Software Engineering Meets Deep Learning: A Mapping Study

被引：16

作者：

Ferreira, Fabio ^{[1
]}

Silva, Luciana Lourdes ^{[2
]}

Valente, Marco Tulio ^{[3
]}

机构：

[1] Fed Inst Southeast Minas Gerais IF Sudeste MG, Ctr Informat, Barbacena, Brazil

[2] Fed Inst Minas Gerais IFMG, Dept Comp, Ouro Branco, Brazil

[3] Fed Univ Minas Gerais UFMG, Dept Comp Sci, ASERG Grp, Belo Horizonte, MG, Brazil

来源：

36TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2021 | 2021年

关键词：

Software Engineering; Deep Learning;

D O I：

10.1145/3412841.3442029

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Deep Learning (DL) is being used nowadays in many traditional Software Engineering (SE) problems and tasks. However, since the renaissance of DL techniques is still very recent, we lack works that summarize and condense the most recent and relevant research conducted at the intersection of DL and SE. Therefore, in this paper, we describe the first results of a mapping study covering 81 papers about DL & SE. Our results confirm that DL is gaining momentum among SE researchers over the years and that the top-3 research problems tackled by the analyzed papers are documentation, defect prediction, and testing.

引用

页码：1542 / 1549

页数：8

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