Pricing crowdsourcing-based software development tasks

ISCAS OpenIR

	Pricing crowdsourcing-based software development tasks
	Mao, Ke (1); Yang, Ye (1); Li, Mingshu (1); Harman, Mark (3)
	2013
会议名称	2013 35th International Conference on Software Engineering, ICSE 2013
页码	1205-1208
会议日期	May 18, 2013 - May 26, 2013
会议地点	San Francisco, CA, United states
收录类别	CPCI ; EI
出版地	IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States
ISSN	2705257
ISBN	9781467330763
部门归属	(1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) University of Chinese, Academy of Sciences, Beijing, China; (3) Dept. of Computer Science, University of College London, London, United Kingdom
摘要	Many organisations have turned to crowdsource their software development projects. This raises important pricing questions, a problem that has not previously been addressed for the emerging crowdsourcing development paradigm. We address this problem by introducing 16 cost drivers for crowdsourced development activities and evaluate 12 predictive pricing models using 4 popular performance measures. We evaluate our predictive models on TopCoder, the largest current crowdsourcing platform for software development. We analyse all 5,910 software development tasks (for which partial data is available), using these to extract our proposed cost drivers. We evaluate our predictive models using the 490 completed projects (for which full details are available). Our results provide evidence to support our primary finding that useful prediction quality is achievable (Pred(30)>0.8). We also show that simple actionable advice can be extracted from our models to assist the 430,000 developers who are members of the TopCoder software development market. © 2013 IEEE.; Many organisations have turned to crowdsource their software development projects. This raises important pricing questions, a problem that has not previously been addressed for the emerging crowdsourcing development paradigm. We address this problem by introducing 16 cost drivers for crowdsourced development activities and evaluate 12 predictive pricing models using 4 popular performance measures. We evaluate our predictive models on TopCoder, the largest current crowdsourcing platform for software development. We analyse all 5,910 software development tasks (for which partial data is available), using these to extract our proposed cost drivers. We evaluate our predictive models using the 490 completed projects (for which full details are available). Our results provide evidence to support our primary finding that useful prediction quality is achievable (Pred(30)>0.8). We also show that simple actionable advice can be extracted from our models to assist the 430,000 developers who are members of the TopCoder software development market. © 2013 IEEE.
关键词	Crowdsourcing Pricing Software Measurement
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16537
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Mao, Ke ,Yang, Ye ,Li, Mingshu ,et al. Pricing crowdsourcing-based software development tasks[C]. IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States,2013:1205-1208.