Image-based Bug Oracle Automation for Bug Report Reproduction Using Wt Detection
In: 2021 IEEE International Conference on Software Engineering and Artificial Intelligence (SEAI), 2021-06-11
Online
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Zugriff:
Automated bug report reproduction aims at assisting developers in efficiently replicating bugs reported by users on developers’ local machines. This activity involves the automation of reproduction trace generation and target bug verification (i.e. leveraging a bug oracle to check whether the triggered bug is the reported one). Recently, intensive studies have been conducted on automatically translating bug reports into executable reproduction traces. However, existing works all rely on crash stack trace to check if a triggered crash is same with the target crash, thus failing to reproduce a significant number of noncrash bugs. To address this problem, we propose an approach that utilizes an error screenshot in bug report as the bug oracle and applies a novel image comparison algorithm in comparing the oracle image with runtime screenshots. The proposed approach parses the oracle and runtime capture image pair using object detection techniques and then constructs a dummy hierarchy tree for structural difference comparison. In this way, it eliminates non-essential differences caused in most common bug reporting scenarios. We implemented our approach in a tool called SegStec. The empirical study upon 52 image pairs from 52 real-world Android bug reports indicates that SegStec outperforms the state-of-the-art pixel- level image comparison tool with an accuracy of 80.8% in target bug verification.
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Image-based Bug Oracle Automation for Bug Report Reproduction Using Wt Detection
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Autor/in / Beteiligte Person: | Jeong, Hohyeon ; Lee, Eunseok ; Kou, Yanran |
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Zeitschrift: | 2021 IEEE International Conference on Software Engineering and Artificial Intelligence (SEAI), 2021-06-11 |
Veröffentlichung: | IEEE, 2021 |
Medientyp: | unknown |
DOI: | 10.1109/seai52285.2021.9477528 |
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