LAUSR

Applications of predictive modelling and data analytics in software engineering have been a long term and an established interest among researchers and practitioners. Such models and analyses can be targeted at: planning, design, implementation, testing, maintenance, quality assurance, evaluation, process improvement, management, decision making, and risk assessment in software and systems development. This interdisciplinary research between the software engineering and data mining communities also targets verifiable and repeatable experiments that are useful in practice. This special section on Predictive Models and Data Analytics in Software Engineering presents extended versions of papers from the 14th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2018). The conference was founded in 2004 as a workshop to bring researchers and practitioners to present, discuss and exchange ideas, results, expertise and experiences in construction and/or application of predictive models in software engineering, then extended its focus to include data analytics, after becoming an international conference in 2009. Empirical Software Engineering https://doi.org/10.1007/s10664-020-09811-0