47,599 research outputs found
Trust, but Verify: Two-Phase Typing for Dynamic Languages
A key challenge when statically typing so-called dynamic languages is the
ubiquity of value-based overloading, where a given function can dynamically
reflect upon and behave according to the types of its arguments. Thus, to
establish basic types, the analysis must reason precisely about values, but in
the presence of higher-order functions and polymorphism, this reasoning itself
can require basic types. In this paper we address this chicken-and-egg problem
by introducing the framework of two-phased typing. The first "trust" phase
performs classical, i.e. flow-, path- and value-insensitive type checking to
assign basic types to various program expressions. When the check inevitably
runs into "errors" due to value-insensitivity, it wraps problematic expressions
with DEAD-casts, which explicate the trust obligations that must be discharged
by the second phase. The second phase uses refinement typing, a flow- and
path-sensitive analysis, that decorates the first phase's types with logical
predicates to track value relationships and thereby verify the casts and
establish other correctness properties for dynamically typed languages
Size-Change Termination as a Contract
Termination is an important but undecidable program property, which has led
to a large body of work on static methods for conservatively predicting or
enforcing termination. One such method is the size-change termination approach
of Lee, Jones, and Ben-Amram, which operates in two phases: (1) abstract
programs into "size-change graphs," and (2) check these graphs for the
size-change property: the existence of paths that lead to infinite decreasing
sequences.
We transpose these two phases with an operational semantics that accounts for
the run-time enforcement of the size-change property, postponing (or entirely
avoiding) program abstraction. This choice has two key consequences: (1)
size-change termination can be checked at run-time and (2) termination can be
rephrased as a safety property analyzed using existing methods for systematic
abstraction.
We formulate run-time size-change checks as contracts in the style of Findler
and Felleisen. The result compliments existing contracts that enforce partial
correctness specifications to obtain contracts for total correctness. Our
approach combines the robustness of the size-change principle for termination
with the precise information available at run-time. It has tunable overhead and
can check for nontermination without the conservativeness necessary in static
checking. To obtain a sound and computable termination analysis, we apply
existing abstract interpretation techniques directly to the operational
semantics, avoiding the need for custom abstractions for termination. The
resulting analyzer is competitive with with existing, purpose-built analyzers
A Simple and Scalable Static Analysis for Bound Analysis and Amortized Complexity Analysis
We present the first scalable bound analysis that achieves amortized
complexity analysis. In contrast to earlier work, our bound analysis is not
based on general purpose reasoners such as abstract interpreters, software
model checkers or computer algebra tools. Rather, we derive bounds directly
from abstract program models, which we obtain from programs by comparatively
simple invariant generation and symbolic execution techniques. As a result, we
obtain an analysis that is more predictable and more scalable than earlier
approaches. Our experiments demonstrate that our analysis is fast and at the
same time able to compute bounds for challenging loops in a large real-world
benchmark. Technically, our approach is based on lossy vector addition systems
(VASS). Our bound analysis first computes a lexicographic ranking function that
proves the termination of a VASS, and then derives a bound from this ranking
function. Our methodology achieves amortized analysis based on a new insight
how lexicographic ranking functions can be used for bound analysis
Static Analysis of Functional Programs
In this paper, the static analysis of programs in the functional programming language Miranda* is described based on two graph models. A new control-flow graph model of Miranda definitions is presented, and a model with four classes of callgraphs. Standard software metrics are applicable to these models. A Miranda front end for Prometrix, ¿, a tool for the automated analysis of flowgraphs and callgraphs, has been developed. This front end produces the flowgraph and callgraph representations of Miranda programs. Some features of the metric analyser are illustrated with an example program. The tool provides a promising access to standard metrics on functional programs
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