most citedA Taxonomy of Data Quality Challenges in Empirical Software Engineering

36 citations · 137 across the 7 of their papers we have counts for

collaborators

9 papers

cs.SE20211 cited

Analyzing the Stationarity Process in Software Effort Estimation Datasets

Michael Franklin Bosu, Stephen G. MacDonell, Peter A. Whigham

Software effort estimation models are typically developed based on an underlying assumption that all data points are equally relevant to the prediction of effort for future project…

cs.SE202136 cited

A Taxonomy of Data Quality Challenges in Empirical Software Engineering

Michael Franklin Bosu, Stephen G. MacDonell

Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for proce…

cs.SE202112 cited

Investigating the Significance of Bellwether Effect to Improve Software Effort Estimation

Solomon Mensah, Jacky Keung, Stephen G. MacDonell +2

Bellwether effect refers to the existence of exemplary projects (called the Bellwether) within a historical dataset to be used for improved prediction performance. Recent studies h…

cs.SE202131 cited

Data Quality in Empirical Software Engineering: A Targeted Review

Michael Franklin Bosu, Stephen G. MacDonell

Context: The utility of prediction models in empirical software engineering (ESE) is heavily reliant on the quality of the data used in building those models. Several data quality…

cs.SE202115 cited

Investigating the Significance of the Bellwether Effect to Improve Software Effort Prediction: Further Empirical Study

Solomon Mensah, Jacky Keung, Stephen G. MacDonell +2

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 Bell…

cs.SE202115 cited

On Satisfying the Android OS Community: User Feedback Still Central to Developers' Portfolios

Sherlock A. Licorish, Amjed Tahir, Michael Franklin Bosu +1

End-users play an integral role in identifying requirements, validating software features' usefulness, locating defects, and in software product evolution in general. Their role in…