ArticleslgStudy

computer science

Internal sort

Internal sort 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 Internal sort rather than just read about it. In short: An internal sort is any data sorting process that takes place entirely within the main memory of a computer. This is possible whenever the data to be sorted is small enough to be completely held in the main memory.

Key takeaways

  • Internal sort 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 Internal sort to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Internal sort from memory before moving on to harder problems.

Reference excerpt

An internal sort is any data sorting process that takes place entirely within the main memory of a computer. This is possible whenever the data to be sorted is small enough to be completely held in the main memory. The opposite of an internal sort is an external sort, where the data is partially or completely held on external media such as a hard disk. Any reading or writing of data to and from this slower media can slow the sort process considerably. This issue has implications for different sort algorithms. Some common internal sorting algorithms include:

Bubble Sort Insertion Sort Quick Sort Heap Sort Radix Sort Selection sort Consider a Bubblesort, where adjacent records are swapped in order to get them into the right order, so that records appear to “bubble” up and down through the dataspace. If this has to be done in chunks, then when we have sorted all the records in chunk 1, we move on to chunk 2, but we find that some of the records in chunk 1 need to “bubble through” chunk 2, and vice versa (i.e., there are records in chunk 2 that belong in chunk 1, and records in chunk 1 that belong in chunk 2 or later chunks). This will cause the chunks to be read and written back to disk many times as records cross over the boundaries between them, resulting in a considerable degradation of performance. If the data can all be held in memory as one large chunk, then this performance hit is avoided. On the other hand, some algorithms handle external sorting rather better. A Merge sort breaks the data up into chunks, sorts the chunks by some other algorithm, such as bubblesort or Quick Sort, and then recombines the chunks two by two so that each recombined chunk is in order. This approach minimizes the number or reads and writes of data-chunks from disk, and is a popular external sort method.

References

Worked examples

Example 1 — a first encounter with Internal sort

Start with the simplest possible case. Write down what Internal sort 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 Internal sort 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 Internal sort 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 Internal sort

In research
Internal sort 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 Internal sort 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
Internal sort is common in secondary-school and first-year university syllabi. It links to neighbouring topics Sorting algorithms, so understanding it makes those chapters shorter.
In everyday life
Look for Internal sort 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.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Internal sort in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Internal sort 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 Internal sort out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Internal sort in simple terms?

An internal sort is any data sorting process that takes place entirely within the main memory of a computer. This is possible whenever the data to be sorted is small enough to be completely held in the main memory.

Why does Internal sort 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 Internal sort?

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 Internal sort.

Tags

  • Sorting algorithms

Keep exploring