Exploratory Analysis of Quality Practices in Open Source Domain
July 24, 2015 Β· Declared Dead Β· π Computer and Information Science
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jie Xu, Luiz Fernando Capretz, Danny Ho
arXiv ID
1507.06906
Category
cs.SE: Software Engineering
Citations
3
Venue
Computer and Information Science
Last Checked
4 months ago
Abstract
Software quality assurance has been a heated topic for several decades, but relatively few analyses were performed on open source software (OSS). As OSS has become very popular in our daily life, many researchers have been keen on the quality practices in this area. Although quality management presents distinct patterns compared with those in closed-source software development, some widely used OSS products have been implemented. Therefore, quality assurance of OSS projects has attracted increased research focuses. In this paper, a survey is conducted to reveal the general quality practices in open source communities. Exploratory analysis has been carried out to disclose those quality related activities. The results are compared with those from closed-source environments and the distinguished features of the quality assurance in OSS projects have been confirmed. Moreover, this study suggests potential directions for OSS developers to follow.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted