Foyzur Rahman

Information Systems · 2013

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Foyzur Rahman trusts overall

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

  1. Ahmed E. Hassan
  2. Tim Menzies
  3. Sunghun Kim
  4. Thomas Zimmermann
  5. Jeremy Greenwald
  6. Audris Mockus
  7. Christian Bird
  8. Andreas Zeller
  9. Art Frank
  10. Raimund Moser

Who trusts Foyzur Rahman overall

  1. Chakkrit Kla Tantithamthavorn
  2. Shane McIntosh
  3. Baishakhi Ray
  4. Jaechang Nam
  5. Xinli Yang
  6. Ahmed E. Hassan
  7. Wei Fu
  8. David Lo
  9. Vincent J. Hellendoorn
  10. Ken-ichi Matsumoto

Papers from Foyzur Rahman's perspective

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

  1. A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction (2008 ACM/IEEE 30th International Conference on Software Engineering)
  2. Predicting risk of software changes (Bell Labs technical journal)
  3. Data Mining Static Code Attributes to Learn Defect Predictors (IEEE Transactions on Software Engineering)
  4. Don't touch my code!: examining the effects of ownership on software quality (ESEC/FSE '11)
  5. Transfer learning for cross-company software defect prediction (Information and Software Technology)
  6. Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings (IEEE Transactions on Software Engineering)
  7. Predicting faults using the complexity of code changes (2009 IEEE 31st International Conference on Software Engineering)
  8. On the relative value of cross-company and within-company data for defect prediction (Empirical Software Engineering)
  9. A systematic and comprehensive investigation of methods to build and evaluate fault prediction models (Journal of Systems and Software)
  10. Predicting Defects for Eclipse (International Conference on Predictive Models in Software Engineering)

Their papers