Bruno De Bus

Link-time binary rewriting techniques for program compaction

Small program size is an important requirement for embedded systems with limited amounts of memory. We describe how link-time compaction through binary rewriting can achieve code size reductions of up to 62&percent; for statically bound languages such as C, C++, and Fortran, without compromising on performance. We demonstrate how the limited amount of information about a program at link time can be exploited to overcome overhead resulting from separate compilation. This is done with scalable, cost-effective, whole-program analyses, optimizations, and duplicate code and data elimination techniques. The discussed techniques are evaluated and their cost-effectiveness is quantified with Squeeze++, a prototype link-time compactor.

Program obfuscation: a quantitative approach

Despite the recent advances in the theory underlying obfuscation, there still is a need to evaluate the quality of practical obfuscating transformations more quickly and easily. This paper presents the first steps toward a comprehensive evaluation suite consisting of a number of deobfuscating transformations and complexity metrics that can be readily applied on existing and future transformations in the domain of binary obfuscation. In particular, a framework based on software complexity metrics measuring four program properties: code, control flow, data and data flow is suggested. A number of well-known obfuscating and deobfuscating transformations are evaluated based upon their impact on a set of complexity metrics. This enables us to quantitatively evaluate the potency of the (de)obfuscating transformations.

Link-time optimization of ARM binaries

The overhead in terms of code size, power consumption and execution time caused by the use of precompiled libraries and separate compilation is often unacceptable in the embedded world, where real-time constraints, battery life-time and production costs are of critical importance. In this paper we present our link-time optimizer for the ARM architecture. We discuss how we can deal with the peculiarities of the ARM architecture related to its visible program counter and how the introduced overhead can be eliminated to a large extent. Our link-time optimizer is evaluated in two tool chains. In the Arm Developer Suite tool chain, average code size reductions with 14.6% are achieved, while execution time is reduced with 8.3% on average, and energy consumption with 7.3%. On binaries from the GCC tool chain the average code size reduction is 16.6%, execution time is reduced with 12.3% and the energy consumption with 11.5% on average. Finally, we show how the incorporation of link-time optimization in tool chains may influence library interface design.

Sifting out the mud: low level C++ code reuse

More and more computers are being incorporated in devices where the available amount of memory is limited. This contrasts with the increasing need for additional functionality and the need for rapid application development. While object-oriented programming languages, providing mechanisms such as inheritance and templates, allow fast development of complex applications, they have a detrimental effect on program size. This paper introduces new techniques to reuse the code of whole procedures at the binary level and a supporting technique for data reuse. These techniques benefit specifically from program properties originating from the use of templates and inheritance. Together with our previous work on code abstraction at lower levels of granularity, they achieve additional code size reductions of up to 38% on already highly optimized and compacted binaries, without sacrificing execution speed. We have incorporated these techniques in Squeeze++, a prototype link-time binary rewriter for the Alpha architecture, and extensively evaluate them on a suite of 8 real-life C++ applications. The total code size reductions achieved post link-time (i.e. without requiring any change to the compiler) range from 27 to 70%, averaging at around 43%.

Post-pass compaction techniques

Seeking to resolve many of the problems related to code size in traditional program development environments.

System-wide compaction and specialization of the linux kernel

The limited built-in configurability of Linux can lead to expensive code size overhead when it is used in the embedded market. To overcome this problem, we propose the application of link-time compaction and specialization techniques that exploit the a priori known, fixed run-time environment of many embedded systems. In experimental setups based on the ARM XScale and i386 platforms, the proposed techniques are able to reduce the kernel memory footprint with over 16%. We also show how relatively simple additions to existing binary rewriters can implement the proposed techniques for a complex, very unconventional program such as the Linux kernel. Finally, we pinpoint an important code size growth problem when compaction and compression techniques are combined on the ARM platform.

Link-time compaction and optimization of ARM executables

The overhead in terms of code size, power consumption, and execution time caused by the use of precompiled libraries and separate compilation is often unacceptable in the embedded world, where real-time constraints, battery life-time, and production costs are of critical importance. In this paper, we present our link-time optimizer for the ARM architecture. We discuss how we can deal with the peculiarities of the ARM architecture related to its visible program counter and how the introduced overhead can to a large extent be eliminated. Our link-time optimizer is evaluated with four tool chains, two proprietary ones from ARM and two open ones based on GNU GCC. When used with proprietary tool chains from ARM Ltd., our link-time optimizer achieved average code size reductions of 16.0 and 18.5%, while the programs have become 12.8 and 12.3% faster, and 10.7 to 10.1% more energy efficient. Finally, we show how the incorporation of link-time optimization in tool chains may influence library interface design.

Combining Global Code and Data Compaction

Computers are increasingly being incorporated in devices with a limited amount of available memory. As a result research is increasingly focusing on the automated reduction of program size. Existing literature focuses on either data or code compaction or on highly language dependent techniques. This paper shows how combined code and data compaction can be achieved using a link-time code compaction system that reasons about the use of both code and data addresses. The analyses proposed rely only on fundamental properties of linked code and are therefore generally applicable. The combined code and data compaction is implemented in SQUEEZE, a link-time program compaction system, and evaluated on SPEC2000, MediaBench and C++ programs, resulting in total binary program size reductions of 23.6%-46.6%. This compaction involves no speed trade-off, as the compacted programs are on average about 8% faster.

The design and implementation of FIT: a flexible instrumentation toolkit

This paper presents FIT, a Flexible open-source binary code Instrumentation Toolkit. Unlike existing tools, FIT is truly portable, with existing backends for the Alpha, x86 and ARM architectures and the Tru64Unix, Linux and ARM Firmware execution environments. This paper focuses on some of the problems that needed to be addressed for providing this degree of portability. It also discusses the trade-off between instrumentation precision and low overhead.

Automated reduction of the memory footprint of the Linux kernel

The limited built-in configurability of Linux can lead to expensive code size overhead when it is used in the embedded market. To overcome this problem, we propose the application of link-time compaction and specialization techniques that exploit the a priori known, fixed runtime environment of many embedded systems. In experimental setups based on the ARM XScale and i386 platforms, the proposed techniques are able to reduce the kernel memory footprint with over 16%. We also show how relatively simple additions to existing binary rewriters can implement the proposed techniques for a complex, very unconventional program, such as the Linux kernel. We note that even after specialization, a lot of seemingly unnecessary code remains in the kernel and propose to reduce the footprint of this code by applying code-compression techniques. This technique, combined with the previous ones, reduces the memory footprint with over 23% for the i386 platform and 28% for the ARM platform. Finally, we pinpoint an important code size growth problem when compaction and compression techniques are combined on the ARM platform.