Code optimization for code compression

With the emergence of software delivery platforms such as Microsoft's .NET, the reduced size of transmitted binaries has become a very important system parameter, strongly affecting system performance. We present two novel pre-processing steps for code compression that explore program binaries' syntax and semantics to achieve superior compression ratios. The first preprocessing step involves heuristic partitioning of a program binary into streams with high auto-correlation. The second preprocessing step uses code optimization via instruction rescheduling in order to improve prediction probabilities for a given compression engine. We have developed three heuristics for instruction rescheduling that explore tradeoffs of the solution quality versus algorithm run-time. The pre-processing steps are integrated with the generic paradigm of prediction by partial matching (PPM) which is the basis of our compression codec. The compression algorithm is implemented for x86 binaries and tested on several large Microsoft applications. Binaries compressed using our compression codec are 18-24% smaller than those compressed using the best available off-the-shelf compressor.