  The impetus for writing this paper are the well publicized media reports that
software failure was the cause of the two recent mishaps of the Boeing 737 Max
aircraft. The problem considered here though, is a specific one, in the sense
that it endeavors to address the general matter of conditions under which an
item such as a drug, a material specimen, or a complex, system can be certified
for use based on a large number of Bernoulli trials, all successful. More
broadly, the paper is an attempt to answer the old and honorable philosophical
question, namely," when can empirical testing on its own validate a law of
nature?" Our message is that the answer depends on what one starts with,
namely, what is one's prior distribution, what unknown does this prior
distribution endow, and what has been observed as data.
  The paper is expository in that it begins with a historical overview, and
ends with some new ideas and proposals for addressing the question posed. In
the sequel, it also articulates on Popper's notion of "propensity" and its role
in providing a proper framework for Bayesian inference under Bernoulli trials,
as well as the need to engage with posterior distributions that are
subjectively specified; that is, without a recourse to the usual Bayesian prior
to posterior iteration.
