Abstract: A computer-implemented method of detecting a likely software malfunction is provided. The method comprises collecting a plurality of software error data sets wherein each software error data set comprises a proposed code section containing an error and a corrected code section containing code changes that fixed the error in the proposed code section. The method further comprises training a computer-implemented algorithmic model using the collected software error data sets to devise a software code classifier for predicting a likely error in a code section, reviewing a section of code using the software code classifier, and identifying suspicious code in the reviewed section of code as containing a suspected error using the software code classifier.

Abstract: A tool for installing and configuring a software development environment with an embedded help feature is provided. The help feature may provide a user (e.g., developer) with technical assistance to resolve problems that occur when building software. In one example, the system may include a configuration tool that includes a help feature and installs and configures one or more software programs to build software. The software programs may include, for example, operating systems, source code editors, debuggers, software build tools or any component of a software development environment.

Abstract: A computer-implemented method of detecting a likely software malfunction is provided. The method comprises collecting a plurality of software error data sets wherein each software error data set comprises a proposed code section containing an error and a corrected code section containing code changes that fixed the error in the proposed code section. The method further comprises training a computer-implemented algorithmic model using the collected software error data sets to devise a software code classifier for predicting a likely error in a code section, reviewing a section of code using the software code classifier, and identifying suspicious code in the reviewed section of code as containing a suspected error using the software code classifier.

Abstract: Systems and methods are provided for classifying support-related messages from users in a support-related group. A method includes receiving a support-related message containing a support-related problem. The received support-related message is classified by using a processor-implemented machine learning model to identify a support-related category. The identified support-related category is provided for user display.

Abstract: A tool for installing and configuring a software development environment with an embedded help feature is provided. The help feature may provide a user (e.g., developer) with technical assistance to resolve problems that occur when building software. In one example, the system may include a configuration tool that includes a help feature and installs and configures one or more software programs to build software. The software programs may include, for example, operating systems, source code editors, debuggers, software build tools or any component of a software development environment.