Early dealing with evolving risks in long-life evolving software systems

Abstract

Existing risk assessment methods often rely on a context of a target software system at a particular point in time. Such contexts of long-living software systems tend to evolve over time. Consequently, risks might also evolve. Therefore, in order to deal with evolving risks, decision makers need to select an appropriate risk countermeasure alternative that is more resilient to evolution than others. To facilitate such decision, we propose a pioneer method taking the uncertainty of evolutions and outputs of a risk assessment to produce additional information about the evolution resilience of countermeasure alternatives. © 2013 Springer-Verlag.