Artificial intelligence-based intelligent programming assistance

A method for artificial intelligence-based intelligent programming assistance, the method comprising:

• ascertaining, by at least one hardware processor, for a software program that is to be completed, code for the program;
• identifying, by the at least one hardware processor, based on an analysis of the ascertained code and error message-based contextual information generated by a compiler associated with the ascertained code, an error in the ascertained code;
• generating, by the at least one hardware processor, based on the identified error, a resolution to the identified error;
• modifying, by the at least one hardware processor, based on the generated resolution to the identified error, the code for the program to resolve the identified error;
• running, by the at least one hardware processor, the modified ascertained code through the compiler,
• wherein the compiler accepts the modified ascertained code on confirming absence of new errors in the modified ascertained code and that the modified ascertained code includes less number of errors than the ascertained code and
• wherein the compiler rejects the modified ascertained code, wherein the modified ascertained code includes new errors or the modified ascertained code includes greater number of errors than the ascertained code;
• generating, by the at least one hardware processor, based on an analysis of the ascertained code and problem description-based contextual information associated with the ascertained code, a next token associated with the ascertained code;
• generating, by the at least one hardware processor, based on the next token associated with the ascertained code, further code for the program;
• adding, by the at least one hardware processor, the further generated code to the code for the program;
• analyzing, by the at least one hardware processor, for the program, a performance of a user with respect to generation of the code for the program;
• generating, by the at least one hardware processor, based on the analyzed performance of the user, feedback for the user;
• ascertaining, by the at least one hardware processor, from the user, a query associated with the program;
• classifying, by the at least one hardware processor, by utilizing an ontology, the query into a specified concept of a plurality of concepts;
• and
• generating, by the at least one hardware processor, based on an analysis of the classified query, a response to the query.

A non-transitory computer readable medium having stored thereon machine readable instructions, the machine readable instructions, when executed by at least one hardware processor, cause the at least one hardware processor to:

• ascertain, for a software program that is to be completed, code for the program;
• identify, based on an analysis of ascertained code and problem description-based contextual information generated by a compiler associated with the ascertained code, an error in the ascertained code;
• generate based on the identified error, a resolution to the identified error;
• modify based on the generated resolution to the identified error, the ascertained code to resolve the identified error;
• run the modified ascertained code through the compiler,
• wherein the compiler accepts the modified ascertained code on confirming absence of new errors in the modified ascertained code and that the modified ascertained code includes less number of errors than the ascertained code and
• wherein the compiler rejects the modified ascertained code, wherein the modified ascertained code includes new errors or the modified ascertained code includes greater number of errors than the ascertained code;
• generate, based on an analysis of the ascertained code and problem description-based contextual information associated with the ascertained code, a next token associated with the ascertained code;
• generate, based on the next token associated with the ascertained code, further code for the program;
• and
• add the further generated code to the code for the program;
• analyze, for the program, a performance of a user with respect to generation of the code for the program;
• generate, based on the analyzed performance of the user, feedback for the user;
• ascertain, from the user, a query associated with the program;
• classify, by the at least one hardware processor, by utilizing an ontology, the query into a specified concept of a plurality of concepts;
• and
• generate, based on an analysis of the classified query, a response to the query.