Full stack software development and multi aspect testing

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Various statistical methods are used to estimate software reliability, to gain accuracy in software reliability prediction the data sets from the software testing results must be in detail and enormous in size. Existing papers have been acquired the reliability with a limited number of datasets, that too acquired from existing templates. This work attempts to create two layers of software design and testing methods to acquire a real-time error dataset. The first one is single system software design and second one is multiuser server-based testing. Using these two types of software design and by employing automatic data testing using Brute force algorithm, dynamic error occurrences of the datasets with time period will be acquired and tabulated, based on the error results. Instead of predicting the accuracy alone, the proposed work will also predict the possible reasons for the error occurrence scenario and tries to provide an optimal solution, using these types of vigorous testing and solutions, various aspects of the software can be measured like user traffic handling capability, possibility of input error combinations etc. For designing purpose, two different type of software one is java for desktop application and another one is python language for multiuser activity will be used to give different flavors in testing results.




Gayathry, G., & Thirumalaiselvi, R. (2019). Full stack software development and multi aspect testing. International Journal of Innovative Technology and Exploring Engineering, 8(10), 2982–2984. https://doi.org/10.35940/ijitee.J1141.0881019

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