Algorithms provide computers with a series of instructions that transform data into usable knowledge. Every algorithm is essentially trying to make a decision, often as part of a series of decisions, to ensure a computational input is processed and transmitted as usable data based on the task it’s trying to accomplish.
Algorithm Definition
An algorithm is a series of step-by-step instructions designed to solve a problem or complete a calculation. These instructions must be followed in a specific order to convert input data into the intended output data, making algorithms ideal for addressing repetitive tasks.
What Is an Algorithm?
An algorithm is a series of commands that are executed to solve a problem or complete a calculation. Algorithms consist of step-by-step instructions that must be performed in a particular order to process input data and convert it into the desired output data. As a result, an algorithm isn’t the same thing as a line of code or a software program — it’s basic logic designed to handle a repetitive task.
Data scientists, computer programmers and other technical personnel often build algorithms to solve simple problems like sorting numbers and removing or adding data points. However, algorithms are also key to automation and serve as the foundation for more complex technologies like artificial intelligence.
How Does an Algorithm Work?
An algorithm consists of a series of three steps: the input, the computation and the output.
- An input is the data that is fed into an algorithm to begin the computation process.
- The computation process then applies arithmetic, decision making and repetition to create “if x, then y” equations to ensure only the proper data is fed through to the output. Many algorithms use machine learning to use past knowledge in computational decision-making.
- The output process is the algorithm’s expression of its conclusion. This can be in the form of information displayed to a user, or much more commonly, as more data that becomes the input for another algorithm in a string of processes that enable a computer to make complex decisions in real time.
Types of Algorithms
Different algorithms are designed to handle various tasks. Below are some of the more common types of algorithms:
- Brute force algorithm: Blindly attempts all possible solutions in the hopes of finding a solution to a problem.
- Searching algorithm: Locate specific data points within structured and unstructured data, making it easier to find information.
- Sorting algorithm: Organize data points in a data set in a particular order or according to other criteria like numerical order.
- Encryption algorithm: Secures data by transforming it into an indecipherable format using cryptography.
- Hashing algorithm: Converts data into a string of letters and numbers that’s fixed in length to protect the data.
- Recursive algorithm: Breaks a problem into smaller parts and calls itself repeatedly until it solves each subproblem.
- Greedy algorithm: Seeks the optimal local solution for each part, working toward a global solution one part at a time.
- Backtracking algorithm: Uses a trial-and-error approach to explore all possible solutions, retracing steps whenever a solution fails.
- Divide and conquer algorithm: Breaks down a problem into subproblems, solves each subproblem and combines these solutions to create an overall solution.
- Dynamic programming algorithm: Breaks a problem into subproblems, solves them and stores the results to avoid repeating the same calculations.
- Randomized algorithm: Incorporates randomness into its logic, finding an approximate solution for a problem.
Real-Life Examples of Algorithms
Algorithms are used in a range of high-tech applications that are now a part of everyday life.
Traffic Lights
Traffic lights use algorithms that compile data via sensors to regulate the flow of traffic at intersections. Instead of changing colors randomly, traffic lights monitor the volume of vehicles and time light changes to ensure vehicles can perform movements safely.
GPS Systems
Algorithms in GPS systems use satellites to pinpoint the exact coordinates of a user. In addition, these algorithms use this same approach to gather real-time data on road and traffic conditions, so they can provide an accurate estimate of travel time.
Bus Schedules
Algorithms consider numerous factors when planning bus routes, including time, fuel capacity and student addresses. Computing how long it takes to reach each address, they establish pickup times to create the most efficient routes possible.
Search Engines
Search engines use algorithms that rank articles according to specific criteria when users submit queries. For example, algorithms may analyze the date an article was published and the quality of the sources it references to calculate its ranking.
E-Commerce Sites
E-commerce sites employ algorithms that analyze items you’ve viewed or purchased before to predict what items you’re likely to buy or show interest in. Sites can then make personalized shopping recommendations.
Facial Recognition
Phones equipped with facial recognition compile data on a user’s facial features. When a user attempts to unlock their phone via facial recognition, algorithms search a database of faces and permit access only if they find a match.
What Is the Best Way to Analyze an Algorithm?
To ensure an algorithm is as efficient as possible, there are a few methods of analysis that check execution speed and memory usage across several use cases.
Algorithm analysis begins with counting the number of operations needed to determine an answer across different input variables. For example, a linear search algorithm will check every value on a given list to see if it matches the target value. Once the value is found, it immediately returns to the index. If no value is found, the equation returns -1. The number of checks necessary to find the target value will determine the algorithm’s execution speed. This speed will vary depending on the target value and the values present in the list, so several values should be checked to determine a relative average speed.
Other variables are necessary to determine the actual running speed of an algorithm, such as the speed of the computer, the programming language and the translation of that language into machine code. To accurately measure how an algorithm will run on a particular device, it must be made to run. This is possible by implementing the algorithm in an actual programming language, and in JavaScript, using the searchList function. This function will tell the amount of time it takes an algorithm to search a specific length of numbers in a list in milliseconds. Measuring the efficiency of different types of algorithms for a given set of values makes it possible to determine the best algorithm for specific use cases.
Frequently Asked Questions
How are algorithms used in real life?
Algorithms are used to help traffic lights regulate traffic flow, GPS systems calculate travel times, e-commerce sites make personalized recommendations based on purchase history and phone facial recognition technology find a face match.
What is the simplest algorithm?
The brute force algorithm is known as the simplest algorithm. It looks for the solution to a problem by blindly testing every solution possible.
What is the most common algorithm?
Some of the most common types of algorithms include searching algorithms, sorting algorithms and divide and conquer algorithms.
What is an example of an algorithm?
One of the most basic examples of an algorithm is a cooking recipe. Like an algorithm, a recipe consists of instructions that must be completed in order and one step at a time. The goal of a recipe is to produce the same result each time, so the process is repeatable.
