By Topic

Recomputing Coverage Information to Assist Regression Testing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chittimalli, P.K. ; Tata Res. Dev. & Design Centre, Pune, India ; Harrold, M.J.

This paper presents a technique that leverages an existing regression test selection algorithm to compute accurate, updated coverage data on a version of the software, Pi+1, without rerunning any test cases that do not execute the changes from the previous version of the software, Pi to Pi+1. The technique also reduces the cost of running those test cases that are selected by the regression test selection algorithm by performing a selective instrumentation that reduces the number of probes required to monitor the coverage data. Users of our technique can avoid the expense of rerunning the entire test suite on Pi+1 or the inaccuracy produced by previous approaches that estimate coverage data for Pi+1 or that reuse outdated coverage data from Pi. This paper also presents a tool, RECOVER, that implements our technique, along with a set of empirical studies on a set of subjects that includes several industrial programs, versions, and test cases. The studies show the inaccuracies that can exist when an application-regression test selection-uses estimated or outdated coverage data. The studies also show that the overhead incurred by selective instrumentation used in our technique is negligible and overall our technique provides savings over earlier techniques.

Published in:

Software Engineering, IEEE Transactions on  (Volume:35 ,  Issue: 4 )