Erik Arisholm

3.4k total citations · 1 hit paper
34 papers, 2.3k citations indexed

About

Erik Arisholm is a scholar working on Information Systems, Software and Artificial Intelligence. According to data from OpenAlex, Erik Arisholm has authored 34 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Information Systems, 15 papers in Software and 13 papers in Artificial Intelligence. Recurrent topics in Erik Arisholm's work include Software Engineering Research (29 papers), Software Engineering Techniques and Practices (21 papers) and Software Reliability and Analysis Research (13 papers). Erik Arisholm is often cited by papers focused on Software Engineering Research (29 papers), Software Engineering Techniques and Practices (21 papers) and Software Reliability and Analysis Research (13 papers). Erik Arisholm collaborates with scholars based in Norway, Canada and Germany. Erik Arisholm's co-authors include Lionel Briand, Dag I. K. Sjøberg, Tore Dybå, Jo Erskine Hannay, T. Dyba, Magne Jørgensen, Yvan Labiche, Bente Anda, Amela Karahasanović and Forrest Shull and has published in prestigious journals such as IEEE Transactions on Software Engineering, IEEE Software and Journal of Systems and Software.

In The Last Decade

Erik Arisholm

34 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

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.

A systematic and comprehensive investigation of methods to build and evaluate fault prediction models

2009 336 citations Erik Arisholm, Lionel Briand et al. Journal of Systems and Software profile →

Peers

Erik Arisholm

IS

SOFTW

AI

CNC

CSA

Ewan Tempero New Zealand

Giuseppe Scanniello Italy

Lesley M. Pickard United Kingdom

Filippo Lanubile Italy

Hironori Washizaki Japan

Michael Fagan United States

Mohamed Wiem Mkaouer United States

Francesca Arcelli Fontana Italy

Debra J. Richardson United States

Christoph Treude Australia

Ewan Tempero New Zealand

Erik Arisholm

1.6k ×0.8

IS

954 ×0.9

SOFTW

678 ×1.1

AI

535 ×1.1

CNC

601 ×1.4

CSA

Citations per year, relative to Erik Arisholm Erik Arisholm (= 1×) peers Ewan Tempero

Countries citing papers authored by Erik Arisholm

Since Specialization

Citations

This map shows the geographic impact of Erik Arisholm'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 Erik Arisholm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik Arisholm more than expected).

Fields of papers citing papers by Erik Arisholm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik Arisholm. 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 Erik Arisholm. The network helps show where Erik Arisholm may publish in the future.

Co-authorship network of co-authors of Erik Arisholm

This figure shows the co-authorship network connecting the top 25 collaborators of Erik Arisholm. A scholar is included among the top collaborators of Erik Arisholm 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 Erik Arisholm. Erik Arisholm is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Briand, Lionel, et al.. (2011). Industrial experiences with automated regression testing of a legacy database application. 16. 362–371. 19 indexed citations

2.

Hannay, Jo Erskine, Tore Dybå, Erik Arisholm, & Dag I. K. Sjøberg. (2009). The effectiveness of pair programming: A meta-analysis. Information and Software Technology. 51(7). 1110–1122. 164 indexed citations

3.

Anda, Bente, et al.. (2009). Understanding software maintenance and evolution by analyzing individual changes: a literature review. Journal of Software Maintenance and Evolution Research and Practice. 21(6). 349–378. 20 indexed citations

4.

Anda, Bente, et al.. (2009). Understanding cost drivers of software evolution: a quantitative and qualitative investigation of change effort in two evolving software systems. Empirical Software Engineering. 15(2). 166–203. 9 indexed citations

5.

Wang, Alf Inge & Erik Arisholm. (2008). The effect of task order on the maintainability of object-oriented software. Information and Software Technology. 51(2). 293–305. 13 indexed citations

6.

Arisholm, Erik, et al.. (2007). Incorporating Rapid User Interface Prototyping in Object-Oriented Analysis and Design with Genova. 1 indexed citations

7.

Wang, Alf Inge, Erik Arisholm, & Letizia Jaccheri. (2007). Educational Approach to an Experiment in a Software Architecture Course. 9. 291–300. 2 indexed citations

8.

Arisholm, Erik, et al.. (2007). Evaluating Pair Programming with Respect to System Complexity and Programmer Expertise. IEEE Transactions on Software Engineering. 33(2). 65–86. 178 indexed citations

9.

Arisholm, Erik, et al.. (2006). The impact of UML documentation on software maintenance: an experimental evaluation. IEEE Transactions on Software Engineering. 32(6). 365–381. 125 indexed citations

10.

Arisholm, Erik. (2006). Empirical assessment of the impact of structural properties on the changeability of object-oriented software. Information and Software Technology. 48(11). 1046–1055. 19 indexed citations

11.

Arisholm, Erik & Lionel Briand. (2006). Predicting fault-prone components in a java legacy system. 8–17. 155 indexed citations

12.

Dyba, T., Nils Brede Moe, & Erik Arisholm. (2005). Measuring software methodology usage: challenges of conceptualization and operationalization. 47. 432–442. 19 indexed citations

13.

Anda, Bente, et al.. (2005). Collecting Feedback during Software Engineering Experiments. Empirical Software Engineering. 10(2). 113–147. 17 indexed citations

14.

Arisholm, Erik, et al.. (2004). An initial framework for research on pair programming. 132–142. 51 indexed citations

15.

Arisholm, Erik & Dag I. K. Sjøberg. (2004). Evaluating the effect of a delegated versus centralized control style on the maintainability of object-oriented software. IEEE Transactions on Software Engineering. 30(8). 521–534. 101 indexed citations

16.

Arisholm, Erik, et al.. (2004). Dynamic coupling measurement for object-oriented software. IEEE Transactions on Software Engineering. 30(8). 491–506. 237 indexed citations

17.

Arisholm, Erik, et al.. (2002). A web-based support environment for software engineering experiments. Nordic journal of computing. 9(3). 231–247. 28 indexed citations

18.

Sjøberg, Dag I. K., Erik Arisholm, & Magne Jørgensen. (2002). Conducting experiments on software evolution. 142–142. 5 indexed citations

19.

Arisholm, Erik & Dag I. K. Sjøberg. (2000). Towards a framework for empirical assessment of changeability decay. Journal of Systems and Software. 53(1). 3–14. 22 indexed citations

20.

Briand, Lionel, Erik Arisholm, Steve Counsell, Frank Houdek, & Pascale Thévenod-Fosse. (1999). Empirical Studies of Object-Oriented Artifacts, Methods, and Processes: State of the Art and Future Directions. Empirical Software Engineering. 4(4). 387–404. 64 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.

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