Dynamic Transformation Code Prediction and Generation for Unavailable Data Element

    公开(公告)号:US20220004528A1

    公开(公告)日:2022-01-06

    申请号:US16921078

    申请日:2020-07-06

    Abstract: Aspects of the disclosure relate to dynamic transformation code prediction and generation for an unavailable data element. In some embodiments, a computing platform may execute an extract, transform, and load process on input data received from a plurality of data sources and detect a missing data element in the received input data. Subsequently, the computing platform may generate a prediction model with respect to the missing data element, which may include executing a first, second, and third machine learning algorithm. Next, the computing platform may determine a confidence level of the prediction model. In response to determining that the confidence level is at or above the predetermined threshold, the computing platform may generate executable transformation code implementing the prediction model. Thereafter, the computing platform may monitor transformation code implementations and execute a fourth machine learning algorithm to adjust the prediction model based on the transformation code implementations.

    Software defect analysis tool
    5.
    发明授权

    公开(公告)号:US10133651B2

    公开(公告)日:2018-11-20

    申请号:US15383694

    申请日:2016-12-19

    Abstract: A software defect detection tool determines a modification in a software code at a first time and analyzes an execution of the software code to detect a performance issue at a second time. The software defect detection tool detects a defect in the software code by a comparison of the first time and a second time. A software defect analysis tool generates a cause/category combination for a software code defect. The software defect analysis tool determines whether the cause/category combination is an approved combination and whether the software code defect is a false positive. The software defect analysis tool generates a corrective action plan indicating measures to implement to reduce software defects.

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