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Publication Detail
Multi-objective software effort estimation
  • Publication Type:
    Conference
  • Authors:
    Sarro F, Petrozziello A, Harman M
  • Publication date:
    14/05/2016
  • Pagination:
    619, 630
  • Published proceedings:
    Proceedings - International Conference on Software Engineering
  • Volume:
    14-22-May-2016
  • ISBN-13:
    9781450339001
  • Status:
    Published
  • Conference start date:
    14/05/2016
  • Conference finish date:
    22/05/2016
  • Print ISSN:
    0270-5257
Abstract
© 2016 ACM.We introduce a bi-objective effort estimation algorithm that combines Confidence Interval Analysis and assessment of Mean Absolute Error. We evaluate our proposed algorithm on three different alternative formulations, baseline comparators and current state-of-the-art effort estimators applied to five real-world datasets from the PROMISE repository, involving 724 different software projects in total. The results reveal that our algorithm outperforms the baseline, state-of-the-art and all three alternative formulations, statistically significantly (p < 0:001) and with large effect size (A12≥ 0:9) over all five datasets. We also provide evidence that our algorithm creates a new state-of-the-art, which lies within currently claimed industrial human-expert-based thresholds, thereby demonstrating that our findings have actionable conclusions for practicing software engineers.
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