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Context: Conflicts between software requirements bring uncertainties toproduct development. Some great approaches have been proposed to identify theseconflicts. However, they usually require the software requirements representedwith specific templates and/or depend on other external source which is oftenuneasy to build for lots of projects in practice. Objective: We aim to proposean approach Finer Semantic Analysis-based Requirements Conflict Detector(FSARC) to automatically detecting the conflicts between the given naturallanguage functional requirements by analyzing their finer semanticcompositions. Method: We build a harmonized semantic meta-model of functionalrequirements with the form of eight-tuple. Then we propose algorithms toautomatically analyze the linguistic features of requirements and to annotatethe semantic elements for their semantic model construction. And we defineseven types of conflicts as long as their heuristic detecting rules on theground of their text pattern and semantical dependency. Finally, we design andimplement the algorithm for conflicts detection. Results: The experiment withfour requirement datasets illustrates that the recall of FSARC is nearly 100%and the average precision is 83.88% on conflicts detection. Conclusion: Weprovide a useful tool for detecting the conflicts between natural languagefunctional requirements to improve the quality of the final requirements set.Besides, our approach is capable of transforming the natural languagefunctional requirements into eight semantic tuples, which is useful not onlythe detection of the conflicts between requirements but also some other taskssuch as constructing the association between requirements and so on.

Automatically detecting the conflicts between software requirements based on finer semantic analysis