Crowdsourcing Software Development: Task Assignment Using PDDL Artificial Intelligence Planning
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The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitiveenvironment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the taskand win rewards. Task searching and assigning are very important aspects of the CSD environment becausetasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on theplatform are very difficult and time-consuming process for both the developer and platform. However, thereare many other problems that are affecting CSD quality and reliability of CSD workers to assign the task whichinclude the required knowledge, large participation, time complexity and incentive motivations. In order toattract the right person for the right task, the execution of action plans will help the CSD platform as well theCSD worker for the best matching with their tasks. This study formalized the task assignment method byutilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefinedconditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planningto provide the best possible solution to matching the CSD worker with their personality type.
Abstract
The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitiveenvironment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the taskand win rewards. Task searching and assigning are very important aspects of the CSD environment becausetasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on theplatform are very difficult and time-consuming process for both the developer and platform. However, thereare many other problems that are affecting CSD quality and reliability of CSD workers to assign the task whichinclude the required knowledge, large participation, time complexity and incentive motivations. In order toattract the right person for the right task, the execution of action plans will help the CSD platform as well theCSD worker for the best matching with their tasks. This study formalized the task assignment method byutilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefinedconditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planningto provide the best possible solution to matching the CSD worker with their personality type.
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