Olin Shivers

Control flow analysis in scheme

Traditional flow analysis techniques, such as the ones typically employed by optimizing Fortran compilers, do not work for Scheme-like languages. This paper presents a flow analysis technique — control flow analysis — which is applicable to Scheme-like languages. As a demonstration application, the information gathered by control flow analysis is used to perform a traditional flow analysis problem, induction variable elimination. Extensions and limitations are discussed. The techniques presented in this paper are backed up by working code. They are applicable not only to Scheme, but also to related languages, such as Common Lisp and ML.

The Flux OSKit: a substrate for kernel and language research

Implementing new operating systems is tedious, costly, and often impractical except for large projects. The Flux OSKit addresses this problem in a novel way by providing clean, well-documented OS components designed to be reused in a wide variety of other environments, rather than defining a new OS structure. The OSKit uses unconventional techniques to maximize its usefulness, such as intentionally exposing implementation details and platform-specific facilities. Further, the OSKit demonstrates a technique that allows unmodified code from existing mature operating systems to beincorporated quickly and updated regularly, by wrapping it with a small amount of carefully designed “glue” code to isolate it s dependencies and export well-defined interfaces. The OSKit uses this technique to incorporate over 230,000 lines of stable code including device drivers, file systems, and network protocols. Ourexperience demonstrates that this approach to component software structure and reuse has a surprisingly large impact in the OS implementation domain. Four real-world examples show how the OSKit is catalyzing research and development in operating systems and programming languages.

Improving flow analyses via ΓCFA: abstract garbage collection and counting

We present two independent and complementary improvements for flow-based analysis of higher-order languages: (1) abstract garbage collection and (2) abstract counting, collectively titled ΓCFA.Abstract garbage collection is an analog to its concrete counterpart: we determine when an abstract resource has become unreachable, and then reallocate it as fresh. This prevents flow sets from merging in the abstract, which has two immediate effects: (1) the precision of the analysis is increased, and (2) the running time of the analysis is frequently reduced. In some nontrivial cases, we achieve an order of magnitude improvement in precision and time simultaneously.In abstract counting, we track how many times an abstract resource has been allocated. A count of one implies that the abstract resource momentarily represents only one concrete resource. This, in turn, allows us to perform environment analysis and to expand the kinds (rather than just the degree) of optimizations available to the compiler.

CFA2: a context-free approach to control-flow analysis

In a functional language, the dominant control-flow mechanism is function call and return. Most higher-order flow analyses, including k-CFA, do not handle call and return well: they remember only a bounded number of pending calls because they approximate programs with control-flow graphs. Call/return mismatch introduces precision-degrading spurious control-flow paths and increases the analysis time. We describe CFA2, the first flow analysis with precise call/return matching in the presence of higher-order functions and tail calls. We formulate CFA2 as an abstract interpretation of programs in continuation passing style and describe a sound and complete summarization algorithm for our abstract semantics. A preliminary evaluation shows that CFA2 gives more accurate data-flow information than 0CFA and 1CFA.

Varieties of learning in Soar: 1987

Abstract : Soar is an architecture for intelligence that integrates learning into all of its problem-solving behavior. The learning mechanism, chunking, has been studied experimentally in a broad range of tasks and situations. This paper summarizes the research on chucking in Soar, covering the effects of chunking in different tasks, task-independent applications of chunking and our theoretical analyses of effects and limits of chunking. We discuss what and when Soar has been able to learn so far. The results demonstrate that the variety of learning in Soar arises from variety in problem solving, rather than from variety in architectural mechanisms. Keywords: Artificial intelligence, Machine learning, cognitive architecture.

Environment analysis via ΔCFA

We describe a new program-analysis framework, based on CPS and procedure-string abstractions, that can handle critical analyses which the k-CFA framework cannot. We present the main theorems concerning correctness, show an application analysis, and describe a running implementation.

Demand-Driven Type Inference with Subgoal Pruning: Trading Precision for Scalability

After two decades of effort, type inference for dynamically typed languages scales to programs of a few tens of thousands of lines of code, but no further. For larger programs, this paper proposes using a kind of demand-driven analysis where the number of active goals is carefully restricted. To achieve this restriction, the algorithm occasionally prunes goals by giving them solutions that are trivially true and thus require no further subgoals to be solved; the previous subgoals of a newly pruned goal may often be discarded from consideration, reducing the total number of active goals. A specific algorithm DDP is described which uses this approach. An experiment on DDP shows that it infers precise types for roughly 30% to 45% of the variables in a program with hundreds of thousands of lines; the percentage varies with the choice of pruning threshold, a parameter of the algorithm. The time required varies from an average of one-tenth of one second per variable to an unknown maximum, again depending on the pruning threshold. These data suggest that 50 and 2000 are both good choices of pruning threshold, depending on whether speed or precision is more important.

A Universal Scripting Framework or Lambda: The Ultimate Little Language

The “little languages” approach to systems programming is flawed: inefficient, fragile, error-prone, inexpressive, and difficult to compose. A better solution is to embed task-specific sublanguages within a powerful, syntactically extensible, universal language, such as Scheme. I demonstrate two such embeddings that have been implemented in scsh, a Scheme programming environment for Unix systems programming. The first embedded language is a highlevel process-control notation; the second provides for Awk-like processing. Embedding systems in this way is a powerful technique: for example, although the embedded Awk system was implemented with 7% of the code required for the standard C-based Awk, it is significantly more expressive than its C counterpart.

Continuations and transducer composition

On-line transducers are an important class of computational agent; we construct and compose together many software systems using them, such as stream processors, layered network protocols, DSP networks and graphics pipelines. We show an interesting use of continuations, that, when taken in a CPS setting, exposes the control flow of these systems. This enables a CPS-based compiler to optimise systems composed of these transducers, using only standard, known analyses and optimisations. Critically, the analysis permits optimisation across the composition of these transducers, allowing efficient construction of systems in a hierarchical way.

The anatomy of a loop: a story of scope and control

Writing loops with tail-recursive function calls is the equivalent of writing them with gotos. Given that loop packages for Lisp-family languages have been around for over 20 years, it is striking that none have had much success in the Scheme world. I suggest the reason is that Scheme forces us to be precise about the scoping of the various variables introduced by our loop forms, something previous attempts to design ambitious loop forms have not managed to do.I present the design of a loop package for Scheme with a well-defined and natural scoping rule, based on a notion of control dominance that generalizes the standard lexical-scope rule of the λ-calculus. The new construct is powerful, clear, modular and extensible.The loop language is defined in terms of an underlying language for expressing control-flow graphs. This language itself has interesting properties as an intermediate representation.