Tuning of Cost Drivers by Significance Occurrences and Their Calibration with Novel Software Effort Estimation Method

<table class="table-group" id="tab9"><tr><td><table class="table"><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr class="thead"><td align="left" rowspan="3"> </td><td align="center" colspan="6">PRED</td></tr><tr class="thead"><td align="center" colspan="3">COCOMO</td><td align="center" colspan="3">Proposed method</td></tr><tr class="thead"><td align="center">10</td><td align="center">20</td><td align="center">30</td><td align="center">10</td><td align="center">20</td><td align="center">30</td></tr><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr><td align="left">Percentage of 63 NASA datasets</td><td align="center">23.81</td><td align="center">39.68</td><td align="center">57.14</td><td align="center">25.4</td><td align="center">42.86</td><td align="center">61.91</td></tr><tr class="table-tr"><td colspan="7"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Pred calculation at different values for both the models.

Advances in Software Engineering

tab9

Table 9

Table 9: Tuning of Cost Drivers by Significance Occurrences and Their Calibration with Novel Software Effort Estimation Method 