Machine learning (ML) techniques increase the effectiveness of software engineering (SE)
lifecycle activities. We systematically collected, quality-assessed, summarized, and …

Data is one of the most valuable assets in the digital era because it may conceal hidden
valuable insights. Diverse organizations in diverse domains overcome the challenges of the …

In the digital era, data is one of the most important assets since it conceals valuable
information. Developers of data-intensive systems have new challenges at each level of …

In the past few years, Tweets have been widely used to perform Big Data analysis. However,
the incredible amount of data captured by Twitter needs to be stored for further processing …

Dominated by quantitative data science techniques, social media data analysis often fails to
incorporate the surrounding context, conversation, and metadata that allows for more …

Simulations of smart grids provide a safe means to test new concepts prior to laboratory and
field tests. Due to the multi-actor and multi-physics complexity of smart grids, various …

Nowadays, when the Internet, software and hardware technologies develop rapidly, we are
in a digital era where a wide range of resources generate data in different formats and 7/24 …

Um den drastischen Anstieg an verfügbaren Daten zu versinnbildlichen, hat sich in den
letzten Jahren das Synonym Big Data in der praktischen und wissenschaftlichen Diskussion …

Developing software systems to meet user-demanded functionality is critical. Achieving the
design goals by providing the needed functionality is a necessary task, and it is about …

In this era of big data, the streaming, storage, and analysis of large amounts of data present
a variety of challenges. Several challenges must be addressed by designers of data …