Can Microtask Programming Work in Industry?
September 11, 2020 ยท Declared Dead ยท ๐ ESEC/SIGSOFT FSE
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Shinobu Saito, Yukako Iimura, Emad Aghayi, Thomas D. LaToza
arXiv ID
2009.05207
Category
cs.SE: Software Engineering
Citations
11
Venue
ESEC/SIGSOFT FSE
Last Checked
3 months ago
Abstract
A critical issue in software development projects in IT service companies is finding the right people at the right time. By enabling assignments of tasks to people to be more fluid, the use of crowdsourcing approaches within a company offers a potential solution to this challenge. Inside a company, as multiple system development projects are ongoing separately, developers with slack time on one project might use this time to contribute to other projects. In this paper, we report on a case study of the application of crowdsourcing within an industrial web application system development project in a large telecommunications company. Developers worked with system specifications which were organized into a set of microtasks, offering a set of short and self-contained descriptions. When crowd workers in other projects had slack time, they fetched and completed microtasks. Our results offer initial evidence for the potential value of microtask programming in increasing the fluidity of team assignments within a company. Crowd contributors to the project were able to onboard and contribute to a new project in less than 2 hours. After onboarding, the crowd workers were together able to successfully implement a small program which contained only a small number of defects. Interview and survey data gathered from project participants revealed that crowd workers reported that they perceived onboarding costs to be reduced and did not experience issues with the reduced face to face communication, but experienced challenges with motivation.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Software Engineering
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
GraphCodeBERT: Pre-training Code Representations with Data Flow
R.I.P.
๐ป
Ghosted
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars
R.I.P.
๐ป
Ghosted
Microservices: yesterday, today, and tomorrow
R.I.P.
๐ป
Ghosted
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks
R.I.P.
๐ป
Ghosted
A Survey of Machine Learning for Big Code and Naturalness
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted