His primary scientific interests are in Software product line, Data mining, Programming language, Software and Software engineering. His Software product line research is multidisciplinary, incorporating perspectives in Software system, Feature, Separation of concerns and Code refactoring. His Data mining research incorporates elements of Feature model, Feature and Document Structure Description.
Borrowing concepts from Product, Gunter Saake weaves in ideas under Software. His research in Software engineering intersects with topics in Software maintenance, Software development, Software development process, Java and Software variability. In his work, Mixin and Incremental build model is strongly intertwined with Aspect-oriented programming, which is a subfield of Feature-oriented programming.
Gunter Saake spends much of his time researching Software engineering, Software, Programming language, Database and Data mining. His Software engineering research includes elements of Software system, Software development and Software evolution. His research in Software development is mostly focused on Software construction.
Many of his research projects under Software are closely connected to Product with Product, tying the diverse disciplines of science together. As part of his studies on Software product line, Gunter Saake frequently links adjacent subjects like Feature model. His Data mining research is multidisciplinary, incorporating elements of Domain, Theoretical computer science and Feature.
His scientific interests lie mostly in Software product line, Data science, Software, Context and Software engineering. His study looks at the relationship between Software product line and topics such as Data mining, which overlap with Data architecture and Domain. He has researched Data science in several fields, including Open data and State.
His Feature model study, which is part of a larger body of work in Software, is frequently linked to Product and Sampling, bridging the gap between disciplines. His Context research is multidisciplinary, incorporating perspectives in Recommender system, Theoretical computer science, Data structure and Usability. His work on Traceability as part of general Software engineering study is frequently connected to Reuse, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Software engineering, Software product line, Data science, Software and Data quality are his primary areas of study. His Traceability study in the realm of Software engineering interacts with subjects such as Reuse. The concepts of his Software product line study are interwoven with issues in Feature, Feature extraction, Software system, Task and Bottleneck.
His research in Data science intersects with topics in Field and State. As part of one scientific family, he deals mainly with the area of Software, narrowing it down to issues related to the Data mining, and often Gut microbiome. In his study, which falls under the umbrella issue of Software development, Java is strongly linked to Human–computer interaction.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
FeatureIDE: An extensible framework for feature-oriented software development
Thomas Thüm;Christian Kästner;Fabian Benduhn;Jens Meinicke.
Science of Computer Programming (2014)
Feature-Oriented Software Product Lines: Concepts and Implementation
Sven Apel;Don Batory;Christian Kstner;Gunter Saake.
A Classification and Survey of Analysis Strategies for Software Product Lines
Thomas Thüm;Sven Apel;Christian Kästner;Ina Schaefer.
ACM Computing Surveys (2014)
Feature-Oriented Software Product Lines
Sven Apel;Don Batory;Christian Kästner;Gunter Saake.
Datenbanken : Konzepte und Sprachen
Gunter Saake;Kai-Uwe Sattler;Andreas Heuer.
FeatureIDE: A tool framework for feature-oriented software development
Christian Kastner;Thomas Thum;Gunter Saake;Janet Feigenspan.
international conference on software engineering (2009)
FeatureC++: on the symbiosis of feature-oriented and aspect-oriented programming
Sven Apel;Thomas Leich;Marko Rosenmüller;Gunter Saake.
generative programming and component engineering (2005)
Predicting performance via automated feature-interaction detection
Norbert Siegmund;Sergiy S. Kolesnikov;Christian Kastner;Sven Apel.
international conference on software engineering (2012)
Logics for databases and information systems
Jan Chomicki;Gunter Saake.
Logics for databases and information systems (1998)
Aspectual Feature Modules
S. Apel;T. Leich;G. Saake.
IEEE Transactions on Software Engineering (2008)
Profile was last updated on December 6th, 2021.
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