Architecture-Agnostic Dynamic Type Recovery

Daniel Pekarek; Hanspeter Mössenböck

doi:10.1145/3475738.3480719

Architecture-Agnostic Dynamic Type Recovery

Daniel Pekarek
, Hanspeter Mössenböck

Institute for Systems Software

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

Programmers can use various data types when developing software. However, if the program is compiled to machine code, most of this type information is lost. If analysis of a compiled program is necessary, the lost data types have to be recovered again, to make the code understandable. Existing approaches for the type recovery problem require detailed knowledge about the CPU architecture in question. An architecture-agnostic approach is missing so far. This work focuses on a truly architecture-agnostic type recovery algorithm, implemented in a dynamic analysis system. It can recover data types using minimal knowledge about the CPU architecture, therefore, making it easy to support many different CPU architectures in the analysis system.

Original language	English
Title of host publication	MPLR 2021: Proceedings of the 18th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes
Editors	Herbert Kuchen, Singer Jeremy
Publisher	ACM Digital
Pages	54-60
Number of pages	7
ISBN (Electronic)	9781450386753
DOIs	https://doi.org/10.1145/3475738.3480719
Publication status	Published - 29 Sept 2021

Fields of science

102 Computer Sciences
102009 Computer simulation
102011 Formal languages
102013 Human-computer interaction
102022 Software development
102024 Usability research
102029 Practical computer science

JKU Focus areas

Digital Transformation

Access to Document

10.1145/3475738.3480719

Cite this

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title = "Architecture-Agnostic Dynamic Type Recovery",

abstract = "Programmers can use various data types when developing software. However, if the program is compiled to machine code, most of this type information is lost. If analysis of a compiled program is necessary, the lost data types have to be recovered again, to make the code understandable. Existing approaches for the type recovery problem require detailed knowledge about the CPU architecture in question. An architecture-agnostic approach is missing so far. This work focuses on a truly architecture-agnostic type recovery algorithm, implemented in a dynamic analysis system. It can recover data types using minimal knowledge about the CPU architecture, therefore, making it easy to support many different CPU architectures in the analysis system.",

author = "Daniel Pekarek and Hanspeter M{\"o}ssenb{\"o}ck",

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language = "English",

pages = "54--60",

editor = "Herbert Kuchen and Singer Jeremy",

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Architecture-Agnostic Dynamic Type Recovery. / Pekarek, Daniel; Mössenböck, Hanspeter.
MPLR 2021: Proceedings of the 18th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes. ed. / Herbert Kuchen; Singer Jeremy. ACM Digital, 2021. p. 54-60.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

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AU - Mössenböck, Hanspeter

PY - 2021/9/29

Y1 - 2021/9/29

N2 - Programmers can use various data types when developing software. However, if the program is compiled to machine code, most of this type information is lost. If analysis of a compiled program is necessary, the lost data types have to be recovered again, to make the code understandable. Existing approaches for the type recovery problem require detailed knowledge about the CPU architecture in question. An architecture-agnostic approach is missing so far. This work focuses on a truly architecture-agnostic type recovery algorithm, implemented in a dynamic analysis system. It can recover data types using minimal knowledge about the CPU architecture, therefore, making it easy to support many different CPU architectures in the analysis system.

AB - Programmers can use various data types when developing software. However, if the program is compiled to machine code, most of this type information is lost. If analysis of a compiled program is necessary, the lost data types have to be recovered again, to make the code understandable. Existing approaches for the type recovery problem require detailed knowledge about the CPU architecture in question. An architecture-agnostic approach is missing so far. This work focuses on a truly architecture-agnostic type recovery algorithm, implemented in a dynamic analysis system. It can recover data types using minimal knowledge about the CPU architecture, therefore, making it easy to support many different CPU architectures in the analysis system.

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U2 - 10.1145/3475738.3480719

DO - 10.1145/3475738.3480719

M3 - Conference proceedings

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BT - MPLR 2021: Proceedings of the 18th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes

A2 - Kuchen, Herbert

A2 - Jeremy, Singer

PB - ACM Digital

ER -

Architecture-Agnostic Dynamic Type Recovery

Abstract

Fields of science

JKU Focus areas

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