Measurement in the physical world can be e categories in two ways:
Direct measures (internal attributes)
Direct measures of the software engineering process involve cost and effort included. Analysis of the product involves lines of code produced, execution speed, memory size, and defects reported over a period of time.
Indirect message all the product include functionality, quality, complexity, efficiency, reliability, maintainability, etc. Direct measures can be easily estimated, whereas indirect measures are very hard to estimate.
Size of oriented metrics
Size of the software produced:
A line of code is every line of program text that is not a comment or a blank line, despite the number of statements or fragments of statements on the line. This particularly covers all lines containing program headers, declarations, and executable and non-executable statements.
Function Oriented metrics
Function oriented metrics are indirect measures. It focuses on functionality or e utility and uses the function point method as a productivity measurement. Function points are derived using an empirical relationship based on countable measures of software's information domain and assessments of software complexity.
Feature point matrics
The feature point metrics are an extension of function point metrics. It includes applications in which algorithm complexity is high. To estimate the Future point, information domain values are again counted and weighted. Also, the feature point metric counts new software characteristics algorithms.
The functional point (and its extinction) like the LOC measure, is controversial. Proponents claim that FP is programming language independent but opponents say that it is difficult to collect the fact.
Metrics for software quality
The overloading goal of software engineering is to produce a high-quality system, application, or product. To achieve this goal, software engineering must apply effective methods coupled with modern tools within the context of a mature software process. A good software engineer must measure if high quality is to be realized.
A good software engineer uses measurement to access the quality of the analysis and design models, the source code, and the test cases that have been created as the software is engineered. Metrics used after delivery focus on the number of defects in the system.
The software quality measure is correctness, maintainability, integrity, usability.
Correctness is the degree to which a software its required function. The common measure of correctness is defects per KLOC.
Maintainability is the comfort with which a program can be corrected if an error is found, adapted if its context changes, or improved if the customer Desires a change in demands. Maintainability is measured only through indirect measures like the time it takes to analyze the change request, design a modification, implement and test it and distribute it to all users. Another metrics available for maintainability is cost-oriented metrics the cost to correct defects encounter after the software is reduced to end-users.
Integrity measure the ability to withstand attacks by hackers and viruses both internal and accidental. The attack can be made on all three components of software programs, data, and documents. Related to integrity security also has to be taken care of.
Usability means user-friendliness. If your product is not user friendly then it will be a failure, irrespective of all other factors. Usability is measured through:
Integrating metrics within the software process
Software developers never thought about measurements or they never realized about measurement. But unless we measure, we will not be able to determine whether we are improving or not. By Requesting and evaluating productivity and quality measures, managers can establish goals for improvement of the software engineering process. So measurement is used to establish a process-based and from which improvement can be calculated. By using these baselines, the project estimates will be made proper, the quality of the product will be increased.
At the time of Data Collection itself, a lot of Investigation should be made, and the data should be reconstructed. This list to proper Analysis of data through LOC or FP metrics and other quality factors. Finally, Matrics must be evaluated and applied during estimation, technical work, project control, and process improvement. This leads to a process set of indicators that guide the project or process.
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