Generating program analysis rules based on coding standard documents

Patent metadata

Field	Value
Publication number	US-11023210-B2
Application number	US-201916358743-A
Country	US
Kind code	B2
Filing date	Mar 20, 2019
Priority date	Mar 20, 2019
Publication date	Jun 1, 2021
Grant date	Jun 1, 2021

Abstract

In an approach to generating program analysis rules, one or more computer processors identify one or more unassociated code standard documents. The one or more computer processors feed the one or more unassociated code standard documents into a cognitive model, wherein the cognitive model utilizes one or more historical code standard documents based on the unassociated code standard documents and associated program analysis rules based on the unassociated code standard documents, wherein the historical code standard documents are natural language documents and the program analysis rules are programmatic. The one or more computer processors generate, based on one or more calculations by the cognitive model, one or more program analysis rules. The one or more computer processors correct one or more programmatic errors or one or more stylistic errors based on the generated one or more program analysis rules.

First claim

What is claimed is:

1. A method comprising:
identifying, by one or more computer processors, one or more unassociated code standard documents;
feeding, by one or more computer processors, the one or more unassociated code standard documents into a cognitive model, wherein the cognitive model utilizes one or more historical code standard documents based on the unassociated code standard documents and associated program analysis rules based on the unassociated code standard documents, wherein the historical code standard documents are natural language documents and the program analysis rules are programmatic;
generating, by one or more computer processors, based on one or more calculations by the cognitive model, one or more program analysis rules; and
correcting, by one or more computer processors, one or more programmatic errors or one or more stylistic errors based on the generated one or more program analysis rules.

2. The method of claim 1 , further comprises:
creating, by one or more computer processors, one or more training sets based on the retrieved historical code standard documents and associated program analysis rules;
creating, by one or more computer processors, one or more testing sets based on the retrieved code standard documents and associated program analysis rules; and
training, by one or more computer processors, the cognitive model utilizing one or more supervised training methods, wherein the supervised training methods utilize the one or more created training sets and testing sets.

3. The method of claim 1 , further comprises:
calculating, by one or more computer processors, one or more cognitive model performance parameters;
determining, by one or more computer processors, whether at least one performance parameters exceeds a performance threshold; and
responsive to determining that at least one performance parameter exceeds the performance threshold; retraining, by one or more computer processors, the cognitive model.

4. The method of claim 1 , further comprises:
exporting, by one or more computer processors, the generated one or more program analysis rules.

5. The method of claim 4 , further comprises:
exporting, by one or more computer processors, the generated one or more program analysis rules to a code repository.

6. The method of claim 4 , further comprises:
exporting, by one or more computer processors, the generated one or more program analysis rules to an integrated development environment.

7. The method of claim 1 , further comprises:
determining, by one or more computer processors, a target application;
retrieving, by one or more computer processors, a rule template associated with the determined target application;
modifying, by one or more computer processors, the generated one or more program analysis rules to conform with the retrieved rule template; and
exporting, by one or more computer processors, the modified rule template.

8. The method of claim 1 , further comprises:
determining, by one or more computer processors, a target programming language;
retrieving, by one or more computer processors, a rule template associated with the determined programming language;
modifying, by one or more computer processors, the generated one or more program analysis rules to conform with the retrieved rule template; and
exporting, by one or more computer processors, the modified rule template.

9. The method of claim 1 , wherein the one or more program analysis rules contains information selected from the group consisting of: target application, target programming language, target system, description of rule, description of corrective measures, and associated rule templates.

10. The method of claim 1 , wherein the cognitive model is a recurrent neural network.

11. A computer program product comprising:
one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the stored program instructions comprising:
program instructions to identify one or more unassociated code standard documents;
program instructions to feed the one or more unassociated code standard documents into a cognitive model, wherein the cognitive model utilizes one or more historical code standard documents based on the unassociated code standard documents and associated program analysis rules based on the unassociated code standard documents, wherein the historical code standard documents are natural language documents and the program analysis rules are programmatic;
program instructions to generate, based on one or more calculations by the cognitive model, one or more program analysis rules; and
program instructions to correct, one or more programmatic errors or one or more stylistic errors based on the generated one or more program analysis rules.

12. The computer program product of claim 11 , further comprises:
program instructions to create one or more training sets based on the retrieved historical code standard documents and associated program analysis rules;
program instructions to create one or more testing sets based on the retrieved code standard documents and associated program analysis rules; and
program instructions to train the cognitive model utilizing one or more supervised training methods, wherein the supervised training methods utilize the one or more created training sets and testing sets.

13. The computer program product of claim 11 , further comprises:
program instructions to calculate one or more cognitive model performance parameters;
program instructions to determine whether at least one performance parameters exceeds a performance threshold; and
responsive to determining that at least one performance parameter exceeds the performance threshold; program instructions to retrain the cognitive model.

14. The computer program product of claim 11 , wherein the cognitive model is a recurrent neural network.

15. The computer program product of claim 11 , wherein the one or more program analysis rules contains information selected from the group consisting of: target application, target programming language, target system, description of rule, description of corrective measures, and associated rule templates.

16. A computer system comprising:
one or more computer processors;
one or more computer readable storage media; and
program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the stored program instructions comprising:
program instructions to identify one or more unassociated code standard documents;
program instructions to feed the one or more unassociated code standard documents into a cognitive model, wherein the cognitive model utilizes one or more historical code standard documents based on the unassociated code standard documents and associated program analysis rules based on the unassociated code standard documents, wherein the historical code standard documents are natural language documents and the program analysis rules are programmatic;
program instructions to generate, based on one or more calculations by the cognitive model, one or more program analysis rules; and
program instructions to correct, one or more programmatic errors or one or more stylistic errors based on the generated one or more program analysis rules.

17. The computer system of claim 16 , further comprises:
program instructions to create one or more training sets based on the retrieved historical code standard documents and associated program analysis rules;
program instructions to create

Assignees

• IBM

Inventors

• Li Yu
• Zhang Zi Lin
• Wang Yingyi
• Guo Miao
• Wang Yi Bin
• Li yao xing

Classifications

• G06N3/047

  Probabilistic or stochastic networks · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N3/044

  Recurrent networks, e.g. Hopfield networks · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06N3/0442

  characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] · CPC title