System and method for identifying and comparing code by semantic abstractions
Abstract
Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.
- Inventors:
- Issue Date:
- Research Org.:
- Univ. of Louisiana, Lafayette, LA (United States)
- Sponsoring Org.:
- USDOE; Defense Advanced Research Projects Agency (DARPA); US Air Force Office of Scientific Research (AFOSR)
- OSTI Identifier:
- 1986743
- Patent Number(s):
- 11481494
- Application Number:
- 16/922,293
- Assignee:
- University of Louisiana at Lafayette (Lafayette, LA)
- DOE Contract Number:
- FA8750-10-C-0171; FA8750-12-C-0144; FA9550-09-1-0715
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 07/07/2020
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Lakhotia, Arun. System and method for identifying and comparing code by semantic abstractions. United States: N. p., 2022.
Web.
Lakhotia, Arun. System and method for identifying and comparing code by semantic abstractions. United States.
Lakhotia, Arun. Tue .
"System and method for identifying and comparing code by semantic abstractions". United States. https://www.osti.gov/servlets/purl/1986743.
@article{osti_1986743,
title = {System and method for identifying and comparing code by semantic abstractions},
author = {Lakhotia, Arun},
abstractNote = {Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {10}
}
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