{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11249887","patent":{"patent_number":"US-11249887","title":"Deep Q-network reinforcement learning for testing case selection and prioritization","assignee":null,"inventors":[],"filing_date":"2020-08-20T00:00:00.000Z","publication_date":"2022-02-15T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F","G06N","G06N","G06N"],"num_claims":12,"abstract":"Systems and methods for automated software test design and implementation. The system and method being able to establish an initial pool of test cases for testing computer code; apply the initial pool of test cases to the computer code in a testing environment to generate test results; preprocess the test results into a predetermined format; extract metadata from the test results; generate a training sequence; calculate a reward value for the pool of test cases; input the training sequence and reward value into a reinforcement learning agent; utilizing the value output from the reinforcement learning agent to produce a ranking list; prioritizing the initial pool of test cases and one or more new test cases based on the ranking list; and applying the prioritized initial pool of test cases and one or more new test cases to the computer code in a testing environment to generate test results."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Deep Q-network reinforcement learning for testing case selection and prioritization","description":"Systems and methods for automated software test design and implementation. The system and method being able to establish an initial pool of test cases for testing computer code; apply the initial pool","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11249887","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11249887","citation_suggestion":"Patentable. \"Deep Q-network reinforcement learning for testing case selection and prioritization\" (US-11249887). https://patentable.app/patents/US-11249887","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11249887","json":"https://patentable.app/api/llm-context/US-11249887","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T15:33:23.186Z"}