The Art and Science of Analyzing Software Data; Quantitative Methods

被引:2
|
作者
Menzies, Tim [1 ]
Minku, Leandro [2 ]
Peters, Fayola [3 ]
机构
[1] North Carolina State Univ, Comp Sci, Raleigh, NC USA
[2] Univ Birmingham, Comptuer Sci, Birmingham B15 2TT, W Midlands, England
[3] Univ Limmerick, Lero, Limerick, Ireland
关键词
D O I
10.1109/ICSE.2015.306
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Using the tools of quantitative data science, software engineers that can predict useful information on new projects based on past projects. This tutorial reflects on the state-of-the-art in quantitative reasoning in this important field. This tutorial discusses the following: (a) when local data is scarce, we show how to adapt data from other organizations to local problems; (b) when working with data of dubious quality, we show how to prune spurious information; (c) when data or models seem too complex, we show how to simplify data mining results; (d) when the world changes, and old models need to be updated, we show how to handle those updates; (e) when the effect is too complex for one model, we show to how reason over ensembles.
引用
收藏
页码:959 / 960
页数:2
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