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  5. Slot-based Calling Context Encoding
Details

Slot-based Calling Context Encoding

Date Issued
August 11, 2018
Author(s)
Zhou, Tong
Advisor(s)
Michael R. Jantz
Additional Advisor(s)
Micah Beck
James S. Plank
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/41340
Abstract

Calling context is widely used in software engineering areas such as profiling, debugging and event logging. It can also enhance some dynamic analysis such as data race detection. To obtain the calling context at runtime, current approaches either perform expensive stack walking to recover contexts or instrument the application and dynamically encode the context into an integer. The current encoding schemes are either not fully precise, or have high instrumentation and detection overhead, and scalability issue for large and highly recursive applications.We propose slot-based calling context encoding (SCCE), which consists of a scalable encoding for acyclic contexts and an efficient encoding for cyclic contexts. Evaluating with CPU 2006 benchmark suite, we show that our acyclic encoding is scalable, has very low instrumentation overhead, and an acceptable detection overhead. We also show that our cyclic encoding also has lower instrumentation and detection overhead than the state-of-the-art approach by significantly reducing the number of bytes pushed and checked for cyclic contexts.

Subjects

calling context encod...

context sensitivity

program analysis

Degree
Master of Science
Major
Computer Science
File(s)
Thumbnail Image
Name

utkirtd_574.pdf

Size

724.48 KB

Format

Adobe PDF

Checksum (MD5)

01a5180c730c8ecf0a51a8fe15134304

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