Constructing and Evaluating Evolving Web-API Networks - A Complex Network Perspective

Despite the continual increase in the number of Web-APIs available on the internet, it is still challenging for API consumers to discover appropriate Web-APIs that could satisfy requirements. One of the main reasons for this is that Web-APIs registered on online directories such as ProgrammableWeb are in general isolated, as they are registered by diverse providers independently and progressively, ignoring continuous interactions among these APIs, which could enhance their discoverability. In this paper, we propose a method for analyzing the Web service ecosystem, and a complex network-based approach for constructing evolving networks for Web-APIs that are capable of enhancing their discoverability. We first conduct a two-phase analysis: We investigate mashups and Web-APIs interactions in the service ecosystem, and analyze their popularity distributions, and quantitatively measure two key node attachment dimensions within the ecosystem: Preferential Attachment and Similarity. Based on the analysis, we propose two methods for constructing evolving Web-API networks using the theoretical procedures of theBarab asi-Albert and the Popularity-SimilarityOptimizationnetwork models. Finally, we comprehensively evaluate the networks and map their properties with service discoverability using the ProgrammableWeb datasets. The results presented in this work will serve as a practical guide for designing a complex network-based solution for Web-API discovery.