48 citations · 61 across the 6 of their papers we have counts for
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cs.SE2018
On the Need of Preserving Order of Data When Validating Within-Project Defect Classifiers
Davide Falessi, Jacky Huang, Likhita Narayana +2
[Context] The use of defect prediction models, such as classifiers, can support testing resource allocations by using data of the previous releases of the same project for predicti…
cs.SE2018
Leveraging Historical Associations between Requirements and Source Code to Identify Impacted Classes
Davide Falessi, Justin Roll, Jin Guo +1
As new requirements are introduced and implemented in a software system, developers must identify the set of source code classes which need to be changed. Therefore, past effort ha…
cs.LG2018★ 11 cited
Optimizing Prediction Intervals by Tuning Random Forest via Meta-Validation
Sean Bayley, Davide Falessi
Recent studies have shown that tuning prediction models increases prediction accuracy and that Random Forest can be used to construct prediction intervals. However, to our best kno…