Software errors and complexity: an empirical investigation0
Communications of the ACM
A message passing standard for MPP and workstations
Communications of the ACM
Open Source Development with Cvs
Open Source Development with Cvs
OpenMP: An Industry-Standard API for Shared-Memory Programming
IEEE Computational Science & Engineering
Programming factors - language features that help explain programming complexity
ACM '78 Proceedings of the 1978 annual conference - Volume 2
ACM SIGPLAN Notices
Automatic Mining of Source Code Repositories to Improve Bug Finding Techniques
IEEE Transactions on Software Engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Perspective-Based Reading: A Replicated Experiment Focused on Individual Reviewer Effectiveness
Empirical Software Engineering
Patterns for parallel programming
Patterns for parallel programming
Defect classification and defect types revisited
DEFECTS '08 Proceedings of the 2008 workshop on Defects in large software systems
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We present an iterative, reading-based methodology for analyzing defects in source code when change history is available. Our bottom-up approach can be applied to build knowledge of recurring defects in a specific domain, even if other sources of defect data such as defect reports and change requests are unavailable, incomplete or at the wrong level of abstraction for the purposes of the defect analysis. After defining the methodology, we present the results of an empirical study where our method was applied to analyze defects in parallel programs which use the MPI (Message Passing Interface) library to express parallelism. This library is often used in the domain of high performance computing, where there is much discussion but little empirical data about the frequency and severity of defect types. Preliminary results indicate the methodology is feasible and can provide insights into the nature of real defects. We present the results, derived hypothesis, and lessons learned.