Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in
industry. However, based on well over a dozen case studies, we have learned that …

While there are many claims for the successful use of extreme programming (XP) and agile
modeling (AM), and the proponents can often be vocal in the extreme regarding their …

Software development companies are increasingly aiming to become data-driven by trying
to continuously experiment with the products used by their customers. Although familiar with …

CONTEXT: Some recent static techniques for automatic bug localization have been built
around modern information retrieval (IR) models such as latent semantic indexing (LSI) …

Today's environments of increasing business change require software development
methodologies that are more adaptable. This article examines how complex adaptive …

Many empirical studies have found that software metrics can predict class error proneness
and the prediction can be used to accurately group error-prone classes. Recent empirical …

Agile methods have proven successful in increasing customer satisfaction and decreasing
time and cost to market under uncertain conditions. Key characteristics of agile methods are …

Traditionally, software development organizations relied on heavyweight development
methodologies, such as waterfall, V-model, and others. Later, agile development …

In today's increasingly volatile environments, evolvability is quickly becoming the most
desirable characteristic of information systems. Current information systems still struggle to …

Context The higher availability of software usage data and the influence of the Lean Startup
led to the rise of experimentation in software engineering, a new approach for development …