ソフトウェアフォールトビッグデータから得られる信頼性学習と品質評価

田村 慶信; 山田 茂

doi:10.11487/oukan.2022.0_B-4-4

The 13th Conference on Transdisciplinary Science and Technology

Session ID : B-4

DOI https://doi.org/10.11487/oukan.2022.0_B-4-4

Conference information

Host: Transdisciplinary Federation of Science and Technology

Name : The 13th Conference on Transdisciplinary Science and Technology

Number : 13

Location : [in Japanese]

Date : December 17, 2022 - December 18, 2022

Reliability Learning and Quality Assessment Obtained from Software Fault Big Data

*Yoshinobu TAMURA, Shigeru YAMADA

Author information

Keywords: Software fault, big data, deep learning

CONFERENCE PROCEEDINGS OPEN ACCESS

Details

Abstract

At present, the open architecture is widespread in various research areas. Especially, many open source software are used in the software engineering because of the standardization and cost reduction. In this research, we discuss the reliability learning and quality assessment obtained from software fault big data.

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