Encoding Optimal Customized Coverage Instrumentation
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Date
2016-08-26Author
Ohmann, Peter
Brown, David Bingham
Neelakandan, Naveen
Linderoth, Jeff
Liblit, Ben
Metadata
Show full item recordAbstract
Program coverage is an important software quality metric. Coverage is most
commonly gathered in the testing lab during development. However, developers
also sometimes use inexpensive forms of program coverage in production software.
In the post-deployment scenario, users often place very strict requirements on
tracing overheads and legal instrumentation strategies. This work deals
specifically with optimizing program coverage instrumentation strategies given
instrumentation requirements and limitations.
The problem of optimal customized coverage instrumentation is known to be
NP-hard, so a polynomial-time solver is unlikely to exist. This particular
report presents a fully-optimal approach to solving the problem of customized
program coverage instrumentation optimization. We encode our solution as a
mixed-integer linear optimization problem. We build up a mathematical model
of the constraints required to satisfy required coverage instrumentation
criteria, and present a complete model for solving the customized coverage
instrumentation problem.
Subject
debugging
program coverage
mixed integer linear optimization