Web API evolution patterns: A usage-driven approach

As the use of Application Programming Interfaces (APIs) is increasingly growing, their evolution becomes more challenging in terms of the service provided according to consumers’ needs. In this paper, we address the role of consumers’ needs in WAPIs evolution and introduce a process mining pattern-b...

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Veröffentlicht in:The Journal of systems and software Jg. 198; S. 111609
Hauptverfasser: Koçi, Rediana, Franch, Xavier, Jovanovic, Petar, Abelló, Alberto
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.04.2023
Schlagworte:
Process mining
Usage patterns
Web API evolution
Web API logs
Process mining
Web API logs
Web API evolution
Usage patterns
ISSN:0164-1212, 1873-1228
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Zusammenfassung:As the use of Application Programming Interfaces (APIs) is increasingly growing, their evolution becomes more challenging in terms of the service provided according to consumers’ needs. In this paper, we address the role of consumers’ needs in WAPIs evolution and introduce a process mining pattern-based method to support providers in WAPIs evolution by analyzing and understanding consumers’ behavior, imprinted in WAPI usage logs. We take the position that WAPIs’ evolution should be mainly usage-based, i.e., the way consumers use them should be one of the main drivers of their changes. We start by characterizing the structural relationships between endpoints, and next, we summarize these relationships into a set of behavioral patterns (i.e., usage patterns whose occurrences indicate specific consumers’ behavior like repetitive or consecutive calls), that can potentially imply the need for changes (e.g., creating new parameters for endpoints, merging endpoints). We analyze the logs and extract several metrics for the endpoints and their relationships, to then detect the patterns. We apply our method in two real-world WAPIs from different domains, education, and health, respectively the WAPI of Barcelona School of Informatics at the Polytechnic University of Catalonia (Facultat d’Informàtica de Barcelona, FIB, UPC), and District Health Information Software 2 (DHIS2) WAPI. The feedback from consumers and providers of these WAPIs proved the effectiveness of the detected patterns and confirmed the promising potential of our approach. •WAPI evolution should be driven by the way WAPI is consumed.•Providers can proactively use WAPI usage logs for evolution, applying process mining.•Providers can detect behavioral patterns, that imply the need for changes in WAPI.•The suggested changes address more thoroughly consumers’ needs.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2023.111609