41,861 research outputs found
Dynamic assertion testing of flight control software
An experiment in using assertions to dynamically test fault tolerant flight software is described. The experiment showed that 87% of typical errors introduced into the program would be detected by assertions. Detailed analysis of the test data showed that the number of assertions needed to detect those errors could be reduced to a minimal set. The analysis also revealed that the most effective assertions tested program parameters that provided greater indirect (collateral) testing of other parameters
Dynamic assertion testing of flight control software
Digital Flight Control System (DFCS) software was used as a test case for assertion testing. The assertions were written and embedded in the code, then errors were inserted (seeded) one at a time and the code executed. Results indicate that assertion testing is an effective and efficient method of detecting errors in flight software. Most errors are eliminate at an earlier stage in the development than before
Development of a flight software testing methodology
The research to develop a testing methodology for flight software is described. An experiment was conducted in using assertions to dynamically test digital flight control software. The experiment showed that 87% of typical errors introduced into the program would be detected by assertions. Detailed analysis of the test data showed that the number of assertions needed to detect those errors could be reduced to a minimal set. The analysis also revealed that the most effective assertions tested program parameters that provided greater indirect (collateral) testing of other parameters. In addition, a prototype watchdog task system was built to evaluate the effectiveness of executing assertions in parallel by using the multitasking features of Ada
A methodology for testing fault-tolerant software
A methodology for testing fault tolerant software is presented. There are problems associated with testing fault tolerant software because many errors are masked or corrected by voters, limiter, or automatic channel synchronization. This methodology illustrates how the same strategies used for testing fault tolerant hardware can be applied to testing fault tolerant software. For example, one strategy used in testing fault tolerant hardware is to disable the redundancy during testing. A similar testing strategy is proposed for software, namely, to move the major emphasis on testing earlier in the development cycle (before the redundancy is in place) thus reducing the possibility that undetected errors will be masked when limiters and voters are added
Automatically Discovering, Reporting and Reproducing Android Application Crashes
Mobile developers face unique challenges when detecting and reporting crashes
in apps due to their prevailing GUI event-driven nature and additional sources
of inputs (e.g., sensor readings). To support developers in these tasks, we
introduce a novel, automated approach called CRASHSCOPE. This tool explores a
given Android app using systematic input generation, according to several
strategies informed by static and dynamic analyses, with the intrinsic goal of
triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented
crash report containing screenshots, detailed crash reproduction steps, the
captured exception stack trace, and a fully replayable script that
automatically reproduces the crash on a target device(s). We evaluated
CRASHSCOPE's effectiveness in discovering crashes as compared to five
state-of-the-art Android input generation tools on 61 applications. The results
demonstrate that CRASHSCOPE performs about as well as current tools for
detecting crashes and provides more detailed fault information. Additionally,
in a study analyzing eight real-world Android app crashes, we found that
CRASHSCOPE's reports are easily readable and allow for reliable reproduction of
crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on
Software Testing, Verification and Validation (ICST'16), Chicago, IL, April
10-15, 2016, pp. 33-4
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