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    RESTful API Testing Methodologies: Rationale, Challenges, and Solution Directions

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    applsci-12-04369.pdf (1.239Mb)
    Date
    2022
    Author
    Ehsan, Adeel
    Abuhaliqa, Mohammed Ahmad M. E.
    Catal, Cagatay
    Mishra, Deepti
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    Abstract
    Service-oriented architecture has evolved to be the backbone for large-scale integration between different applications and platforms. This concept has led to today's reality of cloud services. Many of the major business platforms are providing their services to end-users and other companies as well. Companies are crafting ways to allow other businesses fast service integration and to get on board quickly in the market. REST (representational state transfer) has emerged as the standard protocol for implementing and consuming these services, which are called RESTful application programming interfaces (APIs). As the internal details of the RESTful APIs are not completely available during consumption, thorough testing has been a major challenge. Any unprecedented change in the APIs can cause the major failure of service operations, which can cause an organization to face both financial and trust losses. Research efforts have been made to alleviate testing challenges by introducing different frameworks and auto-generating unit test approaches. However, there is still a lack of an overview of the state-of-the-art in RESTful API testing. As such, the objective of this article is to identify, analyze, and synthesize the studies that have been performed related to RESTful APIs' testing methodologies and unit test generation. With this perspective, a systematic literature review (SLR) study was conducted. In total, 16 papers were retrieved and included based on study selection criteria for in-depth analysis. This SLR discusses and categorizes different problems and solutions related to RESTful APIs' testing and unit test generation. 2022 by the authors. Licensee MDPI, Basel, Switzerland.
    DOI/handle
    http://dx.doi.org/10.3390/app12094369
    http://hdl.handle.net/10576/36783
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    • Computer Science & Engineering [‎2428‎ items ]

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