Empirical Software Engineering

1.6k papers and 32.7k indexed citations i.

About

The 1.6k papers published in Empirical Software Engineering in the last decades have received a total of 32.7k indexed citations. Papers published in Empirical Software Engineering usually cover Information Systems (1.4k papers), Software (713 papers) and Artificial Intelligence (396 papers) specifically the topics of Software Engineering Research (1.3k papers), Software Reliability and Analysis Research (542 papers) and Software Engineering Techniques and Practices (503 papers). The most active scholars publishing in Empirical Software Engineering are Martin Höst, Per Runeson, Ahmed E. Hassan, Claes Wohlin, Burak Turhan, David Lo, Andrea Arcuri, Lionel Briand, Gregg Rothermel and Tim Menzies.

In The Last Decade

Fields of papers published in Empirical Software Engineering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Empirical Software Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Empirical Software Engineering.

Countries where authors publish in Empirical Software Engineering

Since Specialization
Citations

This map shows the geographic impact of research published in Empirical Software Engineering. 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 papers published in Empirical Software Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Empirical Software Engineering more than expected).

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.

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