What is he best known for?
The fields of study he is best known for:
- Programming language
- Operating system
- Software
Satish Chandra spends much of his time researching Software development, Java, Software, Distributed computing and Debugging.
Satish Chandra combines subjects such as Collaborative software and Knowledge management with his study of Software development.
His Java research is multidisciplinary, relying on both Call graph, Theoretical computer science, Property, Object-oriented programming and JavaScript.
His Software study combines topics from a wide range of disciplines, such as Model checking and Software deployment.
His Distributed computing research includes themes of Shared memory and Parallel computing.
Debugging is a primary field of his research addressed under Programming language.
His most cited work include:
- SemFix: program repair via semantic analysis (378 citations)
- A research agenda for distributed software development (190 citations)
- Decentralizing execution of composite web services (165 citations)
What are the main themes of his work throughout his whole career to date?
Programming language, Code, Theoretical computer science, Artificial intelligence and Software engineering are his primary areas of study.
His study in Programming language concentrates on Programmer, JavaScript, Software development, Type safety and Semantics.
His Code research is multidisciplinary, incorporating elements of Python, Natural language user interface, Natural language, Set and Information retrieval.
His Theoretical computer science research focuses on Java and how it relates to Language construct.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Scalability.
His Software engineering research focuses on Test case and how it connects with Computer program and Executable.
He most often published in these fields:
- Programming language (32.61%)
- Code (16.30%)
- Theoretical computer science (15.22%)
What were the highlights of his more recent work (between 2016-2021)?
- Code (16.30%)
- Artificial intelligence (11.96%)
- Natural language (8.70%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Code, Artificial intelligence, Natural language, Python and Machine learning.
The various areas that he examines in his Code study include Perspective, Natural language user interface, Information retrieval and Data science.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Null and Language construct.
To a larger extent, Satish Chandra studies Programming language with the aim of understanding Python.
His Machine learning research incorporates elements of Root cause analysis, Debugging, Java and Root cause.
His work in Debugging covers topics such as Workflow which are related to areas like Scalability.
Between 2016 and 2021, his most popular works were:
- Retrieval on source code: a neural code search (52 citations)
- SapFix: automated end-to-end repair at scale (46 citations)
- Getafix: learning to fix bugs automatically (36 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Operating system
- Software
The scientist’s investigation covers issues in Natural language, Code, Artificial intelligence, Ranking and Machine learning.
His work deals with themes such as Python, Type inference, F1 score and Word embedding, which intersect with Natural language.
The Code study combines topics in areas such as Artificial neural network, Probabilistic logic, Correctness and JavaScript.
Satish Chandra has researched Artificial intelligence in several fields, including Java, Software, Static analysis and Language construct.
His Ranking study combines topics in areas such as Natural language user interface and Source code.
In general Machine learning, his work in Deep learning and Network complexity is often linked to Point, sort and Sequence linking many areas of study.
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.
