@techreport{TD:100215,
	att_abstract={{Does the use of fault prediction models to help focus software testing 
resources and other development efforts to improve software reliability
lead to discovery of different faults in the next release, or simply an improved
process for finding the same faults that would be found if the models
were not used? 
In this short paper, we describe the challenges involved in estimating
effects for this sort of intervention and discuss ways to empirically
answer that question and ways to assess any changes, if present.
We present several experimental design options
and discuss the pros and cons of each.}},
	att_authors={ew1564, to2675, rb2582},
	att_categories={},
	att_copyright={{IEEE}},
	att_copyright_notice={{This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in Testing: Academic & Industrial Conference (TAIC 2011) {{, 2011-03-25}} }},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={experimental design,  estimating causal effects,  software faults,  software testing,  industrial systems},
	att_techdoc={true},
	att_techdoc_key={TD:100215},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100215_DS1_2010-10-06T17:49:45.593Z.pdf},
	author={Elaine Weyuker and Thomas Ostrand and Robert Bell},
	institution={{Testing: Academic & Industrial Conference (TAIC 2011)}},
	month={March},
	title={{Assessing the Impact of Using Fault-Prediction in Industry}},
	year=2011,
}