The effect of inheritance on the maintainability of object-oriented software: an empirical study
ICSM '95 Proceedings of the International Conference on Software Maintenance
REBSE '05 Proceedings of the 2005 workshop on Realising evidence-based software engineering
Using observational pilot studies to test and improve lab packages
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
The Future of Empirical Methods in Software Engineering Research
FOSE '07 2007 Future of Software Engineering
A Systematic Review of Theory Use in Software Engineering Experiments
IEEE Transactions on Software Engineering
Methodology evaluation framework for dynamic evolution in composition-based distributed applications
Journal of Systems and Software
A systematic review of domain analysis solutions for product lines
Journal of Systems and Software
Evaluation of {model-based} testing techniques selection approaches: An external replication
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
The economic impact of software process variations
ICSP'07 Proceedings of the 2007 international conference on Software process
Collaboration on software tasks
XP'03 Proceedings of the 4th international conference on Extreme programming and agile processes in software engineering
A comparison of model-based and judgment-based release planning in incremental software projects
Proceedings of the 33rd International Conference on Software Engineering
Hi-index | 4.11 |
The author believes that scientists apply scientific investigative techniques to gain more understanding of what makes software "good" and how to make software well. Often, they adapt investigative techniques from other disciplines to define measures that make sense in the business, technical, and social contexts people use for decision making. However, the author believes that sometimes failure can educate as well as success. Examples from nineteenth-century physics show how a change in perspective can lead to explanations for previously misunderstood phenomena. The author claims that scientists must also consider whether their measurements constrict their view of what is really happening in the development process, and they must change or expand the approach if they are. Science clearly illustrates the limitations of an overly literal approach to building and maintaining software. Too often, the author believes, scientists tend to view software development the same way nineteenth-century phsicists viewed the universe. Taking a cue from Einstein, scientists should shape their theories and models to fit a more probabilistic reality.