SEHCMar 18, 2021

Impact of Task Cycle Pattern on Project Success in Software Crowdsourcing

arXiv:2103.10355v1
Originality Synthesis-oriented
AI Analysis

This research addresses the problem of optimizing task decomposition and worker supply for project managers in software crowdsourcing, but it appears incremental as it builds on existing models like the waterfall model.

The study analyzed task lifecycle patterns in software crowdsourcing to understand how task arrival sequences impact project success, identifying four distinct patterns: Prior Cycle, Current Cycle, Orbit Cycle, and Fresh Cycle.

Crowdsourcing is becoming an accepted method of software development for different phases in the production lifecycle. Ideally, mass parallel production through Crowdsourcing could be an option for rapid acquisition in software engineering by leveraging infinite worker resource on the internet. It is important to understand the patterns and strategies of decomposing and uploading parallel tasks to maintain a stable worker supply as well as a satisfactory task completion rate. This research report is an empirical analysis of the available tasks' lifecycle patterns in crowdsourcing. Following the waterfall model in Crowdsourced Software Development (CSD), this research identified four patterns for the sequence of task arrival per project: 1) Prior Cycle, 2) Current Cycle, 3) Orbit Cycle, and 4) Fresh Cycle.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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