Abstract. Object-oriented programs often require large heaps to run properly or meet performance goals. They use high-overhead collections, bulky data models, and large caches. Discovering this is quite challenging. Manual browsing and flat summaries do not scale to complex graphs with 20 million objects. Context is crucial to understanding responsibility and inefficient object connectivity. We summarize memory footprint with help from the dominator relation. Each dominator tree captures unique ownership. Edges between trees capture responsibility. We introduce a set of ownership structures, and quantify their abundance. We aggregate these structures, and use thresholds to identify important aggregates. We introduce the ownership graph to summarize responsibility, and backbone equivalence to aggregate patterns within trees. Our implementation quickly generates concise summaries. In two minutes, it generates a 14-node ownership graph from 29 million objects. Backbone equivalence identifies a handful of patterns that account for 80 % of a tree’s footprint. 1

Program slicing is a technique for determining the set of statements of a program that potentially affect the value of a variable at some point in the program. Intra and interprocedural slicing of high-level languages has greatly been studied in the literature; both static and dynamic techniques have been used to aid in the debugging, maintenance, parallelization, program integration, and dataflow testing of programs. In this paper we explain how to apply conventional intraprocedural static analysis to binary executables, for the purposes of static analysis of machine-code and assembly code, such as debugging code and determining the instructions that affect an indexed jump or an indirect call on a register. This analysis is useful in the decoding of machine instructions phase of reverse engineering tools of binary executables, such as binary translators, disassemblers, binary profilers and binary debuggers. 1 Introduction It is well known that a series of programmers worked for days...

. Analysis of symbolic expressions benefits from a suitable program representation. We show how to build thinned gated singleassignment (TGSA) form, a value-oriented program representation which is more complete than standard SSA form, defined on all reducible programs, and better for representing symbolic expressions than program dependence graphs or original GSA form. We present practical algorithms for constructing thinned GSA form from the control dependence graph and SSA form. Extensive experiments on large Fortran programs show these methods to take linear time and space in practice. Our implementation of value numbering on TGSA form drives scalar symbolic analysis in the ParaScope programming environment. 1 Introduction Analysis of non-constant values yields significant benefits in a parallelizing compiler. The design of a symbolic analyzer requires careful choice of a program representation, that these benefits may be gained without using excessive time and space. In symbolic ...

We present a new limited form of interprocedural analysis called field analysis that can be used by a compiler to reduce the costs of modern language features such as objectoriented programming, automatic memory management, and run-time checks required for type safety. Unlike many previous interprocedural analyses, our analysis is cheap, and does not require access to the entire program. Field analysis exploits the declared access restrictions placed on fields in a modular language (e.g. field access modifiers in Java) in order to determine useful properties of fields of an object. We describe our implementation of field analysis in the Swift optimizing compiler for Java, as well a set of optimizations that exploit the results of field analysis. These optimizations include removal of run-time tests, compiletime resolution of method calls, object inlining, removal of unnecessary synchronization, and stack allocation. Our results demonstrate that field analysis is efficient and effectiv...

This paper presents a new al gS ithm for operator strengM reduction, called OSR. OSR improves upon an earlier alg orithm due to Allen, Cocke, and Kennedy [Allen et al. 1981]. OSR operates on the static sing e assig4 ent (SSA) form of a procedure [Cytron et al. 1991]. By taking advantag of the properties of SSA form, we have derived an alg--- ithm that is simple to understand, quick to implement, and, in practice, fast to run. Its asymptotic complexity is, in the worst case, the same as the Allen, Cocke, and Kennedy al gS ithm (ACK). OSR achieves optimization results that are equivalent to those obtained with the ACK alg orithm. OSR has been implemented in several research and production compilers

We present two new data structure tools---disjoint set union with bottom-up linking, and pointer-based radix sort---and combine them with bottom-level microtrees to devise the first linear-time pointer-machine algorithms for off-line least common ancestors, minimum spanning tree (MST) verification, randomized MST construction, and computing dominators in a flowgraph.

Parallel and distributed programming languages often include explicit synchronization primitives, such as rendezvous and semaphores. Such programs are subject to synchronization anomalies; the program behaves incorrectly because it has a faulty synchronization structure. A deadlock is an anomaly in which some subset of the active tasks of the program mutually wait on each other to advance; thus, the program cannot complete execution. In static anomaly detection, the source code of a program is automatically analyzed to determine if the program can ever exhibit a specific anomaly. Static anomaly detection has the unique advantage that it can certify programs to be free of the tested anomaly; dynamic testing cannot generally do this. Though exact static detection of deadlocks is NP-hard [Tay83a], many researchers have tried to detect deadlock by ...

A linear time algorithm is presented for finding dominators in control flow graphs.

The problem of finding the dominators in a control-flow graph has a long history in the literature. The original algorithms su#ered from a large asymptotic complexity but were easy to understand. Subsequent work improved the time bound, but generally sacrificed both simplicity and ease of implementation. This paper returns to a simple formulation of dominance as a global data-flow problem. Some insights into the natureofdominance lead to an implementation of an O(N )algorithm that runs faster, in practice, than the classic Lengauer-Tarjan algorithm, which has a timebound of O(E log(N)). We compare the algorithm to Lengauer-Tarjan because it is the best known and most widely used of the fast algorithms for dominance. Working from the same implementationinsights,wealso rederive (from earlier work on control dependence by Ferrante, et al.)amethodforcalculating dominance frontiers that we show is faster than the original algorithm by Cytron, et al. The aim of this paper is not to present a new algorithm, but, rather, to make an argument based on empirical evidence that algorithms with discouraging asymptotic complexities can be faster in practice than those more commonly employed. We show that, in some cases, careful engineering of simple algorithms can overcome theoretical advantages, even when problems grow beyond realistic sizes. Further, we argue that the algorithms presented herein are intuitive and easily implemented, making them excellent teaching tools.

Many software engineering tools such as program slicers must perform data-flow analysis in order to extract necessary information from the program source. These tools typically borrow much of their implementation from optimizing compilers. However, since these tools are expected to analyze programs in their entirety, rather than functions in isolation, the time and space performance of the dataflow analyses are of major concern. We present techniques that reduce the time and space required to perform dataflow analysis of large programs. We have used these techniques to implement an efficient program slicing tool for C programs and have computed slices of programs with more than 100,000 lines of code.