Method, apparatus and computer program product for predictive configuration management of a software testing system

A computer-implemented method comprising:

• receiving, from a client device and by one or more processors, a requirement request data object, wherein the requirement request data object comprises at least a requirement request description attribute for a software testing task;
• generating, based at least in part on the requirement request description attribute and a supervised machine learning model and by the one or more processors, a predicted complexity attribute and a predicted work track attribute corresponding to the requirement request data object;
• generating, based at least in part on the requirement request description attribute and an unsupervised machine learning model and by the one or more processors, at least one predicted defect description attribute and at least one predicted test case description attribute corresponding to the requirement request data object;
• and
• transmitting, to the client device and by the one or more processors, a prediction data object, wherein:
• (i) the prediction data object comprises the predicted complexity attribute, the predicted work track attribute, the at least one predicted defect description attribute, and the at least one predicted test case description attribute, and (ii) the client device is configured to perform one or more software testing operations corresponding to the software testing task based at least in part on the prediction data object.

A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to:

• receive, from a client device, a requirement request data object, wherein the requirement request data object comprises at least a requirement request description attribute for a software testing task;
• generate, based at least in part on the requirement request description attribute and a supervised machine learning model, at least one of a predicted complexity attribute or a predicted work track attribute corresponding to the requirement request data object;
• generate, based at least in part on the requirement request description attribute and an unsupervised machine learning model, at least one predicted defect description attribute or at least one predicted test case description attribute corresponding to the requirement request data object;
• and
• transmit, to the client device, a prediction data object, wherein:
• (i) the prediction data object comprises at least one of the predicted complexity attribute, the predicted work track attribute, the at least one predicted defect description attribute, or the at least one predicted test case description attribute, and (ii) the client device is configured to perform one or more software testing operations corresponding to the software testing task based at least in part on the prediction data object.