@Article{DBLP:journals/corr/abs-2103-02330,
  author        = {Saad Shafiq and Atif Mashkoor and Christoph Mayr-Dorn and Alexander Egyed},
  journal       = {CoRR},
  title         = {TaskAllocator: {A} Recommendation Approach for Role-based Tasks Allocation in Agile Software Development},
  year          = {2021},
  volume        = {abs/2103.02330},
  abstract      = {In this paper, we propose a recommendation approach -- TaskAllocator -- in order to predict the assignment of incoming tasks to potential befitting roles. The proposed approach, identifying team roles rather than individual persons, allows project managers to perform better tasks allocation in case the individual developers are over-utilized or moved on to different roles/projects. We evaluated our approach on ten agile case study projects obtained from the this http URL repository. In order to determine the TaskAllocator's performance, we have conducted a benchmark study by comparing it with contemporary machine learning models. The applicability of the TaskAllocator was assessed through a plugin that can be integrated with JIRA and provides recommendations about suitable roles whenever a new task is added to the project. Lastly, the source code of the plugin and the dataset employed have been made public.},
  archiveprefix = {arXiv},
  bibsource     = {dblp computer science bibliography, https://dblp.org},
  biburl        = {https://dblp.org/rec/journals/corr/abs-2103-02330.bib},
  eprint        = {2103.02330},
  file          = {:Journals/CORR 2021 - TaskAllocator A Recomendation Approach for Role-based Tasks Allocation in Agile Software Development/TaskAllocator A Recommendation Aprroach for Role-based Tasks Allocation-preprint.pdf:PDF},
  keywords      = {LIT AI Lab, LIT Secure and Correct Systems Lab},
  timestamp     = {Thu, 04 Mar 2021 17:00:40 +0100},
  url           = {https://arxiv.org/abs/2103.02330},
}