
doi: 10.1109/2.796106
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 physicists viewed the universe. Taking a cue from Einstein, scientists should shape their theories and models to fit a more probabilistic reality.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 36 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
