The development of software nowadays
is getting more complex due to the need to use software programs to accomplish more elaborated tasks.
Developers may have a hard time knowing what could happen to the software when
making changes. To
support the developer in reducing the uncertainty of the impact on the software
run behavior due to changes in the source code, this paper presents a tool
called IMPEX which analyzes the differences in the source code and differences
on the run behavior of two subsequent software versions, in the entire
repository, demonstrating to the developer the impact that a change in the
source code has had on the software run, over the whole software history. This
impact helps the developers in knowing what is affected during execution due to
their changes in the source code. This study verifies that the software runs
that are most impacted by a given change in the source code, have higher
chances in being impacted in the future whenever this part of the code is
changed again. The approach taken in this paper was able to precisely predict
what would be impacted on the software execution when a change in the source
code was made in 70% of the cases.
Many biodiversity researchers have
responded to the financial constraints faced by policy makers to develop models
based upon the “Noah’s Ark” metaphor, implying that society can save only a
limited amount of biodiversity. Unfortunately, as Herman Daly (Land Economics, 1991) pointed out, such
microeconomic rules can allow an ark to sink albeit in some optimal fashion.
So, I step back to look at the macroeconomic question, how big should the ark
be? I start with Norgaard’s (Ecological
Economics, 2010) framework, which is based upon the concept of a production
possibility frontier combined with a sustainability criterion. I develop a
model from that starting point by shifting to an isoquant framework while
maintaining the strong sustainability criterion. I demonstrate how this model
allows for identifying and addressing the key biodiversity protection policy
criteria at the macroeconomic level. One key conclusion from this modeling is
that Daly’s analysis remains remarkably prescient.