We study how software engineers design and evolve their domain model when building
applications against NoSQL data stores. Specifically, we target Java projects that use object …

This paper explores scalable implementation strategies for carrying out lazy schema
evolution in NoSQL data stores. For decades, schema evolution has been an evergreen in …

Recent position papers demand more schema flexibility, such as the ability to handle
variational data [3, 42]. Many agile software developers have long since turned towards …

Data accumulating in data lakes can become inaccessible in the long run when its
semantics are not available. The heterogeneity of data formats and the sheer volumes of …

Nowadays, data-intensive applications tend to access their underlying database in an
increasingly dynamic way. The queries that they send to the database server are usually …

NoSQL data stores are becoming popular due to their schema-less nature. They offer a high
level of flexibility, since they do not require to declare a global schema. Thus, the data model …

[Context] Data is being collected at an unprecedented scale. Data sets are becoming so
large and complex that traditionally engineered systems may be inadequate to deal with …

Managing data-intensive systems has long been recognized as an expensive and error-
prone process. This is mainly due to the often implicit consistency relationships that hold …

Abstract Model-driven engineering (MDE) is a software discipline that promotes the adoption
of models to support the specification, analysis, and development of complex systems …

Developers are sharing pre-trained Machine Learning (ML) models through a variety of
model sharing platforms, such as Hugging Face, in an effort to make ML development more …