Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
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doi.org/w5595366 →Countries where authors are citing Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
This map shows the geographic impact of Software Product Lines in Action: The Best Industrial Practice in Product Line 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 Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering more than expected).
Fields of papers citing Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
This network shows the impact of Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering.
About Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
This paper, published in 2007, received 390 indexed citations . Written by F. J. van der Linden, Klaus Schmid and Eelco Rommes covering the research area of Management Information Systems, Artificial Intelligence and Information Systems. It is primarily cited by scholars working on Artificial Intelligence (350 citations), Information Systems (321 citations) and Software (88 citations). Published in Springer eBooks.
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.
This paper is also available at doi.org/w5595366.