Java engineer interview - volatile keyword

In Go, range is used to iterate over data types and return corresponding values: 1. For slices and arrays, range returns index and element copy; 2. Unwanted indexes or values can be ignored using _; 3. For maps, range returns keys and values, but the iteration order is not fixed; 4. For strings, range returns rune index and characters (rune type), supporting Unicode; 5. For channels, range continues to read values until the channel is closed, and only a single element is returned. Using range can avoid manually managing indexes, making iteratives simpler and safer.

Use meaningful naming: variables such as intdaysSinceModification; methods such as getUserRolesByUsername() to make the code intention clear; 2. Functions should be small and do only one thing: for example, createUser() is split into single responsibility methods such as validateRequest() and mapToUser(); 3. Reduce comments and write self-interpretation code: Use userHasPrivilegedAccess() instead of redundant comments; 4. Handle errors elegantly: do not ignore exceptions, use try-with-resources to automatically manage resources; 5. Follow the "Boy Scout Rules": optimize variables every time you modify

There is an essential difference between JavaScript's WebWorkers and JavaThreads in concurrent processing. 1. JavaScript adopts a single-thread model. WebWorkers is an independent thread provided by the browser. It is suitable for performing time-consuming tasks that do not block the UI, but cannot operate the DOM; 2. Java supports real multithreading from the language level, created through the Thread class, suitable for complex concurrent logic and server-side processing; 3. WebWorkers use postMessage() to communicate with the main thread, which is highly secure and isolated; Java threads can share memory, so synchronization issues need to be paid attention to; 4. WebWorkers are more suitable for front-end parallel computing, such as image processing, and

The single responsibility principle (SRP) requires a class to be responsible for only one function, such as separating the saving and mail sending in order processing; 2. The opening and closing principle (OCP) requires opening and closing for extensions and closing for modifications, such as adding new graphics without modifying the calculator; 3. The Richter replacement principle (LSP) requires that subclasses can replace the parent class without destroying the program, such as using independent classes to avoid behavior abnormalities caused by square inheritance rectangles; 4. The interface isolation principle (ISP) requires that clients should not rely on unwanted interfaces, such as splitting the multi-function device interface to independent printing, scanning, and fax interfaces; 5. The dependency inversion principle (DIP) requires that high-level modules do not rely on low-level modules, and both rely on abstraction, such as OrderService depends on Data

Use subprocess.run() to safely execute shell commands and capture output. It is recommended to pass parameters in lists to avoid injection risks; 2. When shell characteristics are required, you can set shell=True, but beware of command injection; 3. Use subprocess.Popen to realize real-time output processing; 4. Set check=True to throw exceptions when the command fails; 5. You can directly call chains to obtain output in a simple scenario; you should give priority to subprocess.run() in daily life to avoid using os.system() or deprecated modules. The above methods override the core usage of executing shell commands in Python.

GraphQL can be easily integrated in SpringBoot through official support. 1. Use spring-boot-starter-graphql to add dependencies; 2. Define the schema.graphqls file under resources to declare Query and Mutation; 3. Use @Controller to cooperate with @QueryMapping and @MutationMapping to achieve data acquisition; 4. Enable GraphiQL interface testing API; 5. Follow best practices such as input verification, N 1 query prevention, security control, etc., and ultimately implement a flexible and efficient client-driven API.

ProjectLoomintroducesvirtualthreadstosolveJava’sconcurrencylimitationsbyenablinglightweight,scalablethreading.1.VirtualthreadsareJVM-managed,low-footprintthreadsthatallowmillionsofconcurrentthreadswithminimalOSresources.2.Theysimplifyhigh-concurrency

To remove duplicate elements in Python list, 1. Use set(): It is suitable for situations where elements are immutable and do not care about order. The syntax is list(set(original_list)), but it will disrupt the original order; 2. Use dict.fromkeys(): The recommended method is suitable for Python 3.7, which can maintain the order of the first occurrence of elements. The syntax is list(dict.fromkeys(original_list)), and the code is concise and efficient; 3. Use list deduction and seed collection: It is suitable for scenarios where custom deduplication logic is required. By traversing the list and recording the seen elements with the set, ensuring uniqueness; 4. Handling non-hashable types such as