What is he best known for?
The fields of study he is best known for:
- Programming language
- Operating system
- Compiler
His main research concerns Programming language, Theoretical computer science, Java, Compiler and Object-oriented programming.
His work in Theoretical computer science addresses issues such as Graph, which are connected to fields such as Class-based programming, Interactive programming, Class hierarchy and Call site.
The Java study combines topics in areas such as Program optimization, Thread and Virtual machine.
His study in Virtual machine is interdisciplinary in nature, drawing from both Software engineering and Virtual reality.
The study incorporates disciplines such as Compiled language and Overhead in addition to Compiler.
His studies deal with areas such as Real-time computing and Program behavior as well as Operating system.
His most cited work include:
- Optimization of Object-Oriented Programs Using Static Class Hierarchy Analysis (554 citations)
- The Jalapeño virtual machine (547 citations)
- Adaptive optimization in the Jalapeno JVM (365 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Programming language, Operating system, Parallel computing, Garbage collection and Java.
Within one scientific family, David Grove focuses on topics pertaining to Theoretical computer science under Programming language, and may sometimes address concerns connected to Graph and Class.
His Operating system research is multidisciplinary, relying on both Computer architecture, Embedded system and Interface.
His Parallel computing study combines topics from a wide range of disciplines, such as Optimizing compiler, Partitioned global address space, Programming paradigm and Just-in-time compilation.
His Garbage collection research incorporates elements of Virtual machine, Real-time computing and Object model.
His work in Virtual machine covers topics such as Profiling which are related to areas like Adaptive system and Adaptive optimization.
He most often published in these fields:
- Programming language (31.19%)
- Operating system (22.02%)
- Parallel computing (22.02%)
What were the highlights of his more recent work (between 2012-2019)?
- Programming paradigm (12.84%)
- Distributed computing (13.76%)
- Scalability (9.17%)
In recent papers he was focusing on the following fields of study:
David Grove mostly deals with Programming paradigm, Distributed computing, Scalability, Parallel computing and Partitioned global address space.
Software engineering, Redundancy, Cloud computing, Analytics and Event is closely connected to Runtime system in his research, which is encompassed under the umbrella topic of Programming paradigm.
As a part of the same scientific family, he mostly works in the field of Scalability, focusing on Work stealing and, on occasion, Idle, Data parallelism, Task parallelism and Instruction-level parallelism.
David Grove studied Parallel computing and Load balancing that intersect with Initialization, Speedup and Scheduling.
His Concurrency study contributes to a more complete understanding of Programming language.
The study incorporates disciplines such as Toolchain and Executable in addition to Compiler.
Between 2012 and 2019, his most popular works were:
- Resilient X10: efficient failure-aware programming (40 citations)
- X10 and APGAS at Petascale (34 citations)
- GLB: lifeline-based global load balancing library in x10 (29 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Operating system
- Compiler
David Grove mainly focuses on Programming paradigm, Distributed computing, Parallel computing, Partitioned global address space and Load balancing.
His research in Programming paradigm intersects with topics in Runtime system, World Wide Web, Event, Analytics and Software engineering.
His study in the field of Fault tolerance also crosses realms of Software framework.
His Parallel computing study frequently draws connections to other fields, such as Stencil code.
He has included themes like Petascale computing and Range in his Partitioned global address space study.
In his research, he undertakes multidisciplinary study on Load balancing and IBM.
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