Building Knowledge through Families of Experiments
IEEE Transactions on Software Engineering
Static analysis tools as early indicators of pre-release defect density
Proceedings of the 27th international conference on Software engineering
Assessing the Relationship between Software Assertions and Faults: An Empirical Investigation
ISSRE '06 Proceedings of the 17th International Symposium on Software Reliability Engineering
The influence of organizational structure on software quality: an empirical case study
Proceedings of the 30th international conference on Software engineering
Empirical Software Engineering
IEEE Transactions on Software Engineering
Does distributed development affect software quality? An empirical case study of Windows Vista
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Test coverage and post-verification defects: A multiple case study
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
On the Effectiveness of Unit Test Automation at Microsoft
ISSRE '09 Proceedings of the 2009 20th International Symposium on Software Reliability Engineering
Putting It All Together: Using Socio-technical Networks to Predict Failures
ISSRE '09 Proceedings of the 2009 20th International Symposium on Software Reliability Engineering
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An important component of Empirical Software Engineering (ESE) research involves the measurement, observation, analysis and understanding of software engineering in practice. Results analyzed without understanding the contexts in which they were obtained can lead to wrong and potentially harmful interpretation. There exist several myths in software engineering, most of which have been accepted for years as being conventional wisdom without having been questioned. In this talk we will deal briefly with a few popular myths in software engineering ranging from testing and static analysis to distributed development and highlight the importance of context and generalization.