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Improving Software Development Management through Software Project Telemetry
July/August 2005 (vol. 22 no. 4)
pp. 76-85
ASCII Text
x 
 
Philip M. Johnson, Hongbing Kou, Michael Paulding, Qin Zhang, Aaron Kagawa, Takuya Yamashita, "Improving Software Development Management through Software Project Telemetry," IEEE Software, vol. 22, no. 4, pp. 76-85, July/August, 2005.
 
 
BibTex
x
 
@article{ 10.1109/MS.2005.95,
author = {Philip M. Johnson and Hongbing Kou and Michael Paulding and Qin Zhang and Aaron Kagawa and Takuya Yamashita},
title = {Improving Software Development Management through Software Project Telemetry},
journal ={IEEE Software},
volume = {22},
number = {4},
issn = {0740-7459},
year = {2005},
pages = {76-85},
doi = {http://doi.ieeecomputersociety.org/10.1109/MS.2005.95},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Software
TI - Improving Software Development Management through Software Project Telemetry
IS - 4
SN - 0740-7459
SP76
EP85
EPD - 76-85
A1 - Philip M. Johnson,
A1 - Hongbing Kou,
A1 - Michael Paulding,
A1 - Qin Zhang,
A1 - Aaron Kagawa,
A1 - Takuya Yamashita,
PY - 2005
KW - automated software metrics collection and analysis
KW - software project telemetry
VL - 22
JA - IEEE Software
ER -
 
Philip M. Johnson, University of Hawaii
Hongbing Kou, University of Hawaii
Michael Paulding, University of Hawaii
Qin Zhang, University of Hawaii
Aaron Kagawa, University of Hawaii
Takuya Yamashita, University of Hawaii
Software project telemetry is a new approach to software project management in which sensors are attached to development environment tools to unobtrusively monitor the development process and products. This sensor data is abstracted into high-level perspectives on development trends called telemetry reports, which give project members useful insights for local, in-process decision making. This article presents software project telemetry's essential characteristics, contrasts it to other approaches such as predictive models based upon historical software project data, describes a reference framework implementation called Hackystat, and presents the authors' lessons learned so far.
Index Terms:
automated software metrics collection and analysis, software project telemetry
Citation:
Philip M. Johnson, Hongbing Kou, Michael Paulding, Qin Zhang, Aaron Kagawa, Takuya Yamashita, "Improving Software Development Management through Software Project Telemetry," IEEE Software, vol. 22, no. 4, pp. 76-85, July/Aug. 2005, doi:10.1109/MS.2005.95
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