Browsing by Author "Hung, Jui-Tsun"

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In-Lab Replay Testing under Real Traffic with a Case Study on WLAN Routers
(2017-03-01)
Lin, Ying-Dar
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Hwang, Ren-Hung
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Lu, Chun-Nan
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Hung, Jui-Tsun
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資訊工程學系
Replaying artificial or real-world traffic is a method used to test networking devices. Using real-world traffic is desirable as it uncovers more realistic properties such as traffic diversity and complicated user behaviors. In this paper, we propose an in-lab replay testing (ILRT) framework, composed of a monitor, a traffic replayer and a library of real-world traffic traces, to replay captured packet traces to test networking devices. To demonstrate its effectiveness, a total of 28 WLAN routers were tested to evaluate whether they could work stably for an extended time. In our experiments, 53.57% and 100% of devices under test (DUTs) were triggered critical (L1) failures and tolerable (L2) failures, respectively. 21.43% and 100% of DUTs were triggered more than one L 1 and L2 failures, respectively. Among high-spec DUTs, there was 25% of DUTs which were triggered L1 failures. Furthermore, among 458 test results, chance of pass, L1 failure, and L2 failure is 2.84%, 7.86%, and 89.3%, respectively. The results showed that even though these devices have passed traditional lab tests, there is still a good chance for them to fail under real-world traffic.
Test coverage optimization for large code problems
(2012-01-01)
Lin, Ying-Dar
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Chou, Chi-Heng
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Lai, Yuan-Cheng
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Huang, Tse-Yau
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Chung, Simon
Software developers frequently conduct regression testing on a series of major, minor, or bug-fix software or firmware releases. However, retesting all test cases for each release is time-consuming. For example, it takes about 36 test-bed-days to thoroughly exercise a test suite made up of 2320 test cases for the MPLS testing area that contains 57,758 functions in Cisco IOS. The cost is infeasible for a series of regression testing on the MPLS area. Thus, the test suite needs to be reduced intelligently, not just randomly, and its fault detection capability must be kept as much as possible. The mode of safe regression test selection approach is adopted for seeking a subset of modification-traversing test cases to substitute for fault-revealing test cases. The algorithms, CW-NumMin, CW-CostMin, and CW-CostCov-B, apply the safe-mode approach in selecting test cases for achieving full-modified function coverage. It is assumed that modified functions are fault-prone, and the fault distribution of the testing area is Pareto-like. Moreover, we also assume that once a subject program is getting more mature, its fault concentration will become stronger. Only function coverage criterion is adopted because of the scalability of a software system with large code. The metrics of test's junction reachability and function's test intensity are defined in this study for algorithms. Both CW-CovMax and CW-CostMin algorithms are not safe-mode, but the approaches they use still attempt to obtain a test suite with a maximal amount of function coverage under certain constraints, i.e. the effective-confidence level and time restriction. We conclude that the most effective algorithm in this study can significantly reduce the cost (time) of regression testing on the MPLS testing area to 1.10%, on the average. Approaches proposed here can be effectively and efficiently applied to the regression testing on bug-fix releases of a software system with large code, especially to the releases having very few modified functions with low test intensities. (C) 2011 Elsevier Inc. All rights reserved.
Traffic diversity and code coverage: a preliminary analysis
(2016-02-01)
Lin, Ying-Dar
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Lai, Yuan-Cheng
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Lu, Chun-Nan
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Hung, Jui-Tsun
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Shao, Chun-Pin
It is generally assumed that using more diverse traffic to test network devices could achieve larger code coverage. However, how to describe the diversity of traffic traces and the relationship between the traffic diversity and code coverage is still an issue. In this paper, the traffic diversity is defined using the number of packets and the size of the subnets involved, and traces having various diversity are used to evaluate the corresponding code coverage for the programs in a network device. Experiment results show that more number of packets or larger size of network segments can generate larger diversity indices and thus larger code coverage. For Snort, as the number of packets increases from 1 to 10,000,000, representative diversity index and the code coverage can increase from 0 to 0.95 on the basis of Simpson\'s index and from 19.1% to 32.2%, respectively. As the size of network segments increases, representative diversity index and the code coverage can increase from 0.41 to 0.82 and from 28.2% to 32.2%, respectively. Similar results can be obtained in the case of Linux kernel. If the mappings among different diversity indices and the corresponding code coverage can be built beforehand, the quality of the tests can improved. Copyright (c) 2014 John Wiley & Sons, Ltd.