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Empirically Guided Software Effort Guesstimation
November/December 2000 (vol. 17 no. 6)
pp. 51-56
ASCII Text
x 
 
Philip M. Johnson, Carleton A. Moore, Joseph A. Dane, Robert S. Brewer, "Empirically Guided Software Effort Guesstimation," IEEE Software, vol. 17, no. 6, pp. 51-56, November/December, 2000.
 
 
BibTex
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@article{ 10.1109/52.895168,
author = {Philip M. Johnson and Carleton A. Moore and Joseph A. Dane and Robert S. Brewer},
title = {Empirically Guided Software Effort Guesstimation},
journal ={IEEE Software},
volume = {17},
number = {6},
issn = {0740-7459},
year = {2000},
pages = {51-56},
doi = {http://doi.ieeecomputersociety.org/10.1109/52.895168},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Software
TI - Empirically Guided Software Effort Guesstimation
IS - 6
SN - 0740-7459
SP51
EP56
EPD - 51-56
A1 - Philip M. Johnson,
A1 - Carleton A. Moore,
A1 - Joseph A. Dane,
A1 - Robert S. Brewer,
PY - 2000
VL - 17
JA - IEEE Software
ER -
 
Project LEAP at the University of Hawaii is investigating tools and methods to support low-cost, empirically based software developer improvement. A recent case study provides evidence that guesstimates, when informed by low-cost analytical methods, might be the most accurate method.
Citation:
Philip M. Johnson, Carleton A. Moore, Joseph A. Dane, Robert S. Brewer, "Empirically Guided Software Effort Guesstimation," IEEE Software, vol. 17, no. 6, pp. 51-56, Nov./Dec. 2000, doi:10.1109/52.895168
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