System and method for end to end performance response time measurement based on graphic recognition
Software testing techniques based on image recognition are disclosed. In various embodiments, a programmatically implemented image classifier is trained to recognize a screen shot image as being associated with a transaction end condition of a transaction. A test script configured to initiate an iteration of the transaction is run. A start time of the iteration of the transaction is recorded. Screen shot images are generated during performance of the iteration of the transaction to capture a series of screen shot images of at least a portion of a user interface display associated with the iteration of the transaction. The image classifier is used to find an earliest-captured image that matches the transaction end condition. A time associated with the matched image is used as a transaction end time to compute an end-to-end time to perform the iteration of the transaction.
1. A software testing method, comprising:
training a programmatically implemented image classifier to recognize a screen shot image as being associated with a transaction end condition of a transaction;
running a test script configured to initiate an iteration of the transaction;
recording a start time of the iteration of the transaction;
causing screen shot images to be generated during performance of the iteration of the transaction to capture a series of screen shot images of at least a portion of a user interface display associated with the iteration of the transaction;
using the image classifier to find an earliest-captured image that matches the transaction end condition; and
using a time associated with the matched image as a transaction end time to compute an end-to-end time to perform the iteration of the transaction.
2. The method of claim 1 , wherein the image classifier comprises a Haar image classifier.
3. The method of claim 1 , wherein the image classifier comprises an OpenCV image classifier.
4. The method of claim 1 , wherein training the image classifier includes initiating an iteration of the transaction and capturing a screen shot of a result end of transaction display.
5. The method of claim 1 , wherein screen shots comprising the series of screen shot images are captured at a fixed interval.
6. The method of claim 1 , wherein the time associated with the matched image comprises a timestamp.
7. The method of claim 6 , wherein the timestamp comprises a timestamp associated with an image file with which the matched image is associated.
8. The method of claim 1 , wherein the end-to-end time is computed by subtracting the start time of the iteration of the transaction from the time associated with the matched image.
9. The method of claim 1 , wherein the image classifier is trained to recognize a characteristic element comprising an end of transaction display page.
10. The method of claim 1 , further comprising providing the computed end-to-end time as a test result associated with the transaction.
11. The method of claim 1 , further comprising providing the computed end-to-end time as a test result associated with the transaction.
12. A software testing system, comprising:
a memory; and
a processor coupled to the memory and configured to:
train a programmatically implemented image classifier to recognize a screen shot image as being associated with a transaction end condition of a transaction;
run a test script configured to initiate an iteration of the transaction;
record a start time of the iteration of the transaction;
cause screen shot images to be generated and stored in the memory during performance of the iteration of the transaction to capture a series of screen shot images of at least a portion of a user interface display associated with the iteration of the transaction;
use the image classifier to find an earliest-captured image that matches the transaction end condition; and
use a time associated with the matched image as a transaction end time to compute an end-to-end time to perform the iteration of the transaction.
13. The system of claim 12 , wherein the image classifier comprises a Haar image classifier.
14. The system of claim 12 , wherein training the image classifier includes initiating an iteration of the transaction and capturing a screen shot of a result end of transaction display.
15. The system of claim 12 , wherein screen shots comprising the series of screen shot images are captured at a fixed interval.
16. The system of claim 12 , wherein the time associated with the matched image comprises a timestamp.
17. The system of claim 12 , wherein the image classifier is trained to recognize a characteristic element comprising an end of transaction display page.
18. A computer program product to perform software testing, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
training a programmatically implemented image classifier to recognize a screen shot image as being associated with a transaction end condition of a transaction;
running a test script configured to initiate an iteration of the transaction;
recording a start time of the iteration of the transaction;
causing screen shot images to be generated during performance of the iteration of the transaction to capture a series of screen shot images of at least a portion of a user interface display associated with the iteration of the transaction;
using the image classifier to find an earliest-captured image that matches the transaction end condition; and
using a time associated with the matched image as a transaction end time to compute an end-to-end time to perform the iteration of the transaction.
19. The computer program product of claim 18 , wherein screen shots comprising the series of screen shot images are captured at a fixed interval.
20. The computer program product of claim 18 , wherein the image classifier is trained to recognize a characteristic element comprising an end of transaction display page.