Eliminating exception handling errors with dependability cases: acomparative, empirical study
Maxion, R.A.
Olszewski, R.T.
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA;
This paper appears in: Software Engineering, IEEE Transactions on
Publication Date: Sep 2000
Volume: 26,
Issue: 9
On page(s): 888-906
ISSN: 0098-5589
References Cited: 43
CODEN: IESEDJ
INSPEC Accession Number: 6738653
Digital Object Identifier: 10.1109/32.877848
Current Version Published: 2002-08-06
Abstract
Programs fail mainly for two reasons: logic errors in the code and
exception failures. Exception failures can account for up to two-thirds
of system crashes, hence, are worthy of serious attention. Traditional
approaches to reducing exception failures, such as code reviews,
walkthroughs, and formal testing, while very useful, are limited in
their ability to address a core problem: the programmer's inadequate
coverage of exceptional conditions. The problem of coverage might be
rooted in cognitive factors that impede the mental generation (or
recollection) of exception cases that would pertain in a particular
situation, resulting in insufficient software robustness. This paper
describes controlled experiments for testing the hypothesis that
robustness for exception failures can be improved through the use of
various coverage-enhancing techniques: N-version programming, group
collaboration, and dependability cases. N-version programming and
collaboration are well known. Dependability cases, derived from safety
cases, comprise a new methodology based on structured taxonomies and
memory aids for helping software designers think about and improve
exception handling coverage. All three methods showed improvements over
control conditions in increasing robustness to exception failures but
dependability cases proved most efficacious in terms of balancing cost
and effectiveness
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