Paper Abstract and Keywords |
Presentation |
2020-10-16 13:25
Comparison of Goodness-of-Fit for the EVM Based on Deep Learning for OSS Kohjiro Tada, Tamura Yosinobu (Tokyo City Univ), Ymada Sigeru (Tottori Univ) R2020-20 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Currently, a lot of open source software are developed. On the other hand, there is a problem that it is difficult to manage the progress of open source projects because of the distributed development environment by using the unique development style. In this paper. we propose the method of progress management for actual open source software based on deep learning. Mainly, we aim to improve the existing method in order to assess the progress of open source projects by EVM (Earned Value Management). We show numerical examples of the evaluation index of EVM using the fault data of actual open source software. Furthermore, we compare the existing method with the proposed method in this paper. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep learning / Open Source Software / Development Effort / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 191, R2020-20, pp. 7-12, Oct. 2020. |
Paper # |
R2020-20 |
Date of Issue |
2020-10-09 (R) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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R2020-20 |
Conference Information |
Committee |
R |
Conference Date |
2020-10-16 - 2020-10-16 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Reliability of Information Communication System, Reliability General |
Paper Information |
Registration To |
R |
Conference Code |
2020-10-R |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Comparison of Goodness-of-Fit for the EVM Based on Deep Learning for OSS |
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Deep learning |
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Open Source Software |
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Development Effort |
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1st Author's Name |
Kohjiro Tada |
1st Author's Affiliation |
Tokyo City University (Tokyo City Univ) |
2nd Author's Name |
Tamura Yosinobu |
2nd Author's Affiliation |
Tokyo City University (Tokyo City Univ) |
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Ymada Sigeru |
3rd Author's Affiliation |
Tottori University (Tottori Univ) |
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Speaker |
Author-1 |
Date Time |
2020-10-16 13:25:00 |
Presentation Time |
25 minutes |
Registration for |
R |
Paper # |
R2020-20 |
Volume (vol) |
vol.120 |
Number (no) |
no.191 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2020-10-09 (R) |
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