Prioritizing Test Cases for Regression Testing of Location-Based Services: Metrics, Techniques, and Case Study
Prioritizing Test Cases for Regression Testing of Location-Based Services: Metrics, Techniques, and Case Study
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DOI：
10.1109/tsc.2012.40
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发表时间：
2014
影响因子：
8.1
通讯作者：
Student Member Ieee Ke Zhai;Member Ieee Bo Jiang;Member Ieee W.K. Chan;B. Jiang
中科院分区：
文献类型：
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作者：
Student Member Ieee Ke Zhai;Member Ieee Bo Jiang;Member Ieee W.K. Chan;B. Jiang
基于位置的服务（LBS）被广泛部署。当启用LBS的服务的实现已经发展时，可以采用回归测试来确保先前建立的行为没有受到不利影响。正确的测试用例优先级有助于有效地揭示服务异常，以便更早地安排修复，从而最大限度地减少对服务使用者的干扰。一个关键的观察结果是，测试用例的输入和预期输出中捕获的位置在物理上与支持LBS的服务相关，并且这些服务启发式地使用估计且不精确的位置进行计算，使得这些服务往往会处理位置非常接近同质。本文利用这一观察。它提出了一套指标，并将其用于演示输入引导技术和兴趣点（POI）感知测试用例优先级排序技术，不同之处在于是否使用测试用例预期输出中的位置信息。它报告了一个有状态LBS启用服务的案例研究。案例研究表明，与随机重新排序测试用例的基线和输入引导技术相比，兴趣点感知技术可以更有效、更稳定。我们还发现，POI感知技术之一，cdist，是最有效的或第二个最有效的技术，在我们评估的方面，所有研究的技术，虽然没有技术优于所有研究的SOA故障类。
Location-based services (LBS) are widely deployed. When the implementation of an LBS-enabled service has evolved, regression testing can be employed to assure the previously established behaviors not having been adversely affected. Proper test case prioritization helps reveal service anomalies efficiently so that fixes can be scheduled earlier to minimize the nuisance to service consumers. A key observation is that locations captured in the inputs and the expected outputs of test cases are physically correlated by the LBS-enabled service, and these services heuristically use estimated and imprecise locations for their computations, making these services tend to treat locations in close proximity homogenously. This paper exploits this observation. It proposes a suite of metrics and initializes them to demonstrate input-guided techniques and point-of-interest (POI) aware test case prioritization techniques, differing by whether the location information in the expected outputs of test cases is used. It reports a case study on a stateful LBS-enabled service. The case study shows that the POI-aware techniques can be more effective and more stable than the baseline, which reorders test cases randomly, and the input-guided techniques. We also find that one of the POI-aware techniques, cdist, is either the most effective or the second most effective technique among all the studied techniques in our evaluated aspects, although no technique excels in all studied SOA fault classes.