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Precise Calling Context Encoding

delete2012-09-01
delete18
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OA
AI
W
William N. Sumner *
Y
Yunhui Zheng
D
Dasarath Weeratunge
X
Xiangyu Zhang
DOI:10.1109/TSE.2011.70delete
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摘要

摘要

En 中文
Calling contexts (CCs) are very important for a wide range of applications such as profiling, debugging, and event logging. Most applications perform expensive stack walking to recover contexts. The resulting contexts are often explicitly represented as a sequence of call sites and hence are bulky. We propose a technique to encode the current calling context of any point during an execution. In particular, an acyclic call path is encoded into one number through only integer additions. Recursive call paths are divided into acyclic subsequences and encoded independently. We leverage stack depth in a safe way to optimize encoding: If a calling context can be safely and uniquely identified by its stack depth, we do not perform encoding. We propose an algorithm to seamlessly fuse encoding and stack depth-based identification. The algorithm is safe because different contexts are guaranteed to have different IDs. It also ensures contexts can be faithfully decoded. Our experiments show that our technique incurs negligible overhead (0-6.4 percent). For most medium-sized programs, it can encode all contexts with just one number. For large programs, we are able to encode most calling contexts to a few numbers. We also present our experience of applying context encoding to debugging crash-based failures.
Keyword:
Calling context
context sensitivity
profiling
path encoding
calling context encoding
call graph
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期刊

IEEE Transactions on Software Engineering 封面图
IEEE Transactions on Software Engineering
IF:
5.6
论文数:
2.9K
被引数:
1.1W

机构

Purdue University System 封面图
Purdue University System
学者数:
3.9W
论文数: 3.6W
被引数: 66
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