Abstract: A system includes processor(s) configured to: receive natural language text describing software requirements for software program; analyze natural language text describing software requirements to identify relationships between different software requirements at least in part by: analyzing how data flows between different software requirements; analyzing how different software requirements influence path and decision points to achieve functionality identified by software requirements; and identifying dependencies between different software requirements; establish sequence for different software requirements based on relationships identified between different software requirements; group plurality of different software requirements together into logical group(s) of software requirements based on sequence for different software requirements and relationships between different software requirements; generate test cases based on logical group(s) of software requirements; execute software program using test cases;

Abstract: Using artificial intelligence, arbitrary synthetic three dimensional weather data may be generated using descriptive information about at least one weather element. A weather element is a type of weather such as rain, wind, cloud, and any other type of weather regardless of complexity; descriptive information of a weather element may include weather type and/or characteristics of the weather type (e.g., relative position with respect to a body, dimensions, shape, intensity, and or any other characteristic of the weather type). Such descriptive information of a weather element may be provided as text, image(s), and/or any other form of descriptive information. Optionally, such synthetic three dimensional weather data may be received by a two dimensional weather algorithm to ascertain whether the algorithm properly processes such data into a two dimensional image. Thus, the two dimensional weather algorithm may be evaluated over a more diverse range of weather conditions to ensure its accuracy.

Abstract: A system comprises a set of databases in communication with a processor, and a requirements validation AI engine hosted by the processor. The databases comprise software requirements, regulatory guidelines, historical requirements defects, requirements review checklist, and prompts. The AI engine communicates with the databases, and a fine-tuned LLM communicates with the AI engine. A user interface communicates with the AI engine, and a configuration management repository communicates with the user interface. The user interface sends new requirements, from the configuration management repository, with corresponding check instructions to the AI engine, which selects prompts for review, based on types of new requirements and the check instructions. The AI engine sends the prompts and the new requirements to the LLM to review for any defects in the new requirements. The LLM sends a response to the user interface, to report on validity of and any defects in the new requirements.

Abstract: Techniques are generating a test plan, based on test requirements, using artificial intelligence (AI) whilst avoiding hallucinations. Hallucinations in the AI generated test plan may be reduced by utilizing generative AI and providing the generative AI with pre-defined custom templates, test plan guidelines, and/or information for selecting a test environment based on test type. Additionally or alternatively, a similarity between the test plan and a similar test plan may be determined to avoid hallucinations.

Abstract: A system includes processor(s) configured to: receive natural language text describing software requirements for software program; analyze natural language text describing software requirements to identify relationships between different software requirements at least in part by: analyzing how data flows between different software requirements; analyzing how different software requirements influence path and decision points to achieve functionality identified by software requirements; and identifying dependencies between different software requirements; establish sequence for different software requirements based on relationships identified between different software requirements; group plurality of different software requirements together into logical group(s) of software requirements based on sequence for different software requirements and relationships between different software requirements; generate test cases based on logical group(s) of software requirements; execute software program using test cases;