| CPC G06F 16/24578 (2019.01) [G06F 16/248 (2019.01)] | 17 Claims |
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8. A method for automatically generating search list rankings of code snippets, the method comprising:
searching one or more source code repositories to identify a plurality of code snippets in response to a search query;
assigning a plurality of weight values to a plurality of ranking parameters, each of the plurality of ranking parameters corresponding to a different type of rating score for plurality of code snippets;
processing the plurality of code snippets using one or more machine learning models to generate a plurality of rating scores for each of the plurality of code snippets, wherein each rating score of the plurality of rating scores applies to a corresponding ranking parameter of the plurality of ranking parameters;
generating a combined score for each of the plurality of code snippets, wherein the combined score for a code snippet is generated by combining the plurality of rating scores for the code snippet according to the plurality of weight values assigned to the corresponding ranking parameters; and
generating and presenting a user interface comprising an ordered list of the plurality of code snippets based on the combined score for each of the plurality of code snippets,
wherein the ranking parameters comprise a popularity score, a relevancy score, a recency score, an engagement score, and a document type score, wherein:
the popularity score is a standardized measurement relative to a popularity of a code snippet;
the relevancy score is a standardized measurement relative to a relevance of a code snippet to the search query;
the recency score is a standardized measurement relative to how recently a code snippet was used;
the engagement score is a standardized measurement relative to an amount of engagement a code snippet receives; and
the document type score is a standardized measurement relative to a type of document from which the code snippet was derived.
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