Dynamic evaluation and improvement of energy efficiency of computer code

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers, cause the one or more computers to perform operations comprising:

• obtaining code data characterizing a computer code snippet to be executed by a computing device;
• obtaining rule data characterizing one or more energy efficiency rules;
• generating a first input from the code data and a second input from the rule data;
• processing the first input using a first embedding machine-learning model to generate a first embedding feature vector for the computer code snippet;
• processing the second input using a second embedding machine-learning model to generate a second embedding feature vector for the one or more energy efficiency rules;
• processing (i) the first embedding feature vector and (ii) the second embedding feature vector using a code defect detection machine-learning model to generate a detection output comprising data representing one or more portions of the computer code snippet that negatively impact a dynamic energy efficiency of the computer code snippet upon execution by the computing device;
• and
• performing an action based on the detection output.

One or more computer-readable storage media storing instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:

• obtaining code data characterizing a computer code snippet to be executed by a computing device;
• obtaining rule data characterizing one or more energy efficiency rules;
• generating a first input from the code data and a second input from the rule data;
• processing the first input using a first embedding machine-learning model to generate a first embedding feature vector for the computer code snippet;
• processing the second input using a second embedding machine-learning model to generate a second embedding feature vector for the one or more energy efficiency rules;
• processing (i) the first embedding feature vector and (ii) the second embedding feature vector using a code defect detection machine-learning model to generate a detection output comprising data representing one or more portions of the computer code snippet that negatively impact a dynamic energy efficiency of the computer code snippet upon execution by the computing device;
• and
• performing an action based on the detection output.