8,733 research outputs found
A methodology for the generation of efficient error detection mechanisms
A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their efficiency typically being measured using fault injection and metrics such as coverage and latency. In this paper, we introduce a methodology for the design of highly efficient error detection mechanisms. The proposed methodology combines fault injection analysis and data mining techniques in order to generate predicates for efficient error detection mechanisms. The results presented demonstrate the viability of the methodology as an approach for the development of efficient error detection mechanisms, as the predicates generated yield a true positive rate of almost 100% and a false positive rate very close to 0% for the detection of failure-inducing states. The main advantage of the proposed methodology over current state-of-the-art approaches is that efficient detectors are obtained by design, rather than by using specification-based detector design or the experience of software engineers
A Survey of Symbolic Execution Techniques
Many security and software testing applications require checking whether
certain properties of a program hold for any possible usage scenario. For
instance, a tool for identifying software vulnerabilities may need to rule out
the existence of any backdoor to bypass a program's authentication. One
approach would be to test the program using different, possibly random inputs.
As the backdoor may only be hit for very specific program workloads, automated
exploration of the space of possible inputs is of the essence. Symbolic
execution provides an elegant solution to the problem, by systematically
exploring many possible execution paths at the same time without necessarily
requiring concrete inputs. Rather than taking on fully specified input values,
the technique abstractly represents them as symbols, resorting to constraint
solvers to construct actual instances that would cause property violations.
Symbolic execution has been incubated in dozens of tools developed over the
last four decades, leading to major practical breakthroughs in a number of
prominent software reliability applications. The goal of this survey is to
provide an overview of the main ideas, challenges, and solutions developed in
the area, distilling them for a broad audience.
The present survey has been accepted for publication at ACM Computing
Surveys. If you are considering citing this survey, we would appreciate if you
could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing
this survey, we would appreciate if you could use the following BibTeX entry:
http://goo.gl/Hf5Fv
Debugging Memory Issues In Embedded Linux: A Case Study
Debugging denotes the process of detecting root causes of unexpected
observable behaviors in programs, such as a program crash, an unexpected output
value being produced or an assertion violation. Debugging of program errors is
a difficult task and often takes a significant amount of time in the software
development life cycle. In the context of embedded software, the probability of
bugs is quite high. Due to requirements of low code size and less resource
consumption, embedded softwares typically do away with a lot of sanity checks
during development time. This leads to high chance of errors being uncovered in
the production code at run time. In this paper we propose a methodology for
debugging errors in BusyBox, a de-facto standard for Linux in embedded systems.
Our methodology works on top of Valgrind, a popular memory error detector and
Daikon, an invariant analyzer. We have experimented with two published errors
in BusyBox and report our findings in this paper.Comment: In proceedings of IEEE TechSym 2011, 14-16 January, 2011, IIT
kharagpur, Indi
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