System for discovering semantic relationships in computer programs

A system comprising:

• a memory that stores instructions;
• and
• a processor that executes the instructions to perform operations, the operations comprising:
• analyzing, for a semantic relationship discovery process, information provided by a source, wherein the information is associated with an application under evaluation by the system and is actively extracted from interactions conducted with the application under evaluation while the application under evaluation is under evaluation by the system;
• determining, based on the analyzing of the information provided by the source, a concept associated with data elements in the information, a relationship between the data elements in the information, a grouping associated with the data elements in the information, or a combination thereof;
• generating, based on the analyzing of the information, a constraint suggestion for the application under evaluation;
• generating, based on the constraint suggestion, a hypothesis associated with the concept, the relationship, the grouping, or a combination thereof;
• ranking the hypothesis relative to other hypotheses generated by the system based on a confidence level of the hypothesis and confidence levels of the other hypotheses to form a ranked plurality of hypotheses;
• filtering, by applying a confidence level threshold to the hypothesis, a subset of hypotheses from the ranked plurality of hypotheses that satisfy the confidence level threshold;
• outputting the subset of hypotheses satisfying the confidence level threshold;
• and
• testing the subset of hypotheses against the application under evaluation to confirm or reject the subset of hypotheses;
• and
• training, based on the testing of the subset of hypotheses and based on a confirmation or a rejection of the subset of hypotheses, a model to enhance the determination of the concept, the relationship, the grouping, or a combination thereof, for a subsequent semantic relationship discovery process.

A non-transitory computer-readable device comprising instructions, which when loaded and executed by a processor, cause the processor to perform operations comprising:

• analyzing, for a semantic relationship discovery process, information provided by a source, wherein the information is associated with an application under evaluation by a system and is actively extracted from interactions conducted with the application under evaluation while the application under evaluation is under evaluation by the system;
• determining, based on the analyzing of the information provided by the source, a concept associated with data elements in the information, a relationship between the data elements in the information, a grouping associated with the data elements in the information, or a combination thereof;
• determining, based on the analyzing of the information, a constraint suggestion for the application under evaluation;
• generating, based on the constraint suggestion, a hypothesis associated with the concept, the relationship, the grouping, or a combination thereof, wherein the hypothesis is ranked relative to other hypotheses generated by the system based on a confidence level of the hypothesis and confidence levels of the other hypotheses to form a ranked plurality of hypotheses;
• filtering, by applying a confidence level threshold to the ranked plurality of hypotheses, a subset of hypotheses from the ranked plurality of hypotheses satisfying the confidence level threshold;
• utilizing the subset of hypotheses filtered from the ranked plurality of hypothesis when testing the application under evaluation;
• testing the hypothesis against the application under evaluation to confirm or reject the hypothesis;
• and
• training, based on the testing of the hypothesis and based on a confirmation or a rejection of the hypothesis, a model to enhance the determination of the concept, the relationship, the grouping, or a combination thereof, for a subsequent semantic relationship discovery process.