Raimund Moser

Information Systems · 2008

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 11 citations into it; #2,901 of 8,771 by trust here, #4,012 by citations
• Software — 10 citations into it; #412 of 1,227 by trust here, #489 by citations

Whom Raimund Moser trusts overall

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

1. N. Nagappan
2. Ramanath Subramanyam
3. Thomas Zimmermann
4. Tim Menzies
5. Thomas Ball
6. Mayuram S. Krishnan
7. Rahul Premraj
8. Jeremy Greenwald
9. Andreas Zeller
10. Ian H. Witten

Who trusts Raimund Moser overall

1. Marco D'Ambros
2. Sunghun Kim
3. Jaechang Nam
4. Song Wang
5. Ahmed E. Hassan
6. Zhimin He
7. Yasutaka Kamei
8. Michele Lanza
9. Ruchika Malhotra
10. Sinno Jialin Pan

Papers from Raimund Moser's perspective

Ordered by how strongly the researchers Raimund Moser 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. Predicting the location and number of faults in large software systems (IEEE Transactions on Software Engineering)
3. Mining metrics to predict component failures (International Conference on Software Engineering)
4. Data Mining Static Code Attributes to Learn Defect Predictors (IEEE Transactions on Software Engineering)
5. Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects (IEEE Trans. Software Eng.)
6. Use of relative code churn measures to predict system defect density (Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005.)
7. CVS release history data for detecting logical couplings (Sixth International Workshop on Principles of Software Evolution, 2003. Proceedings.)
8. Data mining - practical machine learning tools and techniques, Second Edition (The Morgan Kaufmann series in data management systems)
9. Predicting Defects for Eclipse (International Conference on Predictive Models in Software Engineering)
10. Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults (IEEE Transactions on Software Engineering)

Their papers

• A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction (2008) — 771 citations