Title:
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Learning Effective Oracle Comparator Combinations for Web Applications
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Authors:
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Sara Sprenkle, Emily Hill, and Lori Pollock
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Abstract:
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Web application testers need automated, effective approaches to validate the test results of complex, evolving web applications. In previous work, we developed a suite of automated oracle comparators that focus on specific characteristics of a web application's HTML response. We found that oracle comparators' effectiveness depends on
the application's behavior. We also found that by combining the results of two oracle comparators, we could achieve better effectiveness than using a single oracle comparator alone. However, selecting the most effective oracle combination from the large suite of comparators is difficult. In this paper, we propose applying decision tree learning to identify the best combination of oracle comparators, based on the tester's effectiveness goals. Using decision tree learning, we train separately on four web applications and identify the most effective oracle comparator for each application. We evaluate the learned comparators' effectiveness in a case study and propose a process for testers to apply our learning approach in practice.
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Publisher:
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IEEE
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Book Title:
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First International Workshop on Software Test Evaluation (STEV 2007) co-located with the Seventh International Conference on Quality Software (QSIC)
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Pages:
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372--379
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Date:
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October 2007
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Project:
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Web Application Testing
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Document Type:
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Conference Proceedings
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Key Words:
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oracles, web applications
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Files:
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[preprint: Adobe PDF] (134 KB)
[slides: Adobe PDF] (506 KB)
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Bibtex Entry:
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| @inproceedings{123456789/177, |
| author = {Sara Sprenkle and Emily Hill and Lori Pollock}, |
| title = {Learning Effective Oracle Comparator Combinations for Web Applications}, |
| booktitle = {First International Workshop on Software Test Evaluation (STEV 2007) co-located with the Seventh International Conference on Quality Software (QSIC)}, |
| pages = {372--379}, |
| publisher = {IEEE}, |
| month = {October}, |
| year = {2007} |
| } |
|