Interactive Code Generation

This thesis presents two approaches to code generation (synthesis) along with a discussion of other related and influential works, their ideas and relations to these approaches. The common goal of these approaches is to efficiently and effectively assist developers in software development by synthesizing code for them and save their efforts. The two presented approaches differ in the nature of the synthesis problem they try to solve. They are targeted to be useful in different scenarios, apply different set of techniques and can even be complementary. The first approach to code synthesis relies on typing information of a program to define and drive the synthesis process. The main requirement imposes that synthesized solutions have the desired type. This can aid developers in many scenarios of modern software development which typically involves composing functionality from existing libraries which expose a rich API. Our observation is that the developer usually does not know the right combination for composing API calls but knows the type of the desired expression. With the basis being the well-known type inhabitation problem we introduce a succinct representation for type judgements that significantly speed up the search for type inhabitants. Our method finds multiple solutions and ranks them before offering them to the developer. We implemented this approach as a plugin for the Eclipse IDE for Scala. From the evaluation we concluded that this approach goes beyond available related techniques and can be very useful in practical software development. In the second approach, synthesis of code is driven by explicit specification of code in terms of (formal) specification. The goal is to allow the developer to specify a program, by giving formal description of its behavior, rather than writing the code - the actual implementation is synthesized automatically. The practical value of such synthesis is immediately clear since this problem is generally hard. The approach solves this problem by combining existing tools for code generation, verification and testing within the synthesis process, and applies techniques for speeding it up. Interesting modifications to the synthesis driven by types were made to allow synthesizing expressions lazily, on demand, by searching for solutions in an incremental fashion. Results of the evaluation on several examples show that the implementation can be effective and useful in practice, while the approach still offers a lot of room for improvements

Leveraging Sequential Computation for Programming Efficient and Reliable Distributed Systems

While sequential programs represent a simple and natural form for expressing functionality, corresponding distributed implementations get considerably more complex. We examine the possibility of using the sequential computation model for programming distributed systems and requirements for making that possible. The benefits of such an approach include easier specification and reasoning about behaviors in the system, as well as a possibility to directly reuse existing techniques for checking correctness and optimization of sequential programs to produce efficient and reliable distributed implementations

Complete Completion using Types and Weights

Developing modern software typically involves composing functionality from existing libraries. This task is difficult because libraries may expose many methods to the developer. To help developers in such scenarios, we present a technique that synthesizes and suggests valid expressions of a given type at a given program point. As the basis of our technique we use type inhabitation for lambda calculus terms in long normal form. We introduce a succinct representation for type judgements that merges types into equivalence classes to reduce the search space, then reconstructs any desired number of solutions on demand. Furthermore, we introduce a method to rank solutions based on weights derived from a corpus of code. We implemented the algorithm and deployed it as a plugin for the Eclipse IDE for Scala. We show that the techniques we incorporated greatly increase the effectiveness of the approach. Our evaluation benchmarks are code examples from programming practice; we make them available for future comparisons

On Fast Code Completion using Type Inhabitation

Developing modern software applications typically involves composing functionality from existing libraries. This task is difficult because libraries may expose many methods to the developer. To help developers in such scenarios, we present a technique that synthesizes and suggests valid expressions of a given type at a given program point. As the basis of our technique we use type reconstruction for lambda calculus with subtyping. We show that the inhabitation problem in the presence of subtyping remains PSPACE-complete. We introduce a succinct representation for type judgements that merges types into equivalence classes to reduce the search space. We introduce a proof rule on this succinct representation of types and show that it is sound and complete for inhabitation. We implemented the resulting algorithm and deployed it as a plugin for the Eclipse IDE for Scala

Program synthesis from polymorphic refinement types

We present a method for synthesizing recursive functions that provably satisfy a given specification in the form of a polymorphic refinement type. We observe that such specifications are particularly suitable for program synthesis for two reasons. First, they offer a unique combination of expressive power and decidability, which enables automatic verification—and hence synthesis—of nontrivial programs. Second, a type-based specification for a program can often be effectively decomposed into independent specifications for its components, causing the synthesizer to consider fewer component combinations and leading to a combinatorial reduction in the size of the search space. At the core of our synthesis procedure is a newalgorithm for refinement type checking, which supports specification decomposition. We have evaluated our prototype implementation on a large set of synthesis problems and found that it exceeds the state of the art in terms of both scalability and usability. The tool was able to synthesize more complex programs than those reported in prior work (several sorting algorithms and operations on balanced search trees), as well as most of the benchmarks tackled by existing synthesizers, often starting from a more concise and intuitive user input.National Science Foundation (U.S.) (Grant CCF-1438969)National Science Foundation (U.S.) (Grant CCF-1139056)United States. Defense Advanced Research Projects Agency (Grant FA8750-14-2-0242

Leveraging Sequential Computation for Programming Efficient and Reliable Distributed Systems

© Ivan Kuraj and Armando Solar-Lezama; licensed under Creative Commons License CC-BY. While sequential programs represent a simple and natural form for expressing functionality, corresponding distributed implementations get considerably more complex. We examine the possibility of using the sequential computation model for programming distributed systems and requirements for making that possible. The benefits of such an approach include easier specification and reasoning about behaviors in the system, as well as a possibility to directly reuse existing techniques for checking correctness and optimization of sequential programs to produce efficient and reliable distributed implementations

On Repairing Ill-Typed Expressions

Abstract. When developing code, a programmer typically knows the approximate structure of the desired expression. However, often the first attempt at writing it down results in an ill-typed code fragment. We propose an approach that automatically repairs code expressions based on the provided almost-correct code. Such a code repair can be applied in interactive scenarios like advanced code completion, as well as in automated repair in the compilation process. We formally define the problem of automatically repairing ill-typed expressions. For the certain class of problems we describe a polynomial time synthesis algorithm that returns the best well-typed expression corresponding to the given ill-typed expression. We also present a complete algorithm that takes as input an ill-typed expression and returns the desired number of type-correct expressions that are closest to the input expression. We simultaneously fix all the type errors in the expression