  Context: In addressing how best to estimate how much effort is required to
develop software, a recent study found that using exemplary and recently
completed projects [forming Bellwether moving windows (BMW)] in software effort
prediction (SEP) models leads to relatively improved accuracy. More studies
need to be conducted to determine whether the BMW yields improved accuracy in
general, since different sizing and aging parameters of the BMW are known to
affect accuracy. Objective: To investigate the existence of exemplary projects
(Bellwethers) with defined window size and age parameters, and whether their
use in SEP improves prediction accuracy. Method: We empirically investigate the
moving window assumption based on the theory that the prediction outcome of a
future event depends on the outcomes of prior events. Sampling of Bellwethers
was undertaken using three introduced Bellwether methods (SSPM, SysSam, and
RandSam). The ergodic Markov chain was used to determine the stationarity of
the Bell-wethers. Results: Empirical results show that 1) Bellwethers exist in
SEP and 2) the BMW has an approximate size of 50 to 80 exemplary projects that
should not be more than 2 years old relative to the new projects to be
estimated. Conclusion: The study's results add further weight to the
recommended use of Bellwethers for improved prediction accuracy in SEP.
