Exploiting function similarity for code size reduction

Koch, Tobias J.K. Edler von; Franke, Björn; Bhandarkar, Pranav; Dasgupta, Anshuman

doi:10.1145/2597809.2597811

Cited by 14 publications

(15 citation statements)

References 23 publications

(1 reference statement)

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“…They can only handle identical functions, allowing only for type mismatches that can be removed by lossless bitcasting of the conflicting values. Similarly, the stateof-the-art [13], while more powerful, cannot merge the two functions either. It requires both functions to have the same list of parameters.…”

Section: Motivationmentioning

confidence: 99%

“…We compare our optimization against the state-of-theart [13] and LLVM's identical [12] function merging techniques. In our evaluation, we refer to the identical function merging as Identical, the state-of-the-art as SOA, and our approach as FMSA.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…The state-of-the-art function-merging technique exploits structural similarity among functions [13]. Their optimization is able to merge similar functions that are not necessarily identical.…”

Section: A Function-merging Techniquesmentioning

confidence: 99%

“…For example, some C++ ABIs may end up creating multiple identical constructors and destructors of a class to use in different contexts [9] and C++ templates replicate code for different specializations [8], [10]. More advanced approaches [13] have extended this idea into merging non-identical functions by leveraging structural similarity. Functions with identical control-flow graphs (CFGs) and only small differences within corresponding basic blocks are merged into a single function that maintains the semantics of the original functions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Function Merging by Sequence Alignment

Rocha¹,

Petoumenos²,

Wang³

et al. 2019

2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

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Resource-constrained devices for embedded systems are becoming increasingly important. In such systems, memory is highly restrictive, making code size in most cases even more important than performance. Compared to more traditional platforms, memory is a larger part of the cost and code occupies much of it. Despite that, compilers make little effort to reduce code size. One key technique attempts to merge the bodies of similar functions. However, production compilers only apply this optimization to identical functions, while research compilers improve on that by merging the few functions with identical control-flow graphs and signatures. Overall, existing solutions are insufficient and we end up having to either increase cost by adding more memory or remove functionality from programs. We introduce a novel technique that can merge arbitrary functions through sequence alignment, a bioinformatics algorithm for identifying regions of similarity between sequences. We combine this technique with an intelligent exploration mechanism to direct the search towards the most promising function pairs. Our approach is more than 2.4x better than the state-of-the-art, reducing code size by up to 25%, with an overall average of 6%, while introducing an average compilation-time overhead of only 15%. When aided by profiling information, this optimization can be deployed without any significant impact on the performance of the generated code.

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Section: Motivationmentioning

confidence: 99%

Section: A Experimental Setupmentioning

confidence: 99%

Section: A Function-merging Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Function Merging by Sequence Alignment

Rocha¹,

Petoumenos²,

Wang³

et al. 2019

2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

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show abstract

“…LLVM lacks a pass to identify identical functions or code fragments, but adding that is one of our goals for the near future. Several previous papers have presented sophisticated program analysis techniques to identify duplicate code fragments within programs at various granularities, ranging from functions down to a variety of small code regions De Sutter et al 2005, 2003Edler von Koch et al 2014;Johnson 2004]. They all focused on individual applications, and we hope to see bigger benefits when applying some subset of those techniques across multiplexed applications and their libraries.…”

Section: Opportunitiesmentioning

confidence: 99%

Software multiplexing: share your libraries and statically link them too

Dietz

Adve

2018

Proc. ACM Program. Lang.

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We describe a compiler strategy we call “ Software Multiplexing ” that achieves many benefits of both statically linked and dynamically linked libraries, and adds some additional advantages. Specifically, it achieves the code size benefits of dynamically linked libraries while eliminating the major disadvantages: unexpected failures due to missing dependences, slow startup times, reduced execution performance due to indirect references to globals, and the potential for security vulnerabilities. We design Software Multiplexing so that it works even in the common case where application build systems support only dynamic and not static linking; we have automatically built thousands of Linux software packages in this way. Software Multiplexing combines two ideas: Automatic Multicall , i.e., where multiple independent programs are automatically merged into a single executable, and Static Linking of Shared Libraries , which works by linking an IR-level version of application code and all its libraries, even if the libraries are normally compiled as shared, before native code generation. The benefits are achieved primarily through deduplication of libraries across the multiplexed programs, while using static linking, and secondly through more effective unused code elimination for statically linked shared libraries. Compared with equivalent dynamically linked programs, <span>allmux-optimized programs start more quickly and even have slightly lower memory usage and total disk size. Compared with equivalent statically linked programs, <span>allmux-optimized programs are much smaller in both aggregate size and memory usage, and have similar startup times and execution performance. We have implemented Software Multiplexing in a tool called <span>allmux, part of the open-source ALLVM project. Example results show that when the LLVM Compiler Infrastructure is optimized using allmux, the resulting binaries and libraries are 18.3% smaller and 30% faster than the default production version. For 74 other packages containing 2–166 programs each, multiplexing each package into one static binary reduces the aggregate package size by 39% (geometric mean) compared with dynamic linking.

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Obfuscated integration of software protections

Broeck

Coppens

Sutter

2020

Int. J. Inf. Secur.

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To counter man-at-the-end attacks such as reverse engineering and tampering, software is often protected with techniques that require support modules to be linked into the application. It is well-known, however, that attackers can exploit the modular nature of applications and their protections to speed up the identification and comprehension process of the relevant code, the assets, and the applied protections. To counter that exploitation of modularity at different levels of granularity, the boundaries between the modules in the program need to be obfuscated. We propose to do so by combining three cross-boundary protection techniques that thwart the disassembly process and in particular the reconstruction of functions: code layout randomization, interprocedurally coupled opaque predicates, and code factoring with intraprocedural control flow idioms. By means of an elaborate experimental evaluation and an extensive sensitivity analysis on realistic use cases and state-of-the-art tools, we demonstrate our technique's potency and resilience to advanced attacks. All relevant code is publicly available online.

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Exploiting function similarity for code size reduction

Cited by 14 publications

References 23 publications

Function Merging by Sequence Alignment

Function Merging by Sequence Alignment

Software multiplexing: share your libraries and statically link them too

Obfuscated integration of software protections

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