Source code bug prediction
US-2018150742-A1 · May 31, 2018 · US
US10540257B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10540257-B2 |
| Application number | US-201815899965-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 20, 2018 |
| Priority date | Mar 16, 2017 |
| Publication date | Jan 21, 2020 |
| Grant date | Jan 21, 2020 |
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An information processing apparatus includes a memory and a processor coupled to the memory. The processor is configured to obtain a source code. The processor is configured to generate color information by executing conversion processing with regard to the source code while following a rule for converting a character into a color or converting a color of a character in accordance with a type of the character. The processor is configured to output the generated color information.
Opening claim text (preview).
What is claimed is: 1. A non-transitory computer-readable medium storing a program, which when executed by a computer, causes the computer to execute a process comprising: obtaining a source code; generating an image of color information by executing conversion processing with regard to the source code while following a rule for replacing a character with a color in accordance with a type of the character; and outputting the generated image of color information. 2. The non-transitory computer-readable medium according to claim 1 , wherein the rule is a rule for replacing characters with different colors for each evaluation standpoint with respect to the source code. 3. The non-transitory computer-readable medium according to claim 1 , wherein the process further comprises: obtaining another source code; generating another image of color information by executing the conversion processing with regard to the other source code while following the rule; and outputting an evaluation result with respect to the other source code based on a pattern recognition of the image of color information and the another image of color information. 4. The non-transitory computer-readable medium according to claim 3 , wherein the outputting includes outputting different evaluation results for each evaluation standpoint with respect to the other source code based on the pattern recognition of the image of color information and the another image of color information. 5. The non-transitory computer-readable medium according to claim 3 , wherein the process further comprises: dividing the source code into a plurality of partial source codes that are partially superimposed with one another; dividing the other source code into a plurality of other partial source codes that are partially superimposed with one another; and generating the image of color information by executing the conversion processing with respect to the plurality of divided partial source codes and the plurality of other partial source codes while following the rule. 6. An information processing apparatus, comprising: a memory; and a processor coupled to the memory and configured to: obtain a source code, generate an image of color information by executing conversion processing with regard to the source code while following a rule for replacing a character with a color in accordance with a type of the character, and output the generated image of color information. 7. The information processing apparatus according to claim 6 , wherein the rule is a rule for replacing characters with different colors for each evaluation standpoint with respect to the source code. 8. The information processing apparatus according to claim 6 , wherein the processor is further configured to obtain another source code, generate another image of color information by executing the conversion processing with regard to the other source code while following the rule, and output an evaluation result with respect to the other source code based on a pattern recognition of the image of color information and the another image of color information. 9. The information processing apparatus according to claim 8 , wherein the processor outputs different evaluation results for each evaluation standpoint with respect to the other source code based on the pattern recognition of the image of color information and the another image of color information. 10. The information processing apparatus according to claim 8 , wherein the processor is further configured to divide the source code into a plurality of partial source codes that are partially superimposed with one another, divide the other source code into a plurality of other partial source codes that are partially superimposed with one another, and non-transitory computer-readable medium generate the image of color information by executing the conversion processing with respect to the plurality of divided partial source codes and the plurality of other partial source codes while following the rule. 11. A computer-implemented method for evaluating source code, the method comprising: receiving a target source code to be evaluated with a neural network; converting the target source code into at least one image in which characters of the target source code are replaced with color based on a mapping rule; selecting the neural network to evaluate the at least one image; evaluating the at least one image with the selected neural network; and outputting an evaluation result of the target source code based on the evaluating. 12. The method of claim 11 , wherein the converting the target source code into the at least one image includes: generating color information by executing conversion processing with regard to the target source code according the mapping rule for converting a character into a color or converting a color of a character in accordance with a type of the character, and outputting the generated color information as the at least one image. 13. The method of claim 11 , further comprising: dividing the target source code into a plurality of partial source codes, and wherein each partial source code is converted into an image of the at least one image. 14. The method of claim 13 , wherein the divided partial source are partially superimposed with one another. 15. The method of claim 11 , wherein each mapping rule is associated with an evaluation standpoint and each of the converting, selecting and evaluating are performed for a plurality of evaluation standpoints, and the plurality of evaluation standpoints include a readability evaluation standpoint for the target source code, a complexity evaluation standpoint for the target source code, and a comment density evaluation for the target source code. 16. The method of claim 11 , further comprising: obtaining training data for at least one evaluation standpoint for evaluating source code, the at least one evaluation standpoint including at least one of readability, complexity and comment density of the source code. 17. The method of claim 16 , wherein the training data includes an evaluator's analysis of a training source code that is mapped into an image according to the mapping rule for each of the at least one evaluation standpoint. 18. The method of claim 16 , wherein the neural network includes a learnt neural net for each of a plurality of evaluation standpoints for evaluating the target source code and the selecting selects the neural net of the neural network for the evaluating according to the mapping rule corresponding to one of the plurality of evaluation standpoints. 19. The method of claim 18 , further comprising: receiving a training source code; dividing the training source code into a plurality of partial training source codes; converting the plurality of partial training source codes into a plurality of images according to the mapping rule for each of the plurality of evaluation standpoints; generating, with a control application of a server apparatus, a learning unit based on the plurality of images; initializing the learning unit to receive the training data; processing the training data with the learning unit to develop the learnt neural net for each of the plurality of evaluation standpoints. 20. The method of claim 19 , wherein the converting includes generating color information by executing conversion processing with regard to the target source code according the mapping rule for converting a character into a color or converting a color o
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