We propose a novel approach to the view update problem for tree-structured data: a domainspecific programming language in which all expressions denote bi-directional transformations on trees. In one direction, these transformations—dubbed lenses—map a “concrete ” tree into a simplified “abstract view”; in the other, they map a modified abstract view, together with the original concrete tree, to a correspondingly modified concrete tree. Our design emphasizes both robustness and ease of use, guaranteeing strong well-behavedness and totality properties for welltyped lenses. We identify a natural mathematical space of well-behaved bi-directional transformations over arbitrary structures, study definedness and continuity in this setting, and state a precise connection with the classical theory of “update translation under a constant complement ” from databases. We then instantiate this semantic framework in the form of a collection of lens combinators that can be assembled to describe transformations on trees. These combinators include familiar constructs from functional programming (composition, mapping, projection, conditionals, recursion) together with some novel primitives for manipulating trees (splitting, pruning, copying, merging, etc.). We illustrate the expressiveness of these combinators by developing a number of bi-directional listprocessing transformations as derived forms. An extended example shows how our combinators can be used to define a lens that translates between a native HTML representation of browser bookmarks and a generic abstract bookmark format.

We present an algorithm for inverse computation in a first-order functional language based on the notion of a perfect process tree. The Universal Resolving Algorithm (URA) introduced in this paper is sound and complete, and computes each solution, if it exists, in finite time. The algorithm has been implemented for TSG, a typed dialect of S-Graph, and shows some remarkable results for the inverse computation of functional programs such as pattern matching and the inverse interpretation of While-programs.

We survey fundamental concept in inverse programming and present the Universal Resolving Algorithm (URA), an algorithm for inverse computation in a first-order, functional programming language. We discusst he principles behind the algorithm, including a three-step approach based on the notion of a perfect process tree, and demonstrate our implementation with several examples. We explaint he idea of a semantics modifier for inverse computation which allows us to perform inverse computation in other programming languages via interpreters.

A notation is given for describing the inverse of multiple functions and of functions of multiple arguments. A technique based upon this notation is presented for taking a program written in pure LISP and automatically deriving a program which computes the inverse function of the given program. This technique di#ers from previous such methods in its use of heuristics to invert conditionals. # x) 2 = x rather than LISP append reverse as given in [2], unary add1 and sub1, and sev- 1. Introduction There are many applications in which it is useful to compute the inverse of some program, that is, to find another program such that feeding the output of the original program as input to the new program produces the original input. One such application is in programming by specification: one would like to define a program to compute the square root of a number by the equation ( supplying an actual iterative method of solving the equation. Another application of program inversion is in...

Imperative programs can be inverted directly from their forward-directed program code with the use of logical inference. The relational semantics of imperative computations treats programs as logical relations over the observable state of the environment, which is taken to be the state of the variables in memory. Program relations denote both forward and backward computations, and the direction of the computation depends upon the instantiation pattern of arguments in the relation. This view of inversion has practical applications when the relational semantics is treated as a logic program. Depending on the logic programming inference scheme used, execution of this relational program can compute the inverse of the imperative program. A number of nontrivial imperative computations can be inverted with minimal logic programming tools.

In this paper, we investigate the problem of semi-automated inversion of imperative programs, which has the potential to make it much easier and less error prone to write programs that naturally pair as inverses, such as insert/delete operations, compressors/decompressors, and so on. Viewing inversion as a subproblem of program synthesis, we propose a novel synthesis technique called Path-based Inductive Synthesis (PINS) and apply it to inversion. PINS starts from a program P and a template T for its inverse. PINS then iteratively refines the space of template instantiations by exploring paths in the composition of P and T with symbolic execution. PINS uses an SMT solver to intelligently guide the refinement process, based on the paths explored so far. The key idea motivating this approach is the small path-bound hypothesis: that the behavior of a program can be summarized with a small, carefully chosen set of its program paths. We evaluated PINS by using it to invert 14 programs such as compressors (e.g., Lempel-Ziv-Welch), encoders (e.g., UUEncode), and arithmetic operations (e.g., vector rotation). Most of these examples are difficult or impossible to invert using prior techniques, but PINS was able to invert all of them. We also found that a semi-automated technique we developed to mine a template from the program to be inverted worked well. In our experiments, PINS takes between one second to thirty minutes to synthesize inverses. We believe this proof-of-concept implementation demonstrates the viability of the PINS approach to program synthesis.

Invertible programming occurs in the area of data conversion where it is required that the conversion in one direction is the inverse of the other. For that purpose, we introduce bidirectional arrows (biarrows). The bi-arrow class is an extension of Haskell’s arrow class with an extra combinator that changes the direction of computation. The advantage of the use of bi-arrows for invertible programming is the preservation of invertibility properties using the biarrow combinators. Programming with bi-arrows in a polytypic or generic way exploits this the most. Besides bidirectional polytypic examples, including invertible serialization, we give the definition of a monadic bi-arrow transformer, which we use to construct a bidirectional parser/pretty printer.

The need to edit data through a view arises in a host of applications across many different areas of computing. Unfortunately, few existing systems provide support for updatable views. In practice, when they are needed, updatable views are usually implemented using two separate programs: one to compute the view from the source and another to handle updates. This rudimentary design is tedious for programmers, dif�cult to reason about, and a nightmare to maintain. This dissertation describes bidirectional programming languages, which provide an elegant mechanism for describing updatable views. Unlike programs written in an ordinary language, which only work in one direction, programs written in a bidirectional language can be run both forwards and backwards: from left to right, they describe functions that map sources to views, and from right to left, they describe functions that map updated views back to updated sources. Besides eliminating redundancy, these languages can be designed to ensure correctness, guaranteeing by construction that the two functions work well together.

Replace this file with prentcsmacro.sty for your meeting, or with entcsmacro.sty for your meeting. Both can be

The experiments in this paper apply the idea of prototyping programming language tools from robust semantics: we used a partial evaluator (Similix) to turn interpreters into inverse interpreters. This way we generated inverse interpreters for several small languages including interpreters for Turing machines, an applied lambda calculus, a flowchart language, and a subset of Java bytecode. Limiting factors of offline partial evaluation were the polyvariant specialization scheme with its lack of generalization; advantages were the availability of higher-order values to specialize a breadthfirst tree traversal. This application of self-applicable partial evaluation is different from the classical Futamura projections that tell us how to translate a program by specialization of an interpreter.