A Catalogue of Game-Specific Software Nuggets
June 23, 2020 Β· Declared Dead Β· + Add venue
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Vartika Agrahari, Sridhar Chimalakonda
arXiv ID
2006.13129
Category
cs.SE: Software Engineering
Citations
0
Last Checked
5 months ago
Abstract
With the ever-increasing use of games, game developers are expected to write efficient code supporting several qualities such as security, maintainability, and performance. However, the continuous need to update the features of games in less duration might compel the developers to use anti-patterns, code smells and quick-fix solutions that may affect the functional and non-functional requirements of the game. These bad practices may lead to technical debt, poor program comprehension, and can cause several issues during software maintenance. Here, in this paper, we introduce "Software Nuggets" as a concept that affects software quality in a negative way and as a superset of anti-patterns, code smells, bugs, software bad practices. We call these Software Nuggets as "G-Nuggets" in the context of games. While there exists empirical research on games, we are not aware of any work on understanding and cataloguing these G-Nuggets. Thus, we propose a catalogue of G-Nuggets by mining and analyzing 892 commits, 189 issues, and 104 pull requests from 100 open-source GitHub game repositories. We use regular expressions and thematic analysis on this dataset for cataloguing game-specific Software Nuggets. We present a catalogue of ten G-Nuggets and provide examples for them present online at: https://phoebs88.github.io/A-Catalogue-of-Game-Specific-Software-Nuggets. We believe this catalogue might be helpful for researchers for further empirical research in the domain of games as well as for game developers to improve quality of games.
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