- author = "Eric Schulte and Zachary P. Fry and Ethan Fast and Stephanie Forrest and Westley Weimer",
- title = "Software Mutational Robustness: Bridging The Gap Between Mutation Testing and Evolutionary Biology",
- howpublished = "arXiv",
- year = "2012",
- month = "18 " # apr,
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, mutational robustness, proactive diversity, mutation testing, equivalent mutant, reliability, CIL, intel 64bit x86 assembler",
-
URL = "
http://arxiv.org/abs/1204.4224",
- size = "11 pages",
-
abstract = "In the mutation testing paradigm, test suite quality
is measured by its ability to detect (or kill) variant
programs generated through application of random
changes to an original program. The ideal test suite is
sensitive to any semantic change. In evolutionary
biology, however, neutral mutations that leave fitness
unchanged are considered to be beneficial improving the
system's robustness and its ability to discover
evolutionary improvements. In this paper, we generate a
population of variant programs, created from an
original program by applying lightweight random
mutations. We adopt biological terminology and refer to
unkilled variants as neutral, and the percentage of all
variants that are neutral is defined as the program's
mutational robustness. Although they are related to
equivalent mutants in mutation testing, which are
viewed as problematic, we demonstrate positive
properties of neutral variants which easily generated
and can be leveraged to protect software against
unknown defects.
Even when the mutations are restricted to statements executed by the test cases, we find that mutational robustness is surprisingly high: 36.75percent on a corpus of 22 programs including production software projects, the Siemens benchmark suite, and a few specially constructed programs. The results hold for mutations at both the source code and assembly instruction levels, across various programming languages, and are not fully explained by test suite quality. We conclude that mutational robustness is an inherent property of software, existing even when a program is correct according to its specification. Rather than an overhead cost or indicator of test suite inadequacy, it is an opportunity to create useful proactive diversity because neutral mutations often cause nontrivial algorithmic changes. To demonstrate this, we generate and select diverse populations of neutral program variants. For a program with seven or more held-out latent bugs, we can, on average, construct and select seven neutral variants such that at least one fixes a latent bug.",
-
notes = "
Early draft of \cite{Schulte:2014:GPEM}",
- bibsource = "DBLP, http://dblp.uni-trier.de",
