IP Library › Granted Patent US 9,766,868
Granted Patent B2
US 9,766,868 · App. 15/010,185 · Granted Sep 19, 2017

Dynamic source code generation

Inventors: Corville O. Allen (Morrisville, NC); Heather L. Duschl (Raleigh, NC); Marit L. Imsdahl (Cary, NC); Alexandra D Markello (Fayetteville, NC); Dana L. Price (Surf City, NC)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06F8/447G06F8/30G06F8/40G06F8/41G06F8/427G06F17/2705G06N99/005
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Quick Facts
Patent No.
US 9,766,868
App. No.
15/010,185
Granted
Sep 19, 2017
Kind
B2
Abstract

Embodiments include method, systems and computer program products for dynamic source code generation. In some embodiments, a request comprising data may be received. Parsed natural language may be generated using the data. Knowledgebase data may be obtained. Source code may be generated based on the parsed natural language and the knowledgebase data. The generate source code may be transmitted in response to the request.

Claims (50)

1. A computer-implemented method comprising:

receiving a request comprising natural language data;

generating parsed natural language data and metadata from the natural language data;

obtaining knowledgebase data, wherein the knowledgebase data comprises at least one weighted mapping between a natural language problem and a corresponding source code, the natural language problem and the corresponding source code being determined by processing electronic data, the electronic data comprising at least one of an electronic textbook, a scan of a textbook, and computer science literature, the at least one weighted mapping between the natural language problem and the corresponding source code being generated by weighting the mapping according to at least one of a date the electronic data was published, a reputation or ranking of a publisher of the electronic data, and a rating of the electronic data by users;

generating source code based on the parsed natural language data and the knowledgebase data by applying machine learning to the parsed natural language data and the metadata using the knowledgebase data; and

transmitting the generated source code in response to the request.

2. The computer-implemented method of claim 1 , wherein the data is a natural language problem statement.

3. The computer-implemented method of claim 1 , wherein obtaining knowledgebase data further comprises:

obtaining the knowledgebase data from a datastore.

4. The computer-implemented method of claim 1 , wherein generating the source code further comprises:

generating the source code by applying machine learning to the parsed natural language data using the knowledgebase data.

5. The computer-implemented method of claim 1 , wherein the request comprises an indication of a programming language for the source code.

6. The computer-implemented method of claim 1 , wherein transmitting the source code further comprises:

transmitting the source code to a datastore; and

transmitting a notification in response to the request indicating a location of the source code.

7. The computer-implemented method of claim 1 , further comprising:

processing the data to obtain a natural language problem statement.

8. A computer program product comprising a non-transitory storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising:

receiving a request comprising natural language data;

generating parsed natural language data and metadata from the natural language data;

obtaining knowledgebase data, wherein the knowledgebase data comprises at least one weighted mapping between a natural language problem and a corresponding source code, the natural language problem and the corresponding source code being determined by processing electronic data, the electronic data comprising at least one of an electronic textbook, a scan of a textbook, and computer science literature, the at least one weighted mapping between the natural language problem and the corresponding source code being generated by weighting the mapping according to at least one of a date the electronic data was published, a reputation or ranking of a publisher of the electronic data, and a rating of the electronic data by users;

generating source code based on the parsed natural language data and the knowledgebase data applying machine learning to the parsed natural language data and the metadata using the knowledgebase data; and

transmitting the generated source code in response to the request.

9. The computer program product of claim 8 , wherein the data is a natural language problem statement.

10. The computer program product of claim 8 , wherein obtaining knowledgebase data further comprises:

obtaining the knowledgebase data from a datastore.

11. The computer program product of claim 8 , wherein generating the source code further comprises:

generating the source code by applying machine learning to the parsed natural language data using the knowledgebase data.

12. The computer program product of claim 8 , wherein the request comprises an indication of a programming language for the source code.

13. The computer program product of claim 8 , wherein transmitting the source code further comprises:

transmitting the source code to a datastore; and

transmitting a notification in response to the request indicating a location of the source code.

14. The computer program product of claim 8 , wherein the method further comprises:

processing the data to obtain a natural language problem statement.

15. A system, comprising:

a processor in communication with one or more types of memory, the processor configured to:

receive a request comprising natural language data;

generate parsed natural language data and metadata from the natural language data;

obtain knowledgebase data, wherein the knowledgebase data comprises at least one weighted mapping between a natural language problem and a corresponding source code, the natural language problem and the corresponding source code being determined by processing electronic data, the electronic data comprising at least one of an electronic textbook, a scan of a textbook, and computer science literature, the at least one weighted mapping between the natural language problem and the corresponding source code being generated by weighting the mapping according to at least one of a date the electronic data was published, a reputation or ranking of a publisher of the electronic data, and a rating of the electronic data by users;

generate source code based on the parsed natural language data and the knowledgebase data by applying machine learning to the parsed natural language data and the metadata using the knowledgebase data; and

transmit the generated source code in response to the request.

16. The system of claim 15 , wherein the data is a natural language problem statement.

17. The system of claim 15 , wherein, to obtain knowledgebase data, the processor is further configured to:

obtain the knowledgebase data from a datastore.

18. The system of claim 15 , wherein, to generate the source code, the processor is further configured to:

generate the source code by applying machine learning to the parsed natural language data using the knowledgebase data.

19. The system of claim 15 , wherein the request comprises an indication of a programming language for the source code.

20. The system of claim 15 , wherein, to transmit the source code, the processor is further configured to:

transmit the source code to a datastore; and

transmit a notification in response to the request indicating a location of the source code.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 22, 2016
From: ALLEN, CORVILLE O.; DUSCHL, HEATHER L.; IMSDAHL, MARIT L.; MARKELLO, ALEXANDRA D.; PRICE, DANA L.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 037783/0921 →
Continuity (1)
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