TRIMMER: Context-Specific Code Reduction

被引:1
|
作者
Ahmad, Aatira Anum [1 ]
Anwar, Mubashir [2 ]
Sharif, Hashim [2 ]
Gehani, Ashish [3 ]
Zaffar, Fareed [1 ]
机构
[1] LUMS, Lahore, Pakistan
[2] Univ Illinois, Champaign, IL USA
[3] SRI Int, Menlo Pk, CA USA
基金
美国国家科学基金会;
关键词
Static analysis; Code debloating; Program specialization; LLVM;
D O I
10.1145/3551349.3559529
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present Trimmer, a state-of-the-art tool for reducing code size. Trimmer reduces code sizes by specializing programs with respect to constant inputs provided by developers. The static data can be provided as command-line options or through configuration files. The constants define the features that must be retained, which in turn determine the features that are unused in a specific deployment (and can therefore be removed). Trimmer includes sophisticated compiler transformations for input specialization, supports precise yet efficient context-sensitive inter-procedural constant propagation, and introduces a custom loop unroller. Trimmer is easy-touse and extensively parameterized. We discuss how Trimmer can be configured by developers to explicitly trade analysis precision and specialization time. We also provide a high-level description of Trimmer's static analysis passes. The source code is publicly available at: https://github.com/ashish-gehani/Trimmer. A video demonstration can be found here: https://youtu.be/6pAuJ68INnI.
引用
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页数:5
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