Abstract: A device may receive developer profile data identifying developers associated with different technology communities and technology domains and may assign attributes and weights to the developer profile data to generate weighted developer profile data. The device may utilize a first machine learning model, with the weighted developer profile data, to calculate similarity indexes identifying developers associated with multiple technology communities, and may process the weighted developer profile data and the similarity indexes, with a second machine learning model, to calculate developer activity scores for the technology domains and for developer classifications. The device may identify, based on the developer activity scores, a particular developer profile with a greatest developer activity score, and may process the particular developer profile, with a third machine learning model, to determine an engagement strategy for addressing the particular developer.

Abstract: A dynamic application testing and scoring system that tests applications under various tenets and categorizes the applications to be published, to be further reviewed or rejected. The results from administering a plurality of tests to an application are analyzed by applying rulesets that pertain to criteria under each of the tenets. An application score is determined from the analysis using weights associated with the tenets, priority levels of the criteria and the severity levels of the rulesets. The application score identifies a position for the application on a scoring scale relative to two trust threshold values. The application is categorized based on the position. Feedback regarding the categorization is received and the trust threshold values on the scoring scale can be adjusted if the categorization in the feedback is different from the categorization produced by the scoring system.

Abstract: A dynamic application testing and scoring system that tests applications under various tenets and categorizes the applications to be published, to be further reviewed or rejected. The results from administering a plurality of tests to an application are analyzed by applying rulesets that pertain to criteria under each of the tenets. An application score is determined from the analysis using weights associated with the tenets, priority levels of the criteria and the severity levels of the rulesets. The application score identifies a position for the application on a scoring scale relative to two trust threshold values. The application is categorized based on the position. Feedback regarding the categorization is received and the trust threshold values on the scoring scale can be adjusted if the categorization in the feedback is different from the categorization produced by the scoring system.