Making the user bear the mistake ("Your input format is incorrect, check it yourself")

This text sarcastically enumerates a series of poor user input validation practices, including directly blaming users for errors, providing vague prompts, displaying all errors at once, failing to auto-focus, imposing strict formatting restrictions, ignoring case sensitivity, disabling paste functionality, not saving input history, using technical jargon, neglecting mobile compatibility, lacking real-time validation, disregarding assistive technologies, applying inconsistent handling methods, and failing to log errors. These practices completely disregard user experience, shifting all responsibility onto users and reflecting an utterly irresponsible design attitude.

Reject logs ("console printing is enough")

Logging systems are often regarded as a guarantee of code maintainability, but some argue that console logging (console.log) is sufficient—debugging can be done by directly inspecting variable values, and future maintenance issues can be left to others. Logging systems require complex features like design-level error classification and persistent storage, whereas console.log only needs one line of code to output information. When users report issues, simply ask them to check the console logs. Log levels (e.g., warn, error, info) are considered redundant, as console.log can express all intentions. Persistent storage is seen as unnecessary—console records are enough, and users can take screenshots to share. Context can be replaced with comments. Production environment logs are recommended for deletion to avoid performance issues. Log searching can be done with browser Ctrl+F. Logging for async operations depends on luck. Sensitive information can be printed directly for debugging convenience. Cross-file logging can use global variables. Performance monitoring can be done manually by calculating time spent. Logging standards need no restrictions—freestyle is encouraged. If colleagues don’t understand, blame it on their lack of imagination.

Random try-catch (some places have 'try-catch', others just crash)

This passage humorously and sarcastically describes various pitfalls and anti-patterns in software development error handling, including: randomly placing try-catch blocks leading to unpredictability; selectively catching errors while ignoring critical issues; nesting multiple layers of try-catch creating complex structures; silently swallowing errors to mask problems; mixing multiple error-handling approaches that increase confusion; catching without actually addressing issues; over-catching irrelevant code; lumping all error types together; neglecting asynchronous error handling; relying on global error handling that loses context; ignoring runtime errors in TypeScript; using comments as a substitute for actual handling; omitting necessary handling for performance reasons; shifting error responsibility to callers; implementing business logic with try-catch increasing complexity; continuing execution after catching leading to accumulated issues; overlooking error object details; losing original error information in layers of abstraction. Together, these practices form inefficient and hard-to-maintain error-handling approaches.

Not testing boundary conditions (empty array? 'undefined'? non-existent?)

This passage satirically showcases common error-prone practices and dangerous assumptions in programming. The author lists a series of poor coding habits, such as performing array operations without checking length, accessing object properties without existence checks, never validating function parameters, ignoring failure scenarios in asynchronous operations, using magic numbers without comments, recklessly employing global variables, neglecting browser compatibility, relying on loose comparisons, modifying the DOM without checking element existence, and failing to clean up timers and event listeners. Through exaggerated counterexamples, it reveals the severe consequences these practices may cause in real-world development, reminding developers to prioritize defensive programming and avoid writing fragile code. The text employs dark humor, ostensibly praising these hazardous approaches while sharply criticizing irresponsible programming attitudes.

Ignore browser compatibility ("If it runs on my computer, it's fine").

Ignoring browser compatibility can cause code to fail on others' devices or in the future. Testing only on the latest Chrome ignores older versions or other browsers, leading to errors. Disregarding CSS prefixes and experimental features breaks layouts in some browsers. Assuming all users have modern hardware causes poor performance on low-end devices. Relying on non-standardized DOM APIs makes code unusable in other browsers. Neglecting internationalization results in incorrect font or date formatting. Using deprecated APIs guarantees failure in future versions. Failing to handle browser differences renders features unusable in certain browsers. Extreme cases like UserAgent sniffing often misclassify browsers. Overlooking ES module compatibility causes direct errors in older browsers. Ignoring mobile optimization makes the experience unusable on mobile devices. Writing code dependent on current browser implementation details ensures future breakage.

Over-trusting APIs (directly accessing 'data.user.list[0].name' without null checks)

In front-end development, directly accessing deeply nested API data without null checks is extremely dangerous and can easily cause page crashes. The structure of API responses may change, and the backend might return null or undefined, or even omit fields entirely. Typical problematic code directly accesses the deepest-level data, creating multiple potential crash points. In real-world scenarios, empty arrays, renamed fields, or unexpected null values can all lead to disasters. Chained operations suffer from poor readability. Modern solutions include optional chaining, destructuring with default values, type guard functions, and utility libraries like Lodash for defensive programming. However, a balance must be struck—over-defensive coding can introduce its own issues. Best practices include standardizing response formats, using data transformation layers, schema validation, and shared type definitions in team collaboration. Mock testing and code review rules are also essential. Performance and security must be balanced. TypeScript can enforce type checking but should be paired with validation libraries. The philosophy of defensive programming is "trust but verify"—fail fast, define clear contracts, degrade gracefully, and ensure observability.

Silent failure (no error prompts, leaving users to guess)

Silent failure is a highly insidious trap in front-end development where code errors occur without any prompts, leaving users facing blank pages and making it difficult for developers to troubleshoot. The article lists various techniques to achieve silent failure, including ignoring error handling, using meaningless default values, swallowing console logs, and advanced methods like type coercion magic. It also introduces deeply nested silent callback hell and other tactics that make errors harder to debug. Defensive programming anti-patterns, such as over-reliance on third-party libraries, skipping unit tests, and disabling type checks, are highlighted. User-perceived silent failures, like unresponsive interactions or fake success states, are also covered. The build system’s role in aiding silent failure—such as ignoring compilation warnings, automatically deploying untested code, and disabling error monitoring—is discussed. Together, these practices form a perfect silent failure system.

Do not handle any errors ('fetch().then(data => use(data))'

This passage sarcastically lists common error-handling anti-patterns in front-end development, including: ignoring network request errors outright, failing to check response status codes, neglecting Promise rejections, skipping data format validation, overlooking edge cases, mixing async/await without error catching, globally ignoring unhandled Promise rejections, ignoring errors in callback hell, not canceling stale requests, failing to handle race conditions, omitting request timeouts, not cleaning up side effects, ignoring concurrency conflicts, not backing up unsaved data, infinitely retrying requests, disabling error monitoring, skipping log records, and disregarding user interrupt handling. These practices may appear to simplify code but actually lead to various issues like blank screens, data loss, memory leaks, severely impacting user experience and system stability.

Best practices for preventing data leaks

Front-end handling of sensitive data requires ensuring transmission and storage security. Relying solely on HTTPS is insufficient; critical data should undergo secondary encryption using the Web Crypto API for client-side encryption or real-time encryption of form fields. Input validation must strictly enforce allowlisting and dedicated validators. Browser storage of sensitive data should differentiate levels, utilizing sessionStorage with automatic clearing. Cookies must have secure attributes to prevent XSS attacks, requiring secure content rendering and CSP policy implementation. Third-party dependencies require automated checks and resource integrity validation. Error handling must filter sensitive information. Critical operations need secondary verification, and real-time monitoring should detect anomalous behavior. Front-end security demands a comprehensive approach combining encryption, validation, storage protection, and monitoring measures.

Front-end encryption storage solution

Front-end encrypted storage is crucial for preventing data breaches. Common storage methods in the browser environment, such as localStorage and cookies, are unencrypted by default and pose security risks. The Web Crypto API and third-party libraries like SJCL provide encryption solutions. A complete encrypted storage implementation includes key management, data encryption processes, and handling of special scenarios. Security enhancements cover memory cleanup and tamper-proof mechanisms. Performance optimization can be achieved through key caching and WebAssembly. Additionally, browser compatibility issues must be considered, with fallback strategies implemented via feature detection to ensure usability across different environments.