NDLI: Multi-extract and multi-level dataset of mozilla issue tracking history

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Multi-extract and multi-level dataset of mozilla issue tracking history

Content Provider	ACM Digital Library
Author	Zhu, Jiaxin Mei, Hong Zhou, Minghui
Abstract	any studies analy e issue trac ing repositories to understand and support software development To facilitate the analyses we share a o illa issue trac ing dataset covering a -year history The dataset includes three e tracts and multiple levels for each e tract The three e tracts were retrieved through two channels a front-end we user interface I and a ac -end o cial data ase dump of o illa ug illa at three di erent times The variations dynamics among e tracts provide space for researchers to reproduce and validate their studies while revealing potential opportunities for studies that otherwise could not e conducted e provide di erent data levels for each e tract ranging from raw data to standardi ed data as well as to the calculated data level for targeting speci c research uestions Data retrieving and processing scripts related to each data level are o ered too y employing the multi-level structure analysts can more e ciently start an in uiry from the standardi ed level and easily trace the data chain when necessary e g to verify if a phenomenon re ected y the data is an actual event e applied this dataset to several pu lished studies and intend to e pand the multi-level and multi-e tract feature to other software engineering datasets.
Starting Page	472
Ending Page	475
Page Count	4
File Format	PDF
ISBN	9781450341868
DOI	10.1145/2901739.2903502
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-05-14
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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