相关论文: Observation-based unit test generation at Meta

The testing phase is an essential part of software development, but manually creating test cases can be time-consuming. Consequently, there is a growing need for more efficient testing methods. To reduce the burden on developers, various…

We can never be certain that a software system is correct simply by testing it, but with every additional successful test we become less uncertain about its correctness. In absence of source code or elaborate specifications and models,…

Unit tests represent the most basic level of testing within the software testing lifecycle and are crucial to ensuring software correctness. Designing and creating unit tests is a costly and labor-intensive process that is ripe for…

Deep learning (DL)-based systems can exhibit unexpected behavior when exposed to out-of-distribution (OOD) scenarios, posing serious risks in safety-critical domains such as malware detection and autonomous driving. This underscores the…

Machine learning models have been trained to predict semantic information about user interfaces (UIs) to make apps more accessible, easier to test, and to automate. Currently, most models rely on datasets that are collected and labeled by…

Mutation analysis assesses a test suite's adequacy by measuring its ability to detect small artificial faults, systematically seeded into the tested program. Mutation analysis is considered one of the strongest test-adequacy criteria.…

Mutation testing has been widely used to assess the fault-detection effectiveness of a test suite, as well as to guide test case generation or prioritization. Empirical studies have shown that, while mutants are generally representative of…

Android User Interface (UI) testing is a critical research area due to the ubiquity of apps and the challenges faced by developers. Record and replay (R&R) tools facilitate manual and automated UI testing by recording UI actions to execute…

White-box test generator tools rely only on the code under test to select test inputs, and capture the implementation's output as assertions. If there is a fault in the implementation, it could get encoded in the generated tests. Tool…

Most defects in mobile applications are visually observable on the device screen. To track these defects, users, testers, and developers must manually submit bug reports, especially in the absence of crashes. However, these reports are…

Estimating software testability can crucially assist software managers to optimize test budgets and software quality. In this paper, we propose a new approach that radically differs from the traditional approach of pursuing testability…

Applications of reversible circuits can be found in the fields of low-power computation, cryptography, communications, digital signal processing, and the emerging field of quantum computation. Furthermore, prototype circuits for low-power…

This is the first work to report on inferential testing at scale in industry. Specifically, it reports the experience of automated testing of integrity systems at Meta. We built an internal tool called ALPACAS for automated inference of…

Automated test generation is essential for software quality assurance, with coverage rate serving as a key metric to ensure thorough testing. Recent advancements in Large Language Models (LLMs) have shown promise in improving test…

Change-based testing is a key component of continuous integration at Facebook. However, a large number of tests coupled with a high rate of changes committed to our monolithic repository make it infeasible to run all potentially-impacted…

Online reviews in the form of user-generated content (UGC) significantly impact consumer decision-making. However, the pervasive issue of not only human fake content but also machine-generated content challenges UGC's reliability. Recent…

A key challenge in formal verification, particularly in Model Checking, is ensuring the correctness of the verification tools. Erroneous results on complex models can be difficult to detect, yet a high level of confidence in the outcome is…

Machine learning approaches applied to NLP are often evaluated by summarizing their performance in a single number, for example accuracy. Since most test sets are constructed as an i.i.d. sample from the overall data, this approach overly…

Model based diagnosis finds a growing range of practical applications, and significant performance-wise improvements have been achieved in recent years. Some of these improvements result from formulating the problem with maximum…

Multithreaded software is typically built with specialized concurrent objects like atomic integers, queues, and maps. These objects' methods are designed to behave according to certain consistency criteria like atomicity, despite being…