An improved framework for detecting and preventing concurrent bug occurrences in software development

Abstract

Software development is the process of developing complete newlineand efficient software products with the satisfaction level of user newlinerequirements. However concurrent bugs would affect the process of software newlinedevelopment phase where the bug present in one module would affect the newlineentire program execution by forwarding those incorrect prediction data to the newlineexisting values. The difficulty in finding and removing of the concurrent newlinebugs present in the software program motivates to propose the approaches newlinethat can find the concurrent bugs efficiently. The proposed research newlinemethodology is mainly focused to detect and eliminate the concurrent bugs newlineand this process increase the time of the source code execution. newlineToken Issue and Learning based Anticipate Variance Detection newlineSystem (TI-LAVDS) is introduced, which is based on token and the learning newlinemethodologies. The concurrent bug occurrence is avoided by using the token newlinebased methodology where it issues token to the source code instruction and it newlinelimits the source code execution. This method allows to process the newlineinstruction with the exact token. with the use of reinforcement learning newlinemethodology, the concurrent bug detection processes are improved by newlinestudying the source code formation. newline newline