Smart ULT Management for Ultra-Large-Scale Software
N. Luo. International Journal of Software Engineering & Applications (IJSEA), 13 (4):
15-22(Juli 2022)
Zusammenfassung
The importance of development ULT (unit level test) is of no doubt today. But deployment of ULT in ultralarge-scale software till sufficient coverage requires big development effort while it could be hard for
developers to precisely identify the error prone logics deserving the best test coverage. In this paper, we
propose one novel Smart ULT Management system or automatic ULT deployment on ultra-large-scale
software which can provide the test coverage recommendation, and automatically generate >80% ULT
code. It helps us greatly shrink the average ULT code development effort from ~24 Man hours to ~3 Man
hours per 1000 Lines of driver under test. We hope the experience shared can help more practitioners to apply the similar methodology.
%0 Journal Article
%1 luosmart
%A Luo, Ning
%D 2022
%E Inukollu, Venkata N
%J International Journal of Software Engineering & Applications (IJSEA)
%K Unit level test
%N 4
%P 15-22
%T Smart ULT Management for Ultra-Large-Scale Software
%U https://aircconline.com/ijsea/V13N4/13422ijsea02.pdf
%V 13
%X The importance of development ULT (unit level test) is of no doubt today. But deployment of ULT in ultralarge-scale software till sufficient coverage requires big development effort while it could be hard for
developers to precisely identify the error prone logics deserving the best test coverage. In this paper, we
propose one novel Smart ULT Management system or automatic ULT deployment on ultra-large-scale
software which can provide the test coverage recommendation, and automatically generate >80% ULT
code. It helps us greatly shrink the average ULT code development effort from ~24 Man hours to ~3 Man
hours per 1000 Lines of driver under test. We hope the experience shared can help more practitioners to apply the similar methodology.
@article{luosmart,
abstract = {The importance of development ULT (unit level test) is of no doubt today. But deployment of ULT in ultralarge-scale software till sufficient coverage requires big development effort while it could be hard for
developers to precisely identify the error prone logics deserving the best test coverage. In this paper, we
propose one novel Smart ULT Management system or automatic ULT deployment on ultra-large-scale
software which can provide the test coverage recommendation, and automatically generate >80% ULT
code. It helps us greatly shrink the average ULT code development effort from ~24 Man hours to ~3 Man
hours per 1000 Lines of driver under test. We hope the experience shared can help more practitioners to apply the similar methodology.
},
added-at = {2023-08-29T11:53:23.000+0200},
author = {Luo, Ning},
biburl = {https://www.bibsonomy.org/bibtex/22e509404a85cd50ab407741a03d94ab4/janurichie_123},
editor = {Inukollu, Venkata N},
interhash = {f5afe6b7de2ee8d836a5a44c18d7cdec},
intrahash = {2e509404a85cd50ab407741a03d94ab4},
issn = {0975-9018},
journal = {International Journal of Software Engineering & Applications (IJSEA)},
keywords = {Unit level test},
language = {English},
month = {July},
number = 4,
pages = {15-22},
timestamp = {2023-08-29T11:53:23.000+0200},
title = {Smart ULT Management for Ultra-Large-Scale Software},
url = {https://aircconline.com/ijsea/V13N4/13422ijsea02.pdf},
volume = 13,
year = 2022
}