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@article{169963,
        author = {Ayushi and Santosh Kumar and Sajin Shibu and Vivek Reddy},
        title = {Web based Api testing tool},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {3342-3346},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169963},
        abstract = {Testing of net APIs is these days extra vital than ever before, as they may be the cutting- edge preferred for software program integration. A bug in an   business enterprise's web   API   should   have a big impact both internally (services relying on that API) and externally (third- party programs and end customers). most existing gear and trying out  strategies  require  writing  tests  or  instrumenting the machine beneath take a look at (SUT). the primary goal of this dissertation   is   to   take   net   API   testing   to an unprecedented degree of automation and thoroughness. To this stop, we plan to apply artificial intelligence (AI) strategies for the independent detection of software screw ups. mainly, the idea is to develop clever programs (we call them "bots") capable of generating masses, thousands or even tens of millions of check inputs and to assess whether or not the take a look   at   outputs   are   accurate   based   on: 1) patterns learned from previous executions of the SUT; and a pair of) information received from reading hundreds of comparable programs. Assessment consequences of our preliminary prototype are promising, with insects being routinely detected in a few real- international APIs. [1]},
        keywords = {},
        month = {November},
        }