Introspective Pushdown Analysis of Higher-Order Programs

In the static analysis of functional programs, pushdown flow analysis and abstract garbage collection skirt just inside the boundaries of soundness and decidability. Alone, each method reduces analysis times and boosts precision by orders of magnitude. This work illuminates and conquers the theoretical challenges that stand in the way of combining the power of these techniques. The challenge in marrying these techniques is not subtle: computing the reachable control states of a pushdown system relies on limiting access during transition to the top of the stack; abstract garbage collection, on the other hand, needs full access to the entire stack to compute a root set, just as concrete collection does. \emph{Introspective} pushdown systems resolve this conflict. Introspective pushdown systems provide enough access to the stack to allow abstract garbage collection, but they remain restricted enough to compute control-state reachability, thereby enabling the sound and precise product of pushdown analysis and abstract garbage collection. Experiments reveal synergistic interplay between the techniques, and the fusion demonstrates "better-than-both-worlds" precision.Comment: Proceedings of the 17th ACM SIGPLAN International Conference on Functional Programming, 2012, AC

Back-traced Garbage Collection

This disclosure describes back-traced garbage collection in a computer. A back-traced garbage collector searches backwards from an object in an object graph, until a root node is encountered, or until there are no further objects to search. If a root node is not encountered, the searched objects are unreachable and are deleted. The garbage collector can run incrementally, process portions of the object graph, and determine reachability of individual objects without examining the entire object graph. The garbage collector has low latency. The garbage collector is tunable, for example, in response to program characteristics and performance requirements

Pruning, Pushdown Exception-Flow Analysis

Statically reasoning in the presence of exceptions and about the effects of exceptions is challenging: exception-flows are mutually determined by traditional control-flow and points-to analyses. We tackle the challenge of analyzing exception-flows from two angles. First, from the angle of pruning control-flows (both normal and exceptional), we derive a pushdown framework for an object-oriented language with full-featured exceptions. Unlike traditional analyses, it allows precise matching of throwers to catchers. Second, from the angle of pruning points-to information, we generalize abstract garbage collection to object-oriented programs and enhance it with liveness analysis. We then seamlessly weave the techniques into enhanced reachability computation, yielding highly precise exception-flow analysis, without becoming intractable, even for large applications. We evaluate our pruned, pushdown exception-flow analysis, comparing it with an established analysis on large scale standard Java benchmarks. The results show that our analysis significantly improves analysis precision over traditional analysis within a reasonable analysis time.Comment: 14th IEEE International Working Conference on Source Code Analysis and Manipulatio

Liveness-Based Garbage Collection for Lazy Languages

We consider the problem of reducing the memory required to run lazy first-order functional programs. Our approach is to analyze programs for liveness of heap-allocated data. The result of the analysis is used to preserve only live data---a subset of reachable data---during garbage collection. The result is an increase in the garbage reclaimed and a reduction in the peak memory requirement of programs. While this technique has already been shown to yield benefits for eager first-order languages, the lack of a statically determinable execution order and the presence of closures pose new challenges for lazy languages. These require changes both in the liveness analysis itself and in the design of the garbage collector. To show the effectiveness of our method, we implemented a copying collector that uses the results of the liveness analysis to preserve live objects, both evaluated (i.e., in WHNF) and closures. Our experiments confirm that for programs running with a liveness-based garbage collector, there is a significant decrease in peak memory requirements. In addition, a sizable reduction in the number of collections ensures that in spite of using a more complex garbage collector, the execution times of programs running with liveness and reachability-based collectors remain comparable

A Story of Parametric Trace Slicing, Garbage and Static Analysis

This paper presents a proposal (story) of how statically detecting unreachable objects (in Java) could be used to improve a particular runtime verification approach (for Java), namely parametric trace slicing. Monitoring algorithms for parametric trace slicing depend on garbage collection to (i) cleanup data-structures storing monitored objects, ensuring they do not become unmanageably large, and (ii) anticipate the violation of (non-safety) properties that cannot be satisfied as a monitored object can no longer appear later in the trace. The proposal is that both usages can be improved by making the unreachability of monitored objects explicit in the parametric property and statically introducing additional instrumentation points generating related events. The ideas presented in this paper are still exploratory and the intention is to integrate the described techniques into the MarQ monitoring tool for quantified event automata.Comment: In Proceedings PrePost 2017, arXiv:1708.0688