{
  "id": 19998696,
  "title": "You Never Know",
  "url": "https://urgent.news/2026/11/14/you-never-know",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-11-14T15:12:57.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/chaesang/you-never-know-4lcn"
  },
  "original_language": "en",
  "account": "After completing my master's degree on Worst Case Execution Time (WCET) analysis, I worked on improving the prediction methods, which became useful for energy consumption reduction and scaling. I built an abstract machine layer and spent time comparing systems, tackling challenges related to complex CPUs and cross-compiling. The concept of energy consumption became increasingly important as technology advanced and shifted towards mobile and embedded systems. The parallelism and growth in computational power led to exponential growth, with issues related to scaling becoming less relevant. Looking back ten years from now, it is impossible to predict what the future holds.",
  "summary": "Grad-school work on worst-case execution time — and how the same method jumped to energy, then got dwarfed by scale. You never know. A look back — long before any of the tools we argue about now. The topic I was handed as a small first-year master's student in the late 1990s was WCET — Worst Case Execution Time — analysis. Wikipedia dates the term to around 2008, but I'd inherited the project…",
  "key_points": [
    "Master's degree focused on Worst Case Execution Time (WCET) analysis",
    "Developed improved prediction methods for energy consumption reduction",
    "Anticipating future technological advancements is uncertain"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}