NDLI: Geographical Test Data Generation by Simulated-Annealing

Content Provider	IEEE Xplore Digital Library
Author	Kejia Hou Jun Huang Xiaoying Bai
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China (Kejia Hou; Jun Huang; Xiaoying Bai)
Abstract	Location-based services (LBS) have been widely used in many applications like navigation and recommendation, especially for mobile systems. Testing of LBS services is hard due to the difficulties to cover location areas and to evaluate the correctness of location information for LBS query with a given address. To cope with the difficulties, the paper proposed a testing framework to search geographical test data using simulated-annealing algorithm, and to validate the query results by comparing across different LBS platforms. The heuristic search is based on defect clustering assumption. That is, defects intend to cluster in certain areas. Hence, areas with detected defects deserve more test cases in the follow-up testing. A Bayes classifier is used to predict defect probability of geographical areas, and to guide position data generation in the annealing algorithm. Experiments on real LBS platforms showed that with acceptable cost, the proposed method can considerably enhance test effectiveness.
Starting Page	472
Ending Page	477
File Size	239362
Page Count	6
File Format	PDF
ISSN	07303157
e-ISBN	9781467365642
DOI	10.1109/COMPSAC.2015.258
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Testing Optimization Androids Humanoid robots Cooling Search problems Temperature Simulated-Annealing Test Data Generation Location-Based Services
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Software

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