Abstract: Crowdsourcing is a distributed problem solving mechanism using group intelligence.It is widely used in Internet application scenarios based on artificial intelligence activities,using large groups of users on the Internet to work together to solve complex problems that cannot be solved by one person.Taking the development and maintenance process of open source software as an example,participants jointly complete key tasks such as code writing and bug repair through specific platforms.Different from traditional business process management (BPM),collaborative processes in the crowdsourcing scenario face challenges such as undetermined process structure,and unpredictable timing and results,which bring great difficulties to the efficiency and quality control of crowdsourcing collaboration.In this paper,aiming at a series of collaborative behaviors produced by multiple participants according to the time sequence (embodied as text in the form of natural language),natural language processing and artificial intelligence are used to propose a restoration algorithm for the process of crowdsourcing collaboration.An empirical study is carried out on the case of personnel cooperation in the process of bug repair in the field of open source software development.The collaborative process of recovery is visualized,and the accuracy of process recovery algorithm is quantitatively compared.This research can help coordinators of crowdsourcing process (such as open source project managers) to understand the problem solving process more intuitively,and find the typical patterns of collaboration,so as to make an accurate prediction for the nature of the collaborative process of the new crowdsourcing task.

Key words: Bug fix, Collaborative process, Crowdsourcing, Open source software development, Process restore