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computer science

Jump search

Jump search is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Jump search rather than just read about it. In short: In computer science, a jump search or block search refers to a search algorithm for ordered lists. It works by first checking all items Lkm, where k ∈ N {\displaystyle k\in \mathbb {N} } and m is the block size, until an item is found that is larger than the search key.

Key takeaways

  • Jump search belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Jump search to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Jump search from memory before moving on to harder problems.

Reference excerpt

In computer science, a jump search or block search refers to a search algorithm for ordered lists. It works by first checking all items Lkm, where k ∈ N {\displaystyle k\in \mathbb {N} } and m is the block size, until an item is found that is larger than the search key. To find the exact position of the search key in the list a linear search is performed on the sublist L[(k-1)m, km]. The optimal value of m is √n, where n is the length of the list L. Because both steps of the algorithm look at, at most, √n items the algorithm runs in O(√n) time. This is better than a linear search, but worse than a binary search. The advantage over the latter is that a jump search only needs to jump backwards once, while a binary can jump backwards up to log n times. This can be important if jumping backwards takes significantly more time than jumping forward. The algorithm can be modified by performing multiple levels of jump search on the sublists, before finally performing the linear search. For a k-level jump search the optimum block size ml for the l th level (counting from 1) is n(k-l)/k. The modified algorithm will perform k backward jumps and runs in O(kn1/(k+1)) time.

Implementation algorithm JumpSearch is input: An ordered list L, its length n and a search key s. output: The position of s in L, or nothing if s is not in L. a ← 0 b ← ⌊√n⌋ while Lmin(b,n)-1 < s do a ← b b ← b + ⌊√n⌋ if a ≥ n then return nothing while La < s do a ← a + 1 if a = min(b, n) return nothing if La = s then return a else return nothing

See also Jump point search Skip list Interpolation search Linear search - runs in O(n) time, only looks forward Binary search - runs in O(log n) time, looks both forward and backward

References This article incorporates public domain material from Paul E. Black. "jump search". Dictionary of Algorithms and Data Structures. NIST. Ben Shneiderman, Jump Searching: A Fast Sequential Search Technique, CACM, 21(10):831-834, October 1978.

Worked examples

Example 1 — a first encounter with Jump search

Start with the simplest possible case. Write down what Jump search claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Jump search before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Jump search ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Jump search

In research
Jump search appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Jump search in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Jump search is common in secondary-school and first-year university syllabi. It links to neighbouring topics Search algorithms, so understanding it makes those chapters shorter.
In everyday life
Look for Jump search outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Jump search in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Jump search means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Jump search out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Jump search in simple terms?

In computer science, a jump search or block search refers to a search algorithm for ordered lists. It works by first checking all items Lkm, where k ∈ N {\displaystyle k\in \mathbb {N} } and m is the block size, until an item is found that is larger than the search key.

Why does Jump search matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Jump search?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Jump search.

Tags

  • Search algorithms

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