Abstract: The need to merge software artifacts seems inherent
to modern software development. Distribution of development over
several teams and breaking tasks into smaller, more manageable
pieces are an effective means to deal with the kind of complexity. In
each case, the separately developed artifacts need to be assembled as
efficiently as possible into a consistent whole in which the parts still
function as described. In addition, earlier changes are introduced into
the life cycle and easier is their management by designers.
Interaction-based specifications such as UML sequence diagrams
have been found effective in this regard. As a result, sequence
diagrams can be used not only for capturing system behaviors but
also for merging changes in order to create a new version. The
objective of this paper is to suggest a new approach to deal with the
problem of software merging at the level of sequence diagrams by
using the concept of dependence analysis that captures, formally, all
mapping, and differences between elements of sequence diagrams
and serves as a key concept to create a new version of sequence
diagram.
Abstract: In this paper, we present a model-based regression test
suite reducing approach that uses EFSM model dependence analysis
and probability-driven greedy algorithm to reduce software regression
test suites. The approach automatically identifies the difference
between the original model and the modified model as a set of
elementary model modifications. The EFSM dependence analysis is
performed for each elementary modification to reduce the regression
test suite, and then the probability-driven greedy algorithm is adopted
to select the minimum set of test cases from the reduced regression test
suite that cover all interaction patterns. Our initial experience shows
that the approach may significantly reduce the size of regression test
suites.