Application maturity data processing for software development

A method of processing application data comprising:

• receiving responses from users for questions regarding a plurality of criteria applied in development of a software application;
• generating a set of response clusters from the responses, wherein the response clusters cluster the responses based on a corresponding one of the plurality of criteria;
• extracting information extracted from one or more external data sources,
• wherein the information includes search results associated with the plurality of criteria;
• generating a set of result clusters from the search results extracted from the one or more external data sources;
• obtaining, from a decision tree classifier, a maturity level associated with each of the set of response clusters and the set of result clusters with respect to the plurality of criteria;
• identifying one or more gaps in the maturity levels of one or more response clusters of the set of response clusters with respect to at least one criterion of the plurality of criteria,
• wherein the one or more gaps are identified based on lower maturity levels of the at least one criterion;
• automatically generating recommendations for improving corresponding maturity levels of corresponding development stages with the lower maturity levels,
• wherein the recommendations are generated from the set of result clusters.

A non-transitory processor-readable storage medium comprising machine-readable instructions that cause a processor to:

• receive responses from users for questions regarding a plurality of criteria applied in development of a software application;
• generate a set of response clusters from the responses, wherein the response clusters cluster the responses based on a corresponding one of the plurality of criteria;
• extract information extracted from one or more external data sources as search results associated with the plurality of criteria;
• generate a set of result clusters from the search results extracted from the one or more external data sources;
• obtain, from a decision tree classifier, a maturity level associated with each of the set of response clusters and the set of result clusters with respect to the plurality of criteria;
• identify one or more gaps in the maturity levels of one or more response clusters of the set of response clusters with respect to at least one criterion of the plurality of criteria,
• wherein the one or more gaps are identified based on lower maturity levels of the at least one criterion;
• automatically generate recommendations for improving the lower maturity levels of the at least one criterion,
• wherein the recommendations are generated from one or more result clusters of the set of result clusters.