PatternLens: Inferring evolutive patterns from web API usage logs

Abstract

The use of web Application Programming Interfaces (WAPIs) has experienced a boost in recent years. Developers (i.e., WAPI consumers) are continuously relying on third-party WAPIs to incorporate certain features into their applications. Consequently, WAPI evolution becomes more challenging in terms of the service provided according to consumers' needs. When deciding on which changes to perform, besides several dynamic business requirements (from the organization whose data are exposed), WAPI providers should take into account the way consumers use the WAPI. While consumers may report various bugs or may request new endpoints, their feedback may be partial and biased (based on the specific endpoints they use). Alternatively, WAPI providers could exploit the interaction between consumers and WAPIs, which is recorded in the WAPI usage logs, generated while consumers access the WAPI. In this direction, this paper presents PatternLens, a tool with the aim of supporting providers in planning the changes by analyzing WAPI usage logs. With the use of process mining techniques, this tool infers from the logs a set of usage patterns (e.g., endpoints that are frequently called one after the other), whose occurrences imply the need for potential changes (e.g., merging the two endpoints). The WAPI providers can accept or reject the suggested patterns, which will be displayed together with informative metrics. These metrics will help providers in the decision-making, by giving them information about the consequences of accepting/rejecting the suggestions.

Exploratory Analysis of the Structural Evolution of public REST APIs

“…[ Koc ¸i et al 2021b, Koc ¸i et al 2021a][Koc ¸i et al 2020 propose to inform providers about API usage patterns and usability by regarding the interaction of consumers with APIs reported in logs. Finally, [Di Lauro et al 2021] study evolution by mining open-source API versions specified in the OpenAPI standard.…”

A data-driven approach to prescribe web API evolution

“…Building upon these previous results, in this paper we extend the goal of [44] and elaborately introduce a method to help providers in the evolution of their WAPIs. We keep the position that WAPIs evolution should be mainly usage-based, i.e., the way consumers use WAPIs should be one of the main drivers of WAPI changes [3].…”

“…Previously, we analyzed WAPI development usage logs (logs generated when consumers are developing and testing their applications) [42] and prescribed a set of usability-related changes. Then, we focused our research on production logs analysis (generated after consumers' applications' release) and presented our preliminary results through a tool that aims to support providers in planning the changes [44].…”