Abstract: Example solutions performing software code vulnerability reduction. An input code portion is extracted from input software code. The input code passage may be syntactically incomplete and/or syntactically incorrect. A code vulnerability is detected in the input code portion. A correction of the code vulnerability is made, and an output code portion is generated including the correction. In some examples, a code vulnerability detection tool take, as input, the output from a code completion tool. The output is thus annotated or corrected in real-time, as a user is developing the code.

Abstract: A neural classifier model is used to detect cybersecurity vulnerabilities in the source code predicted by a deep learning code generation model having been trained on source code possibly containing security bugs. Upon the classifier model classifying a given source code snippet as likely containing a cybersecurity vulnerability, a proposed repair for the cybersecurity vulnerability is predicted from a neural decoder transformer model having been trained on non-vulnerable source code. The neural decoder transformer model is used to predict source code that repairs the cybersecurity vulnerability given the source code classified with a cybersecurity vulnerability.

Abstract: A code completion system for a CLI utilizes neural transformer models with attention to generate candidates to complete a line of CLI code. The code completion system uses a first deep learning model to predict at most k candidate command names to follow n immediately preceding lines of CLI code which are presented to a developer. Upon the developer accepting one of the candidate command names, the code completion system uses a second deep learning model to predict at most k parameter strings to complete the line of CLI code.

Abstract: A term-weighting and document-scoring function is used to search for a command line interface (CLI) script that is likely relevant to an operation specified in a natural language query. CLI scripts are created to perform various operations of a CLI-based application. A CLI script is associated with a description document having keywords associated with the individual commands used in the CLI script. The relevance of a CLI script to an intended operation is based on the term-weighting and document-scoring function which is applied to each component of each command in a CLI script and weighted accordingly.

Abstract: A term-weighting and document-scoring function is used to search for a command line interface (CLI) script that is likely relevant to an operation specified in a natural language query. CLI scripts are created to perform various operations of a CLI-based application. A CLI script is associated with a description document having keywords associated with the individual commands used in the CLI script. The relevance of a CLI script to an intended operation is based on the term-weighting and document-scoring function which is applied to each component of each command in a CLI script and weighted accordingly.