We present a new code assistance tool for integrated development environments. Our system accepts free-form queries allowing a mixture of English and Java as an input, and produces Java code fragments that take the query into account and respect syntax, types, and scoping rules of Java as well as statistical usage patterns. The returned results need not have the structure of any previously seen code fragment. As part of our system we have constructed a probabilistic context free grammar for Java constructs and library invocations, as well as an algorithm that uses a customized natural language processing tool chain to extract information from free-form text queries. The evaluation results show that our technique can tolerate much of the flexibility present in natural language, and can also be used to repair incorrect Java expressions that contain useful information about the developer's intent. Our demo video is available at http://youtu.be/tx4-XgAZkKU.

We present a new code assistance tool for integrated development environments. Our system accepts as input free-form queries containing a mixture of English and Java, and produces Java code expressions that take the query into account and respect syntax, types, and scoping rules of Java, as well as statistical usage patterns. In contrast to solutions based on code search, the results returned by our tool need not directly correspond to any previously seen code fragment. As part of our system we have constructed a probabilistic context free grammar for Java constructs and library invocations, as well as an algorithm that uses a customized natural language processing tool chain to extract information from free-form text queries. We present the results on a number of examples showing that our technique (1) often produces the expected code fragments, (2) tolerates much of the flexibility of natural language, and (3) can repair incorrect Java expressions that use, for example, the wrong syntax or missing arguments.

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.

Successful software systems continuously change their requirements and thus code. When this happens, some existing tests get broken because they no longer reflect the intended behavior, and thus they need to be updated. Repairing broken tests can be time-consuming and difficult.

We present an approach for describing tests using non-deterministic test generation programs. To write such programs, we introduce UDITA, a Java-based language with non-deterministic choice operators and an interface for generating linked structures. We also describe new algorithms that generate concrete tests by efficiently exploring the space of all executions of non-deterministic UDITA programs.

When developers change a program, regression tests can fail not only due to faults in the program but also due to out-of-date test code that does not reflect the desired behavior of the program. When this occurs, it is necessary to repair test code such that the tests pass. Repairing tests manually is difficult and time consuming. We recently developed ReAssert, a tool that can automatically repair broken unit tests, but only if they lack complex control flow or operations on expected values.

Java PathFinder (JPF) is a popular model checker for Java programs. JPF was used to generate object graphs as test inputs for object-oriented programs. Specifically, JPF was used as an implementation engine for the Korat algorithm. Korat takes two inputs---a Java predicate that encodes properties of desired object graphs and a bound on the size of the graph---and generates all graphs (within the given bound) that satisfy the encoded properties. Korat uses a systematic search to explore the bounded state space of object graphs. Korat search was originally implemented in JPF using a simple instrumentation of the Java predicate. However, JPF is a general-purpose model checker and such direct implementation results in an unnecessarily slow search. We present our results on speeding up Korat search in JPF. The experiments on ten data structure subjects show that our modifications of JPF reduce the search time by over an order of magnitude.

Java PathFinder (JPF) is an explicit-state model checker for Java programs. JPF implements a backtrackable Java Virtual Machine (JVM) that provides non-deterministic choices and control over thread scheduling. JPF is itself implemented in Java and runs on top of a host JVM. JPF represents the JVM state of the program being checked and performs three main operations on this state representation: bytecode execution, state backtracking, and state comparison. This paper summarizes four extensions that we have developed to the JPF state representation and operations. One extension provides a new functionality to JPF, and three extensions improve performance of JPF in various scenarios. Some of our code has already been included in publicly available JPF.