• DOI:10.1145/3172871.3172880
Corpus ID: 3438662

Validating Requirements Reviews by Introducing Fault-Type Level Granularity: A Machine Learning Approach

@inproceedings{Singh2018ValidatingRR,
  title={Validating Requirements Reviews by Introducing Fault-Type Level Granularity: A Machine Learning Approach},
  author={Maninder Singh and Vaibhav K. Anu and Gursimran Singh Walia and Anurag Goswami},
  booktitle={ISEC '18},
  year={2018}
}

Maninder Singh, Vaibhav K. Anu, +1 author Anurag Goswami

Published in ISEC '18 2018

Engineering, Computer Science

Inspections are a proven approach for improving software requirements quality. Owing to the fact that inspectors report both faults and non-faults (i.e., false-positives) in their inspection reports, a major chunk of work falls on the person who is responsible for consolidating the reports received from multiple inspectors. We aim at automation of fault-consolidation step by using supervised machine learning algorithms that can effectively isolate faults from non-faults. Three different… CONTINUE READING

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