  In goal-oriented requirements engineering, goal conflict identification is of
fundamental importance for requirements analysis. The task aims to find the
feasible situations which make the goals diverge within the domain, called
boundary conditions (BCs). However, the existing approaches for goal conflict
identification fail to find sufficient BCs and general BCs which cover more
combinations of circumstances. From the BCs found by these existing approaches,
we have observed an interesting phenomenon that there are some pairs of BCs are
similar in formula structure, which occurs frequently in the experimental
cases. In other words, once a BC is found, a new BC may be discovered quickly
by slightly changing the former. It inspires us to develop a local search
algorithm named LOGION to find BCs, in which the structural similarity is
captured by the neighborhood relation of formulae. Based on structural
similarity, LOGION can find a lot of BCs in a short time. Moreover, due to the
large number of BCs identified, it potentially selects more general BCs from
them. By taking experiments on a set of cases, we show that LOGION effectively
exploits the structural similarity of BCs. We also compare our algorithm
against the two state-of-the-art approaches. The experimental results show that
LOGION produces one order of magnitude more BCs than the state-of-the-art
approaches and confirm that LOGION finds out more general BCs thanks to a large
number of BCs.
