ArticleslgStudy

computer science

Ostrich algorithm

Ostrich algorithm 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 Ostrich algorithm rather than just read about it. In short: In computer science, the ostrich algorithm is a strategy of ignoring potential problems on the basis that they may be exceedingly rare. It is named after the ostrich effect which is defined as "to stick one's head in the sand and pretend there is no problem".

Key takeaways

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

Reference excerpt

In computer science, the ostrich algorithm is a strategy of ignoring potential problems on the basis that they may be exceedingly rare. It is named after the ostrich effect which is defined as "to stick one's head in the sand and pretend there is no problem". It is used when it appears the situation may be more cost-effectively managed by allowing the problem to continue to occur rather than to attempt its prevention.

Use with deadlocks This approach may be used in dealing with deadlocks in concurrent programming if they are believed to be very rare and the cost of detection or prevention is high. A set of processes is deadlocked if each process in the set is waiting for an event that only another process in the set can cause. The ostrich algorithm pretends there is no problem and is reasonable to use if deadlocks occur very rarely and the cost of their prevention would be high. The UNIX and Windows operating systems take this approach. Although using the ostrich algorithm is one of the methods of dealing with deadlocks, other effective methods exist such as dynamic avoidance, banker's algorithm, detection and recovery, and prevention.

See also Crash-only software End-to-end principle

References

External links Ostrich algorithm Non-Hard Locking Read-Write Locker Archived 2011-12-18 at the Wayback Machine Deadlock Basics + Modelling + Ostrich Algorithm

Worked examples

Example 1 — a first encounter with Ostrich algorithm

Start with the simplest possible case. Write down what Ostrich algorithm 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 Ostrich algorithm 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 Ostrich algorithm 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 Ostrich algorithm

In research
Ostrich algorithm 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 Ostrich algorithm 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
Ostrich algorithm is common in secondary-school and first-year university syllabi. It links to neighbouring topics Concurrent algorithms, so understanding it makes those chapters shorter.
In everyday life
Look for Ostrich algorithm 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 Ostrich algorithm in 20 minutes

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

Frequently asked questions

What is Ostrich algorithm in simple terms?

In computer science, the ostrich algorithm is a strategy of ignoring potential problems on the basis that they may be exceedingly rare. It is named after the ostrich effect which is defined as "to stick one's head in the sand and pretend there is no problem".

Why does Ostrich algorithm 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 Ostrich algorithm?

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 Ostrich algorithm.

Tags

  • Concurrent algorithms

Keep exploring