# Software Engineering Meets Deep Learning: A Mapping Study

arXiv: https://arxiv.org/abs/1909.11436 · HTML: https://mlsanity.com/paper/1909.11436/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Sep 2019.

## Built on by (most cited first, 1 of 1)

- [PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code](https://mlsanity.com/paper/2103.12778/) (2021)

## Abstract (arXiv)

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.