This page is supplementary to the paper entitled "Multi-Objective Software Effort Estimation" ([PDF] [BIB]), which is currently to appear in the proceedings of ICSE 2016.

In this paper 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 5 real-world datasets from the PROMISE repository, involving 724 different software projects in total. The results revealed that our proposed algorithm outperforms the baseline, state-of-the-art and all three alternative formulations, statistically significantly (p ≤ 0.01) and with large effect size (Aˆ12 ≥ 0.9) over all five datasets. We also provide evidence that our algorithm creates a new state-of-the-art that lies within currently claimed industrial thresholds, thereby demonstrating that our findings have actionable conclusions for practicing software engineers.