15,801 research outputs found

    A survey of the use of crowdsourcing in software engineering

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    The term 'crowdsourcing' was initially introduced in 2006 to describe an emerging distributed problem-solving model by online workers. Since then it has been widely studied and practiced to support software engineering. In this paper we provide a comprehensive survey of the use of crowdsourcing in software engineering, seeking to cover all literature on this topic. We first review the definitions of crowdsourcing and derive our definition of Crowdsourcing Software Engineering together with its taxonomy. Then we summarise industrial crowdsourcing practice in software engineering and corresponding case studies. We further analyse the software engineering domains, tasks and applications for crowdsourcing and the platforms and stakeholders involved in realising Crowdsourced Software Engineering solutions. We conclude by exposing trends, open issues and opportunities for future research on Crowdsourced Software Engineering

    A goal model for crowdsourced software engineering

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    Crowdsourced Software Engineering (CSE) is the act of undertaking any external software engineering tasks by an undefined, potentially large group of online workers in an open call format. Using an open call, CSE recruits global online labor to work on various types of software engineering tasks, such as requirements extraction, design, coding and testing. The field is rising rapidly and touches various aspects of software engineering. CSE has grown significance in both academy and industry. Despite of the enormous usage and significance of CSE, there are many open challenges reported by various researchers. In order to overcome the challenges and realizing the full potential of CSE, it is highly important to understand the concrete advantages and goals of CSE. In this paper, we present a goal model for CSE, to understand the real environment of CSE, and to explore the aspects that can somehow overcome the aforementioned challenges. The model is designed using RiSD, a method for building Strategic Dependency (SD) models in the i* notation, applied in this work using iStar2.0. This work can be considered useful for CSE stakeholders (Requesters, Workers, Platform owners and CSE organizations).Peer ReviewedPostprint (published version

    A data-driven game theoretic strategy for developers in software crowdsourcing: a case study

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    Crowdsourcing has the advantages of being cost-effective and saving time, which is a typical embodiment of collective wisdom and community workers’ collaborative development. However, this development paradigm of software crowdsourcing has not been used widely. A very important reason is that requesters have limited knowledge about crowd workers’ professional skills and qualities. Another reason is that the crowd workers in the competition cannot get the appropriate reward, which affects their motivation. To solve this problem, this paper proposes a method of maximizing reward based on the crowdsourcing ability of workers, they can choose tasks according to their own abilities to obtain appropriate bonuses. Our method includes two steps: Firstly, it puts forward a method to evaluate the crowd workers’ ability, then it analyzes the intensity of competition for tasks at Topcoder.com—an open community crowdsourcing platform—on the basis of the workers’ crowdsourcing ability; secondly, it follows dynamic programming ideas and builds game models under complete information in different cases, offering a strategy of reward maximization for workers by solving a mixed-strategy Nash equilibrium. This paper employs crowdsourcing data from Topcoder.com to carry out experiments. The experimental results show that the distribution of workers’ crowdsourcing ability is uneven, and to some extent it can show the activity degree of crowdsourcing tasks. Meanwhile, according to the strategy of reward maximization, a crowd worker can get the theoretically maximum reward

    Privacy in crowdsourcing:a systematic review

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    The advent of crowdsourcing has brought with it multiple privacy challenges. For example, essential monitoring activities, while necessary and unavoidable, also potentially compromise contributor privacy. We conducted an extensive literature review of the research related to the privacy aspects of crowdsourcing. Our investigation revealed interesting gender differences and also differences in terms of individual perceptions. We conclude by suggesting a number of future research directions.</p

    Outsourcing labour to the cloud

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    Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area
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