Qinghang Bao

dblp:349/5317 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
YearPublicationVenuePosition
2023 Identifying Topics and Trends in DevOps: A Study of Stack Overflow Posts
abstract
DevOps (i.e., Development and Operations) is a growing concept, which aims to make building, testing, and releasing software faster, more frequent, and more reliable by automating the software delivery and architectural change process. Since DevOps is a relatively new concept, we seek to understand the hot topics in DevOps and the challenges encountered so far. We use data from Stack Overflow (SO), the largest developer question-and-answer platform, to understand the interests and difficulties of DevOps. First, we collected all DevOps-related posts from 2009 to 2022 based on SO tags. Then we used the Latent Dirichlet Allocation model to identify topics, and manually analyzed time trends and hot topics. The results indicate that: (1) DevOps-related issues can be divided into four categories: Container, Pipeline, Configuration, and Deployment; (2) The issues that get more attention are DevOps foundation issues, cloud deployment failure issues, Kubernetes technology usage issues, and DevOps complex environment issues, while the most difficult issues to solve are CI/CD-related issues; (3) DevOps has been introduced since 2009 and the number of questions on the SO platform is growing, especially between 2014 and 2020; (4) The percentage of DevOps-related questions with no accepted answers on the SO platform reached 56.3%. Our results show that problems are evident in terms of complex environments and the lack of experts. Also, developers need to pay more attention to basic theoretical knowledge when they are new to DevOps.
Qing Mi, Qinghang Bao, Longjie Cui
SEAA2
2023 A graph-based code representation method to improve code readability classification
Qing Mi, Han Weng, Qinghang Bao, Longjie Cui, Wei Ma 0008
Empir. Softw. Eng.4