Abstract: A system and method for estimating software project delivery details is disclosed. The disclosed method and system accurately predicts project delivery details (e.g., person-days, effort, full-time equivalent (FTE), etc.) from input text (e.g., text describing a software project requirements) and project input parameters (e.g., variables, such as logical entities, transactions, individual/team proficiency, team level, duration of project, technology, industry domain, etc.) corresponding to a project scenario. In addition to predicting project delivery details, the disclosed system and method can provide a what-if analysis engine that allows a user to understand the possibilities of project scenarios having certain output.

Abstract: A device may receive requirement data identifying a requirement for modification of software code, and may process the requirement data, with a machine learning model, to identify entities and intents in the software code and to generate a query. The device may process the query, with a code locator model, to encode text of the query into high-dimensional vectors and to identify a semantic similarity between the high-dimensional vectors and code text. The device may process the query, the semantic similarity, and the code text, with a code developer model, to generate metadata, and may utilize the metadata to identify an identifier associated with the software code. The device may determine, utilizing the identifier, a portion of the software code, and may modify the portion of the software code based on the query to generate modified software code. The device may perform actions based on the modified software code.

Abstract: A device may receive requirement data identifying a requirement for modification of software code, and may process the requirement data, with a machine learning model, to identify entities and intents in the software code and to generate a query. The device may process the query, with a code locator model, to encode text of the query into high-dimensional vectors and to identify a semantic similarity between the high-dimensional vectors and code text. The device may process the query, the semantic similarity, and the code text, with a code developer model, to generate metadata, and may utilize the metadata to identify an identifier associated with the software code. The device may determine, utilizing the identifier, a portion of the software code, and may modify the portion of the software code based on the query to generate modified software code. The device may perform actions based on the modified software code.