Background: Code smells indicate suboptimal design or implementation choices in the
source code that often lead it to be more change-and fault-prone. Researchers defined …

Context Software effort estimation (SEE) is most crucial activity in the field of software
engineering. Vast research has been conducted in SEE resulting into a tremendous …

While deep learning is an exciting new technique, the benefits of this method need to be
assessed with respect to its computational cost. This is particularly important for deep …

Context Due to the complex nature of software development process, traditional parametric
models and statistical methods often appear to be inadequate to model the increasingly …

Solar radiation is the Earth's primary source of energy and has an important role in the
surface radiation balance, hydrological cycles, vegetation photosynthesis, and weather and …

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 …

The recent availability of datasets on transportation networks with higher spatial and
temporal resolution is enabling new research activities in the fields of Territorial Intelligence …

Studies in software effort estimation (SEE) have explored the use of hyper-parameter tuning
for machine learning algorithms (MLA) to improve the accuracy of effort estimates. In other …

Replication studies increase our confidence in previous results when the findings are similar
each time, and help mature our knowledge by addressing both internal and external validity …

Several software effort estimation techniques based on mathematical formulations have
been proposed, however there is little consensus on the best technique for effort estimation …