RANKING PEER SUBMITTED CODE SNIPPETS USING EXECUTION FEEDBACK

Patent №

US 8,756,576

Granted

2014-06-17

Filed 2008

Owner

INTERNATIONAL BUSINESS MACHINES CORPORATION

AI components

4

nlp · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

12195373

A method, system and program product for providing execution feedback of peer submitted code snippets executed for correction of semantic errors in code. A first developer executing a code snippet to correct a semantic error in the use of a third-party library within a first IDE results in the transmission of an execution result to a collaboration datastore. If the code snippet execution completed with no errors, a result indicating a success is automatically transmitted by the IDE. Further, if the code snippet execution resulted in an error due to error within the code snippet, a result indicating code snippet failure along with error details is automatically transmitted. When a second developer is working on code within a second IDE that contains semantic errors, code snippets to correct the semantic error are presented to the second developer, ranked based on previous execution feedback provided by peer developers.

AI classification

Natural language1.00
Planning1.00
AI hardware0.90
Knowledge representation0.80
Machine learning0.04
Evolutionary computation0.00
Vision0.00
Speech0.00

Ownership

INTERNATIONAL BUSINESS MACHINES CORPORATION

assignment · 214190681

Assignors

BALASUBRAMANIAN, SWAMINATHAN

On an employer assignment, the assignors are typically the inventors.

From the same owner

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