Automated test generation has been extensively studied for dynamically compiled or typed programming languages like Java and Python. However, Go, a popular statically compiled and typed programming language for server application development, has received limited support from existing tools. To address this gap, we present NxtUnit, an automatic unit test generation tool for Go that uses random testing and is well-suited for microservice architecture. NxtUnit employs a random approach to generate unit tests quickly, making it ideal for smoke testing and providing quick quality feedback. It comes with three types of interfaces: an integrated development environment (IDE) plugin, a command-line interface (CLI), and a browser-based platform. The plugin and CLI tool allow engineers to write unit tests more efficiently, while the platform provides unit test visualization and asynchronous unit test generation. We evaluated NxtUnit by generating unit tests for 13 open-source repositories and 500 ByteDance in-house repositories, resulting in a code coverage of 20.74% for in-house repositories. We conducted a survey among Bytedance engineers and found that NxtUnit can save them 48% of the time on writing unit tests. We have made the CLI tool available at https://github.com/bytedance/nxt_unit.

A server API bug could have a huge impact on the operation of other servers and clients relying on that API, resulting in service downtime and financial losses. A common practice of server API testing inside enterprises is writing test inputs and assertions manually, and the test effectiveness depends largely on testers’ carefulness, expertise and domain knowledge. Writing test cases for complicated business scenarios with multiple and ordered API calls is also a heavy task that requires a lot of human effort. In this paper, we present the design and deployment of SIT, a fully automated server interface reliability testing platform at ByteDance that provides capabilities including (1) traffic data generation based on combinatorial testing and fuzzing, (2) scenario testing for complicated business logics and (3) automated test execution with fault localisation in a controlled environment that does not affect online services. SIT has been integrated into the source control system and is triggered when new code change is submitted or configured as scheduled tasks. During the year of 2021, SIT blocked 434 valid issues before they were introduced into the production system.