UCLA

Modern software is bloated. Demand for new functionality has led developers to include more and more features, many of which become unneeded or unused as software evolves. This phenomenon of software bloat results in software consuming more resources than it otherwise needs to. Automation of effective debloating is a long standing problem in software engineering. Various software debloating techniques have been proposed since the late 1990s. However, many of these techniques are built upon pure static analysis and have yet to be extended and evaluated in the context of modern Java applications where dynamic language features are prevalent. To this end, we develop an end-to-end bytecode debloating framework called JShrink. JShrink augments traditional static reachability analysis with dynamic profiling and type dependency analysis, and renovates existing byte-code transformations to perform effective debloating. We highlight several nuanced technical challenges that must be handled properly to debloat modern Java applications and further examine behavior preservation of debloated software via regression testing. Our study finds that (1) JShrink is able to debloat our real-world Java benchmark suite by up to 47% (14% on average); (2) accounting for reflection and dynamic language features is crucial to ensure behavior preservation for debloated software | reducing 98% of test failures incurred by a purely static equivalent, Jax, and 84% for ProGuard; and (3) compared with purely dynamic approaches, integrating static analysis with dynamic profiling makes the debloated software more robust to unseen test executions|in 22 out of 26 projects, the debloated software ran successfully under new tests. We enhance JShrink with the checkpointing feature to ensure 100% behaviour preservation with minimal loss in code size reduction(0.9% om average), to make it a practical solution for balancing semantic preservation and code size reduction benefits