Which of the following measures are used to assess the quality of an algorithm pick 3
reusability
number lines amount of variable
time complexity
resource consumption
The three measures used to assess the quality of an algorithm are:
1. Time complexity: This measures the amount of time required by an algorithm to run, usually expressed in terms of the number of operations performed. It helps determine how efficient or fast an algorithm is.
2. Resource consumption: This measures the amount of resources (such as memory or disk space) used by an algorithm. Evaluating resource consumption helps determine how efficient an algorithm is in terms of the resources it requires.
3. Reusability: This measures the ability of an algorithm to be easily reused in different contexts or for different problem-solving scenarios. It assesses how modular and adaptable the algorithm is, allowing it to be employed in various situations without significant modifications.
Number of lines or variables is not typically considered a measure of algorithm quality, as it is more related to the code implementation rather than the algorithm itself.
The three measures used to assess the quality of an algorithm are:
1. Time complexity: It calculates how much time an algorithm takes to execute as a function of the input size. It helps determine the efficiency of an algorithm by measuring the number of operations it performs.
2. Resource consumption: It refers to the amount of system resources an algorithm utilizes, such as memory, disk space, or network bandwidth. Lower resource consumption usually indicates better performance.
3. Reusability: It assesses whether an algorithm can be reused in different contexts or easily adapted for different applications. Reusable algorithms tend to have modular design and clear separation of concerns, making them more versatile and maintainable.
The number of lines or the amount of variables in an algorithm is not typically used as a measure of its quality.
To assess the quality of an algorithm, there are several measures that can be considered. Out of the options you provided, three common measures are:
1. Time complexity: This measure evaluates how the algorithm's execution time increases with the size of the input. It helps determine how efficient the algorithm is in terms of time. Lower time complexity is generally preferred, as it means the algorithm can solve problems more quickly.
2. Resource consumption: This measure evaluates the amount of resources (such as memory, disk space, or network bandwidth) that an algorithm uses during execution. It helps determine how efficiently the algorithm utilizes system resources. Lower resource consumption is desirable, as it allows for more efficient usage of hardware and reduces costs.
3. Reusability: While not directly related to the efficiency of an algorithm, reusability is an important measure for assessing its quality. This measure evaluates how easily and effectively the algorithm can be used and adapted for different purposes or in different contexts. A reusable algorithm can save time and effort by eliminating the need to develop a new algorithm from scratch.
On the other hand, "number of lines or amount of variables" is not a commonly used measure to assess the quality of an algorithm. The number of lines of code or variables in an algorithm does not necessarily correlate with its efficiency or correctness. These factors may contribute to code readability and maintainability, but they are not key measures of algorithm quality.
To determine the quality of an algorithm in terms of time complexity, resource consumption, and reusability, you can analyze the algorithm's performance, resource usage, and code structure. Time complexity can be analyzed by evaluating the algorithm's time complexity function, while resource consumption can be measured by monitoring system resource usage during execution. Reusability can be assessed by considering factors such as modularity, flexibility, and ease of integration with other systems.