Enabling Additional Parallelism in Asynchronous JavaScript Applications (Artifact)

JavaScript is a single-threaded programming language, so asynchronous programming is practiced out of necessity to ensure that applications remain responsive in the presence of user input or interactions with file systems and networks. However, many JavaScript applications execute in environments that do exhibit concurrency by, e.g., interacting with multiple or concurrent servers, or by using file systems managed by operating systems that support concurrent I/O. In this paper, we demonstrate that JavaScript programmers often schedule asynchronous I/O operations suboptimally, and that reordering such operations may yield significant performance benefits. Concretely, we define a static side-effect analysis that can be used to determine how asynchronous I/O operations can be refactored so that asynchronous I/O-related requests are made as early as possible, and so that the results of these requests are awaited as late as possible. While our static analysis is potentially unsound, we have not encountered any situations where it suggested reorderings that change program behavior. We evaluate the refactoring on 20 applications that perform file- or network-related I/O. For these applications, we observe average speedups ranging between 0.99% and 53.6% for the tests that execute refactored code (8.1% on average)

Enabling Additional Parallelism in Asynchronous JavaScript Applications

JavaScript is a single-threaded programming language, so asynchronous programming is practiced out of necessity to ensure that applications remain responsive in the presence of user input or interactions with file systems and networks. However, many JavaScript applications execute in environments that do exhibit concurrency by, e.g., interacting with multiple or concurrent servers, or by using file systems managed by operating systems that support concurrent I/O. In this paper, we demonstrate that JavaScript programmers often schedule asynchronous I/O operations suboptimally, and that reordering such operations may yield significant performance benefits. Concretely, we define a static side-effect analysis that can be used to determine how asynchronous I/O operations can be refactored so that asynchronous I/O-related requests are made as early as possible, and so that the results of these requests are awaited as late as possible. While our static analysis is potentially unsound, we have not encountered any situations where it suggested reorderings that change program behavior. We evaluate the refactoring on 20 applications that perform file- or network-related I/O. For these applications, we observe average speedups ranging between 0.99% and 53.6% for the tests that execute refactored code (8.1% on average)

A slicing-based approach for locating type errors

The effectiveness of a type checking tool strongly depends on the accuracy of the positional information that is associated with type errors. We present an approach where the location associated with an error message e is defined as a slice P_e of the program P being type checked. We show that this approach yields highly accurate positional information: P_e is a program that contains precisely those program constructs in P that caused error e. Semantically, we have the interesting property that type checking P_e is guaranteed to produce the same error e. Our approach is completely language-independent, and has been implemented for a significant subset of Pascal

A slicing-based approach for locating type errors

The effectiveness of a type checking tool strongly depends on the accuracy of the positional information that is associated with type errors. We present an approach where the location associated with an error message e is defined as a slice P_e of the program P being type checked. We show that this approach yields highly accurate positional information: P_e is a program that contains precisely those program constructs in P that caused error e. Semantically, we have the interesting property that type checking P_e is guaranteed to produce the same error e. Our approach is completely language-independent, and has been implemented for a significant subset of Pascal

An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation

Unit tests play a key role in ensuring the correctness of software. However, manually creating unit tests is a laborious task, motivating the need for automation. Large Language Models (LLMs) have recently been applied to this problem, utilizing additional training or few-shot learning on examples of existing tests. This paper presents a large-scale empirical evaluation on the effectiveness of LLMs for automated unit test generation without additional training or manual effort, providing the LLM with the signature and implementation of the function under test, along with usage examples extracted from documentation. We also attempt to repair failed generated tests by re-prompting the model with the failing test and error message. We implement our approach in TestPilot, a test generation tool for JavaScript that automatically generates unit tests for all API functions in an npm package. We evaluate TestPilot using OpenAI's gpt3.5-turbo LLM on 25 npm packages with a total of 1,684 API functions. The generated tests achieve a median statement coverage of 70.2% and branch coverage of 52.8%, significantly improving on Nessie, a recent feedback-directed JavaScript test generation technique, which achieves only 51.3% statement coverage and 25.6% branch coverage. We also find that 92.8% of TestPilot's generated tests have no more than 50% similarity with existing tests (as measured by normalized edit distance), with none of them being exact copies. Finally, we run TestPilot with two additional LLMs, OpenAI's older code-cushman-002 LLM and the open LLM StarCoder. Overall, we observed similar results with the former (68.2% median statement coverage), and somewhat worse results with the latter (54.0% median statement coverage), suggesting that the effectiveness of the approach is influenced by the size and training set of the LLM, but does not fundamentally depend on the specific model

Refactoring for parameterizing Java classes

Type safety and expressiveness of many existing Java libraries and theirclient applications would improve, if the libraries were upgraded to definegeneric classes. Efficient and accurate tools exist to assist clientapplications to use generics libraries, but so far the libraries themselvesmust be parameterized manually, which is a tedious, time-consuming, anderror-prone task. We present a type-constraint-based algorithm forconverting non-generic libraries to add type parameters. The algorithmhandles the full Java language and preserves backward compatibility, thusmaking it safe for existing clients. Among other features, it is capableof inferring wildcard types and introducing type parameters formutually-dependent classes. We have implemented the algorithm as a fullyautomatic refactoring in Eclipse.We evaluated our work in two ways. First, our tool parameterized code thatwas lacking type parameters. We contacted the developers of several ofthese applications, and in all cases where we received a response, theyconfirmed that the resulting parameterizations were correct and useful.Second, to better quantify its effectiveness, our tool parameterizedclasses from already-generic libraries, and we compared the results tothose that were created by the libraries' authors. Our tool performed therefactoring accurately -- in 87% of cases the results were as good as thosecreated manually by a human expert, in 9% of cases the tool results werebetter, and in 4% of cases the tool results were worse

Animators and error reporters for generated programming environments

We study animators and error reporters for generated programming environments. An error reporter is a tool for indicating the exact position of a type-error in the source text. An animator visualizes program execution; typically, it highlights the statement that is currently executing. Applications of both tools are mainly to be found in the areas of debugging and tutoring. Instead of explicitly extending language specifications with these facilities, we claim that error reporters and animators can be generated from existing specifications for type-checkers and interpreters with little effort; to this end, a simple pattern-matching mechanism is used in conjunction with origin tracking, a generic tracing technique. In this paper, we discuss our claim, and at the same time investigate the limitations and deficiencies of origin tracking. Our techniques are illustrated using an example language named CLaX, a Pascal relative. The full specifications of the CLaX syntax, type-checker and interpreter are included in appendices