What is he best known for?
The fields of study he is best known for:
- Programming language
- Software
- Software engineering
His primary areas of investigation include Programming language, Software engineering, Software, Software construction and Engineering management.
His work deals with themes such as Development and Set-builder notation, which intersect with Programming language.
His Software engineering research is mostly focused on the topic Formal methods.
His study in the field of Software project management also crosses realms of Risk analysis.
His Software construction study integrates concerns from other disciplines, such as Systems engineering and Software development process.
His Engineering management research is multidisciplinary, incorporating elements of Best practice, Software peer review and Software quality management, Software quality, Software quality control.
His most cited work include:
- Systematic software development using VDM (1747 citations)
- Tentative steps toward a development method for interfering programs (521 citations)
- Why software fails (465 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Programming language, Software engineering, Formal methods, Artificial intelligence and Concurrency.
His Notation research extends to Programming language, which is thematically connected.
His studies deal with areas such as Development and Software, Software development, Software development process, Software construction as well as Software engineering.
His study involves Package development process and Vienna Development Method, a branch of Software development.
His research on Formal methods also deals with topics like
- Formal specification which intersects with area such as Specification language,
- Automated theorem proving which intersects with area such as Mathematical proof.
His research on Concurrency often connects related topics like Theoretical computer science.
He most often published in these fields:
- Programming language (30.64%)
- Software engineering (25.72%)
- Formal methods (18.79%)
What were the highlights of his more recent work (between 2009-2020)?
- Software engineering (25.72%)
- Programming language (30.64%)
- Formal methods (18.79%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Software engineering, Programming language, Formal methods, Concurrency and Artificial intelligence.
Cliff B. Jones usually deals with Software engineering and limits it to topics linked to Automated theorem proving and Mathematical proof.
Cliff B. Jones combines topics linked to Abstraction with his work on Programming language.
His research in Formal methods tackles topics such as Formal specification which are related to areas like Software development process.
His study on Concurrency also encompasses disciplines like
- Theoretical computer science which intersects with area such as Process and Value,
- Notation which is related to area like Expression.
His biological study deals with issues like Turing, which deal with fields such as State.
Between 2009 and 2020, his most popular works were:
- Balancing expressiveness in formal approaches to concurrency (26 citations)
- Assessing the Long-Term Performance of Cross-Sectoral Strategies for National Infrastructure (25 citations)
- Elucidating concurrent algorithms via layers of abstraction and reification (24 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Software
- Artificial intelligence
Cliff B. Jones focuses on Concurrency, Programming language, Theoretical computer science, Artificial intelligence and Notation.
The various areas that Cliff B. Jones examines in his Concurrency study include Refinement calculus, Operational semantics, Rule of inference, Interference and Software.
Cliff B. Jones performs integrative study on Programming language and Key issues.
His Theoretical computer science research is multidisciplinary, incorporating elements of Partial function, Determinism and Semantic analysis.
Many of his research projects under Artificial intelligence are closely connected to Value with Value, tying the diverse disciplines of science together.
He has included themes like Process, Concurrent computing, Expression, Principle of compositionality and Value in his Notation study.
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