
Abstract It is usual to base the assessment of software testing progress on a coverage measure such as code coverage or specification coverage, or on the percentage of the input domain exercised. In this paper it is argued that these characteristics do not provide good indications of the degree to which the software has been tested. Instead we propose that the assessment of testing progress be based on the total percentage of the probability mass that corresponds to the test cases selected and run. To do this, it is necessary to collect data that profiles how the software will be used once it is operational in the field. By so doing, we are able to accurately determine how much testing has been done, and whether it has met the standards of completeness for the product under consideration.
| 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). | 6 | |
| 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. | Average | |
| 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 |
