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   "source": "# Algorithms\n\n<!-- chapter-intro -->\n\nAn algorithm is a step-by-step procedure for solving a problem. This chapter covers the two most fundamental algorithmic tasks — **searching** and **sorting** — and the mathematical framework used to compare their efficiency."
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   "source": "<h2>Why this chapter matters</h2>\n\nKnowing an algorithm's behavior under different inputs separates guessing from engineering:\n\n- linear search is simple but slow for large sorted data\n- binary search cuts the problem in half with every comparison\n- sorting algorithms trade simplicity for speed depending on input size\n- Big-O notation gives a hardware-independent language for comparing algorithms"
  },
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   "source": "<h2>Learning goals</h2>\n\nBy the end of this chapter, you should be able to:\n\n- implement and compare linear and binary search\n- trace through bubble, selection, and insertion sort\n- explain what O(N), O(N log N), and O(N²) mean\n- measure and interpret actual runtime performance\n\n<h2>Chapter flow</h2>\n\n```{tableofcontents}\n```\n"
  }
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