CODE CONCIERGE MODEL (CCM) FOR PREDICTING RUNTIME ERRORS OF SOURCE CODE

Aspects of the present disclosure relate generally to software development environments and, more particularly, to predicting runtime errors in software development environments. For example, a computer-implemented method includes: clustering similar regions of source code into clusters of code regions; identifying source code exceptions from at least one past execution of an executable image of the source code; deriving a model of features of the source code associated with the source code exceptions for the clusters of code regions; generating a matrix as output of the model that predicts a likelihood of an occurrence of at least one uncaught exception during a future execution of the executable image of the source code in a cluster of the clusters of code regions; and annotating the source code in the code region of the cluster with an indication of the likelihood of the occurrence of the at least one uncaught exception.