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Web API evolution patterns: A usage-driven approach

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10.1016/j.jss.2023.111609
 
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Koçi, RedianaMés informacióMés informació
Franch Gutiérrez, JavierMés informacióMés informacióMés informació
Jovanovic, PetarMés informacióMés informacióMés informació
Abelló Gamazo, AlbertoMés informacióMés informacióMés informació
Document typeArticle
Defense date2023-01-12
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 4.0 International
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 4.0 International
ProjectDESARROLLO, OPERATIVA Y GOBERNANZA DE DATOS PARA SISTEMAS SOFTWARE BASADOS EN APRENDIZAJE AUTOMATICO (AEI-PID2020-117191RB-I00)
Abstract
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.
CitationKoçi, R. [et al.]. Web API evolution patterns: A usage-driven approach. "Journal of systems and software", 12 Gener 2023, vol. 198, article 111609, p. 1-17. 
URIhttp://hdl.handle.net/2117/380168
DOI10.1016/j.jss.2023.111609
ISSN0164-1212
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S0164121223000043
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  • Doctorat en Computació - Articles de revista [35]
  • Departament d'Enginyeria de Serveis i Sistemes d'Informació - Articles de revista [203]
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