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In goal-oriented requirements engineering, goal conflict identification is offundamental importance for requirements analysis. The task aims to find thefeasible situations which make the goals diverge within the domain, calledboundary conditions (BCs). However, the existing approaches for goal conflictidentification fail to find sufficient BCs and general BCs which cover morecombinations of circumstances. From the BCs found by these existing approaches,we have observed an interesting phenomenon that there are some pairs of BCs aresimilar in formula structure, which occurs frequently in the experimentalcases. In other words, once a BC is found, a new BC may be discovered quicklyby slightly changing the former. It inspires us to develop a local searchalgorithm named LOGION to find BCs, in which the structural similarity iscaptured by the neighborhood relation of formulae. Based on structuralsimilarity, LOGION can find a lot of BCs in a short time. Moreover, due to thelarge number of BCs identified, it potentially selects more general BCs fromthem. By taking experiments on a set of cases, we show that LOGION effectivelyexploits the structural similarity of BCs. We also compare our algorithmagainst the two state-of-the-art approaches. The experimental results show thatLOGION produces one order of magnitude more BCs than the state-of-the-artapproaches and confirm that LOGION finds out more general BCs thanks to a largenumber of BCs.

Structural Similarity of Boundary Conditions and an Efficient Local Search Algorithm for Goal Conflict Identification