Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Cliff B. Jones
Since
Specialization
Citations
This map shows the geographic impact of Cliff B. Jones's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cliff B. Jones with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cliff B. Jones more than expected).
This network shows the impact of papers produced by Cliff B. Jones. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cliff B. Jones. The network helps show where Cliff B. Jones may publish in the future.
Co-authorship network of co-authors of Cliff B. Jones
This figure shows the co-authorship network connecting the top 25 collaborators of Cliff B. Jones.
A scholar is included among the top collaborators of Cliff B. Jones based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Cliff B. Jones. Cliff B. Jones is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hayes, Ian J., Cliff B. Jones, & Robert J. Colvin. (2014). Laws and Semantics for Rely-Guarantee Refinement. School of Computing Science Technical Report Series.5 indexed citations
4.
Jones, Cliff B., et al.. (2012). Towards a Mechanisation of a Logic that Copes with Partial Terms. School of Computing Science Technical Report Series.1 indexed citations
5.
Hayes, Ian J., Cliff B. Jones, & Robert J. Colvin. (2012). Refining rely-guarantee thinking. School of Computing Science Technical Report Series.
6.
Hayes, Ian J., Alan Burns, Brijesh Dongol, & Cliff B. Jones. (2011). Comparing Models of Nondeterministic Expression Evaluation. School of Computing Science Technical Report Series.6 indexed citations
Grov, Gudmund, et al.. (2010). The AI4FM approach for proof automation within formal methods — A Grand Challenge 6 "Dependable Systems Evolution" project. ERA.1 indexed citations
9.
Jones, Cliff B., Gudmund Grov, & Alan Bundy. (2010). Ideas for a high-level proof strategy language. Edinburgh Research Explorer.1 indexed citations
10.
Jones, Cliff B. & Ken Pierce. (2010). Splitting Atoms with Rely/Guarantee Conditions Coupled with Data Reification. School of Computing Science Technical Report Series.2 indexed citations
11.
Bundy, Alan, Gudmund Grov, & Cliff B. Jones. (2009). Learning from experts to aid the automation of proof search. Edinburgh Research Explorer.4 indexed citations
12.
Butler, Michael, Cliff B. Jones, Alexander Romanovsky, & Elena Troubitsynå. (2005). Proceedings of the Workshop on Rigorous Engineering of Fault-Tolerant Systems (REFT 2005).. ePrints Soton (University of Southampton).1 indexed citations
Jones, Cliff B.. (1990). Systematic software development using VDM (2nd ed.). Prentice-Hall, Inc eBooks.121 indexed citations
19.
Jones, Cliff B., et al.. (1990). Case studies in systematic software development. Prentice-Hall, Inc eBooks.26 indexed citations
20.
Jones, Cliff B.. (1983). Specification and Design of (Parallel) Programs. IFIP Congress. 321–332.196 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.