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Extracting conceptual interoperability constraints from API documentation using machine learning

: Abukwaik, Hadil; Abujayyab, Mohammed; Humayoun, Shah Rukh; Rombach, H. Dieter


Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Software Engineering -SIGSOFT-:
ICSE 2016, 38th International Conference on Software Engineering Companion. Proceedings : Austin, Texas, May 14 - 22, 2016
New York: ACM Press, 2016
ISBN: 978-1-4503-4205-6
International Conference on Software Engineering (ICSE) <38, 2016, Austin/Tex.>
Fraunhofer IESE ()
machine learning; application program interfaces

Successfully using a software web-service/platform API requires satisfying its conceptual interoperability constraints that are stated within its shared documentation. However, manual and unguided analysis of text in API documents is a tedious and time consuming task. In this work, we present our empirical-based methodology of using machine learning techniques for automatically identifying conceptual interoperability constraints from natural language text. We also show some initial promising results of our research.