Software commit risk level

Patent metadata

Field	Value
Publication number	US-9921948-B2
Application number	US-201315028725-A
Country	US
Kind code	B2
Filing date	Oct 30, 2013
Priority date	Oct 30, 2013
Publication date	Mar 20, 2018
Grant date	Mar 20, 2018

Abstract

A risk level of a software commit is assessed through the use of a classifier. The classifier may be generated based on attributes pertaining to previous commits and used to determine a risk level for deployment of a software commit into a production environment based on attributes extracted from the software commit.

First claim

What is claimed is:

1. A method, comprising:
generating, by a processor, a classifier for attributes of previous software commits, wherein the previous software commits are code that has already been deployed, and wherein generating the classifier includes classifying the attributes of the previous software commits into three classes: a first class based on a frequency of update of the previous software commits, a second class based on successful levels of the previous software commits, and a third class based on code complexity of the previous software commits;
extracting, by the processor, attributes pertaining to a new software commit, wherein the new software commit is code that has not been deployed; and
running, by the processor, the classifier on the extracted attributes of the new software commit to determine a risk level for deployment of the new software commit into a production environment to determine whether or not to skip a testing phase,
wherein generating the classifier of the previous software commits includes:
removing one of the previous software commits from the data structure,
calculating a classifier on the previous software commits remaining in the data structure,
running the calculated classifier on the removed software commit, and
comparing a risk level label returned by the calculated classifier to an actual risk level label of the removed software commit.

2. The method of claim 1 , wherein the attributes of the new software commit include an attribute that provides information about the new software commit, an attribute that provides information about a label for the new software commit, and an attribute indicative of the code complexity of the new software commit for which the risk level is determined.

3. The method of claim 1 , wherein the risk level includes a plurality of levels.

4. The method of claim 1 , further comprising:
storing the previous software commits in a table of the data structure, the table including a column of the attributes of the previous software commits and a column of labels indicating the successful levels of the previous software commits.

5. A non-transitory computer-readable storage device containing instructions that, when executed by a processor, cause the processor to:
generate a classifier for attributes of previous software commits, wherein the previous software commits are code that has already been deployed;
determine a plurality of attributes pertaining to a new software commit, wherein the new software commit is code that has not been deployed; and
use the classifier to classify the attributes of the new software commit to determine a risk level for deployment of the new software commit into a production environment to determine whether or not to skip a testing phase,
wherein, to generate the classifier, the instructions are to cause the processor to:
remove one of the previous software commits stored in a data structure,
calculate the classifier on the previous software commits remaining in the data structure,
run the calculated classifier on the removed software commit, and

compare a risk level label returned by the calculated classifier to an actual risk level label of the removed software commit.

6. The non-transitory computer-readable storage device of claim 5 , wherein, to generate the classifier for the attributes of the previous software commits, the instructions are to cause the processor to:
classify the attributes of the previous software commits into three classes: a first class based on a frequency of update of the previous software commits, a second class based on successful levels of the previous software commits, and a third class based on code complexity of the previous software commits.

7. The non-transitory computer-readable storage device of claim 6 , wherein, when executed, the instructions are to cause the processor to validate the classifier.

8. The non-transitory computer-readable storage device of claim 5 , wherein the attributes of the new software commit include an attribute that provides information about the new software commit and an attribute that provides information about a label for the new software commit.

9. The non-transitory computer-readable storage device of claim 5 , wherein the attributes of the new software commit include an attribute indicative of code complexity of the new software commit for which the risk level is determined.

10. The non-transitory computer-readable storage device of claim 5 , wherein the new software commit includes an update to an existing software application.

11. The non-transitory computer-readable storage device of claim 5 , wherein the data structure includes a plurality of entries that store the attributes of the previous software commits and labels indicating successful levels of the previous software commits.

12. A system, comprising:
a data structure to store a plurality of software commits that have already been deployed, each software commit in the data structure to include a plurality of attributes and a label indicating a success level of the software commit;
a processor; and
a memory storing instructions that when executed cause the processor to:
generate a classifier for the plurality of attributes of the software commits from the data structure,
determine an attribute of a new software commit that has not been deployed, and
run the classifier to classify the attribute of the new software commit to determine a risk level for deployment of the new software commit into a production environment to determine whether or not to skip a testing phase,

wherein, to generate the classifier, the instructions are to cause the processor to:
remove one of the previous software commits from the data structure,
calculate the classifier on the previous software commits remaining in the data structure,
run the calculated classifier on the removed software commit, and
compare a risk level label returned by the calculated classifier to an actual risk level label of the removed software commit.

13. The system of claim 12 , wherein the attribute of the new software commit includes a measure of code complexity of the new software commit for which the risk level is determined.

14. The system of claim 12 , wherein to generate the classifier, the instructions are to cause the processor to classify the plurality of attributes of the software commits into three classes: a first class based on a frequency of an update of the software commits, a second class based on successful levels of the software commits, and a third class based on code complexity of the software commits.

Assignees

• Hewlett Packard Entpr Dev Lp
• Entit Software Llc

Inventors

• Zieder Gil
• Kozorovitzky Boris
• Eliassaf Ofer
• Egozi Levi Efrat
• Assulin Ohad

Classifications

• G06F11/004

  Error avoidance (G06F11/07 and subgroups take precedence) · CPC title

• G06F8/65

  Updates (security arrangements therefor G06F21/57) · CPC title

• G06F11/008

  Reliability or availability analysis · CPC title

• G06F11/3604

  Analysis of software for verifying properties of programs (testing of software G06F11/3668) · CPC title

• G06F17/30884

  Physics · mapped topic