No abstract

As object-oriented class libraries evolve, classes are occasionally deprecated in favor of others with roughly the same functionality. In Java's standard libraries, for example, class Hashtable has been superseded by HashMap, and Iterator is now preferred over Enumeration. Migrating client applications to use the new idioms is often desirable, but making the required changes to declarations and allocation sites can be quite labor-intensive. Moreover, migration becomes complicated-and sometimes impossible-if an application interacts with external components, if a legacy class is not completely equivalent to its replacement, or if multiple interdependent classes must be migrated simultaneously. We present an approach in which mappings between legacy classes and their replacements are specified by the programmer. Then, an analysis based on type constraints determines where declarations and allocation sites can be updated. The method was implemented in Eclipse, and evaluated on a number of Java applications. On average, our tool could migrate more than 90% of the references to legacy classes.

No abstract

Type constraints express subtype relationships between the types of program expressions, for example, those relationships that are required for type correctness. Type constraints were originally proposed as a convenient framework for solving type checking and type inference problems. This paper shows how type constraints can be used as the basis for practical refactoring tools. In our approach, a set of type constraints is derived from a type-correct program P. The main insight behind our work is the fact that P constitutes just one solution to this constraint system, and that alternative solutions may exist that correspond to refactored versions of P. We show how a number of refactorings for manipulating types and class hierarchies can be expressed naturally using type constraints. Several refactorings in the standard distribution of Eclipse are based on our work

Predicate abstraction has become one of the most successful methodologies for proving safety properties of programs. Recently, several abstraction methodologies have been proposed for proving liveness properties. This paper studies "ranking abstraction" where a program is augmented by a non-constraining progress monitor based on a set of ranking functions, and further abstracted by predicate-abstraction, to allow for automatic verification of progress properties. Unlike many liveness methodologies, the augmentation does not require a complete ranking function that is expected to decrease with each helpful step. Rather, adequate user-provided inputs are component rankings from which a complete ranking function may be automatically formed. The premise of the paper is an analogy between the methods of ranking abstraction and predicate abstraction, one ingredient of which is refinement: When predicate abstraction fails, one can refine it. When ranking abstraction fails, one must determine whether the predicate abstraction, or the ranking abstraction, needs be refined. The paper presents strategies for determining which case is at hand, and methods for performing the apporpriate refinements. The other part of the analogy is that of automatically deriving deductive proof constructs: Predicate abstraction is often used to derive program invariants for proving safety properties as a boolean combination of the given predicates. Deductive proof of progress properties requires well-founded ranking functions in addition to invariants. We show how the constructs necessary for a deductive proof of an arbitrary LTL formula can be automatically extracted from a successful application of the ranking abstraction method.