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| Presentation | 2024-01-24 15:40 Improvement of learning method using intermediate representation in machine learning method for code smell detection Risa Hirahara, Tomoji Kishi (Waseda Univ.)  KBSE2023-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years，methods for detecting code smells have mainly been researched using machine learning．However，the disadvantage of machine learning methods is that they are difficult to apply to various programming languages．As a result，most methods using machine learning target a single language，making it difficult to actually apply them to real-world applications written in multiple programming languages．Therefore，in this research，we propose a method that uses LLVM-IR，which is intermediate between source code and binary code that can be generated from various languages，as training data．By changing the learning data from conventional ones，we will improve the versatility of machine learning methods for programming languages，and make proposals for practical use of machine learning methods. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Intermediate Representation / Code Smell / Machine Learning / LLVM-IR / metrics / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 352, KBSE2023-64, pp. 79-84, Jan. 2024. | |
| Paper # | KBSE2023-64 | |
| Date of Issue | 2024-01-16 (KBSE) | |
| 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) | |
| Download PDF | KBSE2023-64 |
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| Conference Information | |
| Committee | KBSE |
| Conference Date | 2024-01-23 - 2024-01-24 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | KBSE |
| Conference Code | 2024-01-KBSE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of learning method using intermediate representation in machine learning method for code smell detection |
| Sub Title (in English) | |
| Keyword(1) | Intermediate Representation |
| Keyword(2) | Code Smell |
| Keyword(3) | Machine Learning |
| Keyword(4) | LLVM-IR |
| Keyword(5) | metrics |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Risa Hirahara |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Tomoji Kishi |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
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| Speaker | Author-1 |
| Date Time | 2024-01-24 15:40:00 |
| Presentation Time | 30 minutes |
| Registration for | KBSE |
| Paper # | KBSE2023-64 |
| Volume (vol) | vol.123 |
| Number (no) | no.352 |
| Page | pp.79-84 |
| #Pages | 6 |
| Date of Issue | 2024-01-16 (KBSE) |
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