Corpus ID: 13688465

Effective Automated Decision Support for Managing Crowdtesting

  title={Effective Automated Decision Support for Managing Crowdtesting},
  author={Junjie Wang and Ye Yang and Rahul Krishna and T. Menzies and Qing Wang},
Crowdtesting has grown to be an effective alter-native to traditional testing, especially in mobile apps. However,crowdtesting is hard to manage in nature. Given the complexity of mobile applications and unpredictability of distributed, parallel crowdtesting process, it is difficult to estimate (a) the remaining number of bugs as yet undetected or (b) the required cost to find those bugs. Experience-based decisions may result in ineffective crowdtesting process. This paper aims at exploring… Expand


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Domain Adaptation for Test Report Classification in Crowdsourced Testing
  • Junjie Wang, Qiang Cui, Song Wang, Qing Wang
  • Engineering, Computer Science
  • 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP)
  • 2017
This work uses the Stacked Denoising Autoencoders to automatically learn the high-level features from raw textual terms, and utilize these features for classification in an effective cross-domain classification model. Expand