Erik Arisholm

Information Systems · 2004–2010

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 20 citations into it; #4,600 of 8,771 by trust here, #4,188 by citations
• Software — 14 citations into it; #627 of 1,227 by trust here, #602 by citations
• Computer Networks and Communications — 5 citations into it; #5,524 of 9,886 by trust here, #5,340 by citations

Whom Erik Arisholm trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. P. Lachenbruch
2. Lionel Claude Briand
3. Raymond H. Myers
4. Ian H. Witten
5. James A. Hanley
6. Karim O. Elish
7. Sunghun Kim
8. Tore Dybå
9. N. Nagappan
10. Eibe Frank

Who trusts Erik Arisholm overall

1. Marco D'Ambros
2. Andrian Marcus
3. Danijel Radjenovic
4. Dag I.K. Sjøberg
5. Ruchika Malhotra
6. Cagatay Catal
7. Denys Poshyvanyk
8. Michele Lanza
9. Tore Dybå
10. M. Heričko

Papers from Erik Arisholm's perspective

Ordered by how strongly the researchers Erik Arisholm trusts endorse each paper. Same corpus, a different order for every researcher.

1. Predicting Fault Incidence Using Software Change History (IEEE Trans. Software Eng.)
2. Robust prediction of fault-proneness by random forests (IEEE International Symposium on Software Reliability Engineering)
3. Predicting the location and number of faults in large software systems (IEEE Transactions on Software Engineering)
4. Data mining - practical machine learning tools and techniques, Second Edition (The Morgan Kaufmann series in data management systems)
5. Use of relative code churn measures to predict system defect density (Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005.)
6. A systematic review of statistical power in software engineering experiments (Information and Software Technology)
7. Statistical Power Analysis for the Behavioral Sciences (2nd ed.)
8. An Empirical Investigation of an Object-Oriented Software System (IEEE Trans. Software Eng.)
9. Classifying Software Changes: Clean or Buggy? (IEEE Transactions on Software Engineering)
10. The meaning and use of the area under a receiver operating characteristic (ROC) curve.

Their papers

• A systematic and comprehensive investigation of methods to build and evaluate fault prediction models (2010) — 482 citations
• Evaluating Pair Programming with Respect to System Complexity and Programmer Expertise (2007) — 297 citations
• Dynamic coupling measurement for object-oriented software (2004) — 404 citations