{
  "id": 8041276,
  "title": "A Decision Trace Must Distinguish False From Missing",
  "url": "https://urgent.news/2026/09/17/a-decision-trace-must-distinguish-false-from-missing",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-17T14:53:19.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/stratcorealpha/a-decision-trace-must-distinguish-false-from-missing-2nci"
  },
  "original_language": "en",
  "account": null,
  "summary": "The article discusses the importance of distinguishing between false observations and missing data in decision traces for trading engines. It emphasizes the need to preserve inputs that actually existed at decision time, including explicit false values, rather than treating missing data as if it were a false result. The author suggests that a system should give explicit status and reason to unavailable observations, rather than validating a boolean with if (!value). The article also provides a code example demonstrating how to preserve and validate the necessary information for decision traces, using Node's built-in test runner.",
  "key_points": [],
  "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."
}