Optimization method, optimization system for computer programming code and electronic device using the same

Patent metadata

Field	Value
Publication number	US-2022129254-A1
Application number	US-202017109788-A
Country	US
Kind code	A1
Filing date	Dec 2, 2020
Priority date	Oct 23, 2020
Publication date	Apr 28, 2022
Grant date	—

Abstract

An optimization method, an optimization system for computer programming code and an electronic device using the same are provided. The optimization method includes the following steps. Several optimizers each having several branch paths are provided. A counter is set on each of the branch paths. When the optimizers run through the branch paths, the counters set on the branch paths, where the optimizer run through, are counted. The computer programming code is compiled through the optimizers. Several count values of the counters are obtained. The count values are collected to obtain a feature vector of the computer programming code. The feature vector is inputted to a machine learning model to obtain an optimizer collection suitable for the computer programming code.

First claim

What is claimed is:

1 . An optimization method for computer programming code, comprising:
providing a plurality of optimizers each having a plurality of branch paths; setting a counter on each of the branch paths, wherein when the optimizers run through the branch paths, the counters set on the branch paths, where the optimizers run through, are counted; complying the computer programming code through the optimizers; obtaining a plurality of count values of the counters; collecting the count values to obtain a feature vector of the computer programming code; and inputting the feature vector to a machine learning model to obtain an optimizer collection suitable for the computer programming code.

2 . The optimization method for the computer programming code according to claim 1 , wherein the counters are set on all of the branch paths of the optimizers.

3 . The optimization method for the computer programming code according to claim 1 , wherein the branch paths comprise paths of if-else command, switch-case command, while-loop command, for-loop command, do-loop command, branch command, loop command or a combination thereof.

4 . The optimization method for the computer programming code according to claim 1 , wherein each of the branch paths is a two-branch path, a path with more than two branches or a loop path.

5 . The optimization method for the computer programming code according to claim 1 , wherein the count values are arranged as the feature vector according to a predetermined order.

6 . The optimization method for the computer programming code according to claim 1 , wherein the feature vector is a one-dimensional vector.

7 . An optimization system for computer programming code, wherein the optimization system comprises:
a database configured to store a plurality of optimizers each having a plurality of branch paths; a setting unit configured to set a counter on each of the branch paths, wherein when the optimizers run through the branch paths, the counters set on the branch paths, where the optimizers run through, are counted; a compiling unit configured to compile the computer programming code through the optimizers; a value taking unit configured to obtain a plurality of count values of the counters; a collection unit configured to collect the count values to obtain a feature vector of the computer programming code; and a machine learning analysis unit configured to input the feature vector to a machine learning model to obtain an optimizer collection suitable for the computer programming code.

8 . The optimization system for the computer programming code according to claim 7 , wherein the setting unit sets the counters on all of the branch paths of the optimizers.

9 . The optimization system for the computer programming code according to claim 7 , wherein the branch paths comprise paths of if-else command, switch-case command, while-loop command, for-loop command, do-loop command, branch command, loop command or a combination thereof.

10 . The optimization system for the computer programming code according to claim 7 , wherein each of the branch paths is a two-branch path, a path with more than two branches or a loop path.

11 . The optimization system for the computer programming code according to claim 7 , wherein the count values are arranged as the feature vector according to a predetermined order.

12 . The optimization system for the computer programming code according to claim 7 , wherein the feature vector is a one-dimensional vector.

13 . An electronic device, comprising a processor configured to perform an optimization method for computer programming code, wherein the processor performing comprises:
providing a plurality of optimizers each having a plurality of branch paths; setting a counter on each of the branch paths, wherein when the optimizers run through the branch paths, the counters set on the branch path, where the optimizers run through, are counted; complying the computer programming code through the optimizers; obtaining a plurality of count values of the counters; collecting the count values to obtain a feature vector of the computer programming code; and inputting the feature vector to a machine learning model to obtain an optimizer collection suitable for the computer programming code.

14 . The electronic device according to claim 13 , wherein the counters are set on all of the branch paths of the optimizers.

15 . The electronic device according to claim 13 , wherein the branch paths comprise paths of if-else command, switch-case command, while-loop command, for-loop command, do-loop command, branch command, loop command or a combination thereof.

16 . The electronic device according to claim 13 , wherein each of the branch paths is a two-branch path, a path with more than two branches, or a loop path.

17 . The electronic device according to claim 13 , wherein the count values are arranged as the feature vector according to a predetermined order.

18 . The electronic device according to claim 13 , wherein the feature vector is a one-dimensional vector.

Assignees

• Ind Tech Res Inst

Inventors

• Chang Jia-Rung
• Su Yi-Chiao
• Hsieh Tien-Yuan
• You Yi-Ping

Classifications

• G06F8/4441 Primary

  Reducing the execution time required by the program code · CPC title

• G06F8/443 Primary

  Optimisation · CPC title

• G06N20/00

  Machine learning · CPC title