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. © 2010 Springer-Verlag.
CITATION STYLE
Nagappan, N. (2010). Myths in software engineering: From the other side. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6143 LNCS, pp. 3–5). https://doi.org/10.1007/978-3-642-13977-2_2
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