Management Notes

Reference Notes for Management

In size oriented metrics, metrics are developed based on the ___________________

In size oriented metrics metrics are developed based on the ___________________


A. number of functions
B. number of user inputs
C. number of lines of code

The Correct Answer Is:

  • C. number of lines of code

The correct answer is C) number of lines of code.

Why Size-Oriented Metrics are Developed Based on the Number of Lines of Code:

Size-oriented metrics, as the name suggests, are metrics that focus on measuring software size. Among the various factors that can be used to determine the size of software, the number of lines of code (LOC) is a widely used and important metric.

Here’s a detailed explanation of why size-oriented metrics are developed based on the number of lines of code, along with explanations for the other options:

C. Number of Lines of Code (LOC) (Correct):


LOC is a comprehensive measure of software size because it takes into account all the lines of code written to develop a software application. This includes code written for functions, methods, procedures, classes, libraries, and any other code artifacts that make up the software.


LOC provides a standardized and consistent way to measure software size across different programming languages and platforms. Regardless of the language used, a line of code represents a basic unit of functionality or instruction in the software.

Easy to Measure:

Counting lines of code is a straightforward and easily quantifiable process. Software developers and tools can readily determine the number of lines of code in a program, making it a practical metric for software size estimation.

Historical Data:

Many software projects have historical data on LOC, which can be used for benchmarking, estimating project effort, and assessing code complexity.

Why the Other Options are Not as Suitable:

A. Number of Functions (Not as Comprehensive):

While the number of functions is an important aspect of software design and architecture, it is not as comprehensive as LOC in measuring overall software size. Functions can vary significantly in size and complexity, making it challenging to use them as the sole basis for size-oriented metrics.

B. Number of User Inputs (Not Comprehensive and Depends on Functionality):

The number of user inputs is related to the functionality of the software, but it is not a suitable metric for measuring software size on its own. The size of user inputs alone does not account for the entirety of the software, including internal logic and code that may not directly involve user inputs.

Why Size-Oriented Metrics are Valuable:

Size-oriented metrics are valuable for several reasons, including:

Effort Estimation:

Software size metrics, such as LOC, are used to estimate the effort required to develop, test, and maintain software. By knowing the size of a project, project managers can better allocate resources and schedule tasks.

Project Planning:

Software size metrics are crucial for project planning, including setting project milestones, deadlines, and resource allocation.

Quality Assessment:

Size-oriented metrics can also help in assessing code quality. For example, higher LOC in a given module may indicate higher complexity, potentially leading to increased testing efforts.

Cost Estimation:

Software size metrics are used in cost estimation models, allowing organizations to predict the cost of software development based on its size.

Productivity Measurement:

Organizations can use size-oriented metrics to measure the productivity of their development teams over time, helping identify areas for improvement.

In conclusion, size-oriented metrics, particularly those based on the number of lines of code, provide a standardized, comprehensive, and easily measurable way to estimate the size of software. This metric is valuable for various purposes, including effort estimation, project planning, quality assessment, cost estimation, and productivity measurement.

While other factors like the number of functions and user inputs are important, they are not as comprehensive or standardized as LOC and are typically considered in conjunction with LOC and other size-oriented metrics for a more holistic assessment of software size and complexity.

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