Pushing the Limits: Creative Solutions to Stubborn JavaScript Problems

JavaScript is full of deceptively simple problems that become surprisingly hard at scale. This post collects a set of stubborn JavaScript challenges and shows creative, practical solutions that often combine language features in interesting ways.

For each problem you’ll get a concise description, a creative solution, example code, and notes on trade-offs and browser support.

1) Event delegation that survives dynamic content and Shadow DOM

Problem: You want one listener on a container to handle clicks on dynamically added items - but some items live in a shadow DOM or deeper composed trees, and event.target doesn’t always reflect the element you care about.

Creative solution: Use event delegation with event.composedPath() (which crosses shadow boundaries) and a helper that walks the composed path for a matching selector. Fall back to a manual capturing strategy if composedPath isn’t available.

Example:

function delegate(root, selector, eventName, handler, options) {
  root.addEventListener(
    eventName,
    e => {
      const path = e.composedPath ? e.composedPath() : composedPathFallback(e);
      for (const node of path) {
        if (!node || node === root || node === document) break;
        if (node.nodeType === 1 && node.matches && node.matches(selector)) {
          handler.call(node, e);
          break;
        }
      }
    },
    options
  );
}

function composedPathFallback(e) {
  const path = [];
  let node = e.target;
  while (node) {
    path.push(node);
    node = node.parentNode || node.host; // shadow fallback
  }
  path.push(window);
  return path;
}

// Usage
delegate(document.body, '.todo .remove', 'click', e => {
  console.log('remove', this); // this === matched element
});

Notes: composedPath is supported in modern browsers; fallback helps older environments. Works across shadow DOM boundaries and for dynamically inserted nodes.

References: MDN on Event.composedPath - https://developer.mozilla.org/en-US/docs/Web/API/Event/composedPath

2) Debouncing/throttling across component instances

Problem: You have many instances of a widget that all call the same expensive operation (e.g., auto-save). Individual debouncing on each instance still floods the backend if many instances trigger simultaneously.

Creative solution: Maintain a global registry keyed by resource or operation. Debounce per resource instead of per-instance. Use a Map or WeakMap to avoid leaks.

Example:

const debounceRegistry = new Map();

function debounceGlobal(key, fn, wait = 300) {
  if (!debounceRegistry.has(key)) {
    debounceRegistry.set(key, { timer: null, lastArgs: null });
  }
  const entry = debounceRegistry.get(key);
  return function (...args) {
    entry.lastArgs = args;
    clearTimeout(entry.timer);
    entry.timer = setTimeout(() => {
      fn(...entry.lastArgs);
      entry.timer = null;
    }, wait);
  };
}

// Usage: multiple components call saveDraft('doc-123') but only one network call occurs
const debouncedSave = debounceGlobal('save-doc-123', data => sendSave(data));

// Component A/B/C can all call:
debouncedSave({ content: '...' });

Notes: Keys can be strings, Symbols, or objects (via WeakMap). Good for rate-limiting shared resources.

3) Cancel arbitrary async tasks (not just fetch)

Problem: fetch supports AbortController, but what about custom promises or chained async operations? How do you cancel a task cleanly?

Creative solution: Use an AbortController as a cancellation token and race the primary promise against an abort promise. Also provide helpers that wire the abort signal into your async flows.

Example:

function cancellable(promiseFactory, signal) {
  if (signal && signal.aborted)
    return Promise.reject(new DOMException('Aborted', 'AbortError'));
  return new Promise((resolve, reject) => {
    const onAbort = () => reject(new DOMException('Aborted', 'AbortError'));
    signal && signal.addEventListener('abort', onAbort);

    Promise.resolve()
      .then(() => promiseFactory(signal))
      .then(resolve, reject)
      .finally(() => signal && signal.removeEventListener('abort', onAbort));
  });
}

// Example async job that knows about signal
async function heavyComputation(signal) {
  for (let i = 0; i < 1e9; i++) {
    if (signal && signal.aborted)
      throw new DOMException('Aborted', 'AbortError');
    // chunked work ...
    if (i % 1e6 === 0) await Promise.resolve();
  }
  return 'done';
}

const ac = new AbortController();
cancellable(() => heavyComputation(ac.signal), ac.signal)
  .then(console.log)
  .catch(err => console.log('cancelled', err));

// later
ac.abort();

Notes: Truly cancelling CPU work requires cooperation from the work itself (periodic checks for signal.aborted), or offloading to a Web Worker where you can terminate the worker.

References: AbortController - https://developer.mozilla.org/en-US/docs/Web/API/AbortController

4) Deep cloning complex structures (cycles, dates, buffers, functions?)

Problem: JSON can’t handle Dates, Maps, Sets, cyclical graphs, or functions. You need a clone that preserves as much as possible.

Creative solution: Prefer the native structuredClone (fast and handles cycles, many built-ins). For environments without it, use MessageChannel-based structured cloning in a worker-like way. For functions, decide on a serialization policy (often better to keep functions out of data, but if necessary, tag and resurrect them explicitly).

Example:

async function smartClone(value) {
  if (typeof structuredClone === 'function') return structuredClone(value);
  // fallback using MessageChannel
  return new Promise((resolve, reject) => {
    const { port1, port2 } = new MessageChannel();
    port1.onmessage = e => resolve(e.data);
    port2.postMessage(value);
  });
}

// Usage
const original = { date: new Date(), map: new Map([[1, 'a']]) };
smartClone(original).then(clone => {
  console.log(clone.date instanceof Date, clone.map instanceof Map);
});

If you must serialize functions (rare in data exchange), store them as source strings with a safety policy, then reconstruct with new Function(...) in a controlled environment.

References: structuredClone - https://developer.mozilla.org/en-US/docs/Web/API/structuredClone

5) Memory leaks from closures and DOM references

Problem: Long-lived closures accidentally retain DOM nodes or heavy graphs (event listeners, timers), causing leaks in single-page apps.

Creative solution: Use WeakRef and FinalizationRegistry for some advanced cleanup scenarios and use a MutationObserver to detect node removal and automatically cleanup listeners. Also prefer WeakMap/WeakSet for caches tied to nodes.

Example:

// attach handler with automatic cleanup when node is removed from DOM
function attachSmart(el, event, handler) {
  el.addEventListener(event, handler);
  const mo = new MutationObserver((mutations, obs) => {
    if (!document.contains(el)) {
      el.removeEventListener(event, handler);
      obs.disconnect();
    }
  });
  mo.observe(document, { childList: true, subtree: true });
}

// Advanced: weak cache keyed by node
const nodeData = new WeakMap();
function setNodeData(node, data) {
  nodeData.set(node, data); // doesn't prevent GC when node is gone
}

Notes: WeakRef/FinalizationRegistry are powerful but subtle; their timing is non-deterministic. Prefer explicit lifecycle management when possible.

References: WeakRef - https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/WeakRef

6) Scheduling heavy CPU work without blocking the UI

Problem: Large synchronous loops or recursion freeze the UI and cause jank.

Creative solution: Chunk the work and yield back to the event loop between chunks. Use requestIdleCallback where available, and fallback to MessageChannel microtask-based scheduling for responsive slicing. For real parallelism, use Web Workers.

Example (chunking with requestIdleCallback fallback):

const schedule =
  window.requestIdleCallback ||
  (cb => setTimeout(() => cb({ timeRemaining: () => 50 }), 0));

function processLargeArray(items, processItem, onDone) {
  let i = 0;
  function work(deadline) {
    while (i < items.length && deadline.timeRemaining() > 1) {
      processItem(items[i++]);
    }
    if (i < items.length) schedule(work);
    else onDone();
  }
  schedule(work);
}

Alternative microtask-based trampoline using MessageChannel for lower latency when you need immediate chunking.

References: requestIdleCallback - https://developer.mozilla.org/en-US/docs/Web/API/Window/requestIdleCallback

7) Deterministic hashing of objects for change detection

Problem: JSON.stringify is non-deterministic for key order and can’t handle cycles; you want a stable hash to detect changes in large objects.

Creative solution: Implement a stable serialization with sorted keys and cycle handling, then hash using the Web Crypto API (crypto.subtle.digest) to produce a compact fingerprint.

Example:

function stableStringify(obj) {
  const seen = new WeakSet();
  function helper(value) {
    if (value && typeof value === 'object') {
      if (seen.has(value)) return '"__cycle__"';
      seen.add(value);
      if (Array.isArray(value)) return '[' + value.map(helper).join(',') + ']';
      const keys = Object.keys(value).sort();
      return (
        '{' +
        keys.map(k => JSON.stringify(k) + ':' + helper(value[k])).join(',') +
        '}'
      );
    }
    return JSON.stringify(value);
  }
  return helper(obj);
}

async function hashObject(obj) {
  const s = stableStringify(obj);
  const buf = new TextEncoder().encode(s);
  const digest = await crypto.subtle.digest('SHA-256', buf);
  return Array.from(new Uint8Array(digest))
    .map(b => b.toString(16).padStart(2, '0'))
    .join('');
}

Notes: This is robust for change detection. For very large objects you may want incremental hashing or persistent caching.

References: SubtleCrypto.digest - https://developer.mozilla.org/en-US/docs/Web/API/SubtleCrypto/digest

8) Build a tiny reactive system with Proxy (no framework)

Problem: You want reactivity with memoized updates and batched notification without pulling in a framework.

Creative solution: Use Proxy to intercept gets/sets, track dependencies, and schedule batched updates with a microtask queue. This is the core idea behind modern reactivity systems.

Example (minimal):

function reactive(obj) {
  const subs = new Set();
  const queue = new Set();
  let scheduled = false;

  function scheduleFlush() {
    if (scheduled) return;
    scheduled = true;
    Promise.resolve().then(() => {
      for (const fn of queue) fn();
      queue.clear();
      scheduled = false;
    });
  }

  const proxy = new Proxy(obj, {
    get(target, key) {
      // in a full system we'd track which effect is active
      return Reflect.get(target, key);
    },
    set(target, key, value) {
      const res = Reflect.set(target, key, value);
      for (const sub of subs) {
        queue.add(sub);
      }
      scheduleFlush();
      return res;
    },
  });

  return {
    proxy,
    subscribe(fn) {
      subs.add(fn);
      return () => subs.delete(fn);
    },
  };
}

// Usage
const { proxy: state, subscribe } = reactive({ count: 0 });
subscribe(() => console.log('render', state.count));
state.count++;
state.count++;
// render logs once with final value due to batching

Notes: This minimal example omits dependency tracking; real systems record which properties each effect uses to avoid over-updating. Still, it demonstrates how Proxy + microtask batching yields high-impact results.

References: Proxy - https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Proxy

9) Optimistic UI with robust retry and rollback

Problem: You want snappy UIs that assume success (optimistic updates) but must roll back cleanly when the server rejects or network fails.

Creative solution: Apply changes locally, enqueue the network operation in a durable queue, and provide a compensation (rollback) callback. Retry with exponential backoff and escalate failures to a visible error state.

Example pattern:

const queue = [];
let working = false;

async function processQueue() {
  if (working) return;
  working = true;
  while (queue.length) {
    const { op, rollback, attempts = 0 } = queue[0];
    try {
      await op(); // send to server
      queue.shift();
    } catch (err) {
      if (attempts > 3) {
        // permanent failure: revert locally and notify
        rollback();
        queue.shift();
      } else {
        // exponential backoff
        queue[0].attempts = attempts + 1;
        await new Promise(r => setTimeout(r, 200 * Math.pow(2, attempts)));
      }
    }
  }
  working = false;
}

// when user edits
applyLocalChange();
queue.push({
  op: () => sendToServer(data),
  rollback: () => revertLocalChange(),
});
processQueue();

Notes: Persist the queue to IndexedDB for resilience across page reloads.

10) Avoid stack-overflow in deep recursion with trampolining

Problem: Deep recursive algorithms blow the stack in JS (no tail-call optimization reliably available).

Creative solution: Transform recursion into an explicit stack and use a trampoline (a loop that iteratively executes thunk functions). This lets you express recursion ergonomically while executing iteratively.

Example:

function trampoline(fn) {
  return function trampolined(...args) {
    let result = fn.apply(this, args);
    while (typeof result === 'function') {
      result = result();
    }
    return result;
  };
}

function factThunk(n, acc = 1) {
  if (n === 0) return acc;
  return () => factThunk(n - 1, n * acc);
}

const factorial = trampoline(factThunk);
console.log(factorial(10000)); // no stack overflow

Notes: Trampolining is useful for functional-style recursion where you can return thunks instead of recursing directly.

Final thoughts: Think in layers and design for cooperative cancellation and observability

Many “stubborn” bugs or performance problems become manageable when you separate concerns:

Decouple work (UI vs CPU-heavy) via scheduling or workers.
Use cancellation tokens (AbortController) for long-running tasks and wire them through your async stack.
Prefer weak references for caches tied to DOM or short-lived objects.
Use native primitives like structuredClone, crypto, and Proxy where available - but provide pragmatic fallbacks.

The best creative solutions often combine multiple small language features into a dependable pattern: a WeakMap cache + a MutationObserver to clean up, a Promise-microtask batching strategy alongside Proxy-based reactivity, or an AbortController wired through fetch and custom promises. Try to make cancellation, cleanup, and observability first-class in your architecture - it pays off as projects scale.