confidence: 75%
“…Similar research to ours is bug classification (Maalej and Nabil 2015;Herzig et al 2013;Ohira et al 2016). Some research targets emerging applications, such as TensorFlow bugs (Zhang et al 2018) and Blockchain bugs (Wan et al 2017), while others target distributed systems such as node change bugs (Lu et al 2019) and concurrency bugs (Lu et al 2008).…”
Section: Software Bugs and Classificationmentioning
confidence: 75%
“…Similar research to ours is bug classification [34,24,42]. Some research targets emerging applications, such as TensorFlow bugs [70] and Blockchain bugs [60], while others target distributed systems such as node change bugs [31] and concurrency bugs [32].…”
Section: Related Workmentioning
confidence: 99%
“…On the search for realistic and documented performance bugs, researchers typically resort to mining software repositories and bug tracking systems [3]- [7]. However, this is a timeconsuming and error-prone task that inevitably requires the manual inspection of the issue's records, for example, to detect false positives (e.g., misclassified issues), and to understand the bug, its cause, the source code (if available), and the fix (if any) [8].…”
Section: Introductionmentioning
confidence: 99%