Time-Aware Models for Software Effort Estimation

TL;DR

This paper explores the impact of incorporating project timing information into software effort estimation models, demonstrating that time-aware models can be built and differ from traditional models, but without clear superiority.

Contribution

It introduces and compares two time-aware modeling approaches for software effort estimation, highlighting their differences from non-time-aware models.

Findings

Time-aware models can be built using project timing data.

Models differ in parameters and weightings from non-time-aware models.

No statistically significant difference in accuracy between the two approaches.

Abstract

It seems logical to assert that the dynamic nature of software engineering practice would mean that software effort estimation (SEE) modelling should take into account project start and completion dates. That is, we should build models for future projects based only on data from completed projects; and we should prefer data from recent similar projects over data from older similar projects. Research in SEE modelling generally ignores these recommendations. In this study two different model development approaches that take project timing into account are applied to two publicly available datasets and the outcomes are compared to those drawn from three baseline (non-time-aware) models. Our results indicate: that it is feasible to build accurate effort estimation models using project timing information; that the models differ from those built without considering time, in terms of the parameters included and their weightings; and that there is no statistical significance difference as to which of the two model building approaches is superior in terms of accuracy.