Abstract: A process includes receiving, by a machine learning support system, an instruction to generate a machine learning model from a plurality of candidate-programs, specifying, for each of the plurality of candidate-programs generated using a program-component included in any of a plurality of program-component sets, a first proficiency-level of a user for a first program-component set which includes a first program-component used in the candidate-program, the first proficiency-level is based on proficiency-level information which indicates a proficiency-level of the user related to use of each of the plurality of program-component sets and is determined based on a use record of the plurality of program-component sets in an editing process of the candidate-program by the user and a change in performance of the candidate-program by the editing process, and determining, for each of the plurality of candidate-programs, a priority to present the candidate-program to the user, based on the specified first proficiency-l

Abstract: A process includes obtaining update history information that includes respective update histories of a plurality of versions of software, the plurality of versions including a first version immediately previous to a second version, identifying, from the update history information, second version that corresponds to the update history that includes a predetermined keyword, identifying, based on development history information that includes a change location in a source code of the software between the first version and the second version, a code block deleted from the source code when the first version is upgraded to the second version, as the code block that includes a possibility of including vulnerability, and detecting, out of the plurality of versions, a third version that includes the identified code block in the source code.