Software Metrics in Software Engineering

What are Software Metrics in Software Engineering?

Software metrics in software engineering are the standards for estimating the quality, progress, and health of software development activity. A software metric is a quantifiable or countable assessment of the qualities of software.

Characteristics of Software Metrics

Software metrics in software engineering should possess the following characteristics:

• Quantitative: Metrics must be quantitative in order to be helpful. It means that metrics can be stated numerically.
• Understandable: Metric computation should be simple to grasp, and the method for computing them should be well explained.
• Applicability: Metrics should be applied during the early stages of software development.
• Repeatable: When measured regularly and consistently in nature, the metric values should be the same.
• Economical: Metric computation should be cost-effective.
• Language agnostic: Metrics should be language-independent, meaning their computation should not depend on any programming language.

Need for Software Metrics

Software metrics in software engineering can be used for a variety of purposes, including analyzing software performance, planning work items, estimating productivity, and so on. For example, you can use software metrics to monitor performance, plan upcoming work tasks, track productivity, and better regulate the production process throughout project management if you can view distinct statistics and trends as production takes place. You can also use software metrics in conjunction with management functions to simplify your projects by building more efficient procedures, creating software maintenance plans, and keeping production teams updated on issues that need to be resolved.

Software metrics are needed for various reasons, including the following:

• By preventing faults, it is possible to save money.
• Aids in the improvement of overall project planning
• Aids in the advancement of overall project planning
• Encourages eagerness to improve processes
• Aids in a more thorough analysis of the dangers involved.
• Aids in studying indicators at each testing stage to increase problem eradication efficiency.
• Increases the ROI of test automation over time
• Improves the relationship between testing coverage, risks, and system complexities.

Classification of Software Metrics

There are three types of software metrics in software engineering: product metrics, process metrics, and project metrics. Product metrics are used to define product attributes such as size, design features, complexity, performance, level of quality, and so on. In contrast, process metrics are used to optimize software development and maintenance. Project metrics, such as the number of software developers, cost, and so on, indicate the project's characteristics and performance.

Product Metrics

Product metrics represent product attributes such as size, complexity, design features, performance, and quality level. A working product is created at the end of each successive phase of the software development process. At any step of development, a product can be measured. Metrics are built for these items to determine whether a product is being developed in accordance with user requirements. If a product fails to satisfy consumer expectations, the relevant steps are made in the appropriate phase. Product metrics assist software engineers in detecting and correcting possible issues before they cause catastrophic failures.

Process Metrics

To improve any process, it is important to measure its defined properties, establish a set of meaningful metrics based on these attributes, and then utilize these metrics to generate indicators to develop a process improvement strategy. Software engineers can measure the performance of a software process that is executed using the process as a framework by utilizing software process metrics. The process is at the center of the triangle that connects three aspects (product, people, and technology) that significantly impact software quality and organizational performance. People's competence and motivation, the complexity of the product, and the level of technology utilized in software development all significantly impact quality and team performance.

Project Metrics

Project metrics explain the characteristics and execution of a project. Examples include the number of software developers, the staffing pattern throughout the software's life cycle, cost, schedule, and productivity. The project manager monitors the project's progress using measures known as project metrics. Various metrics, such as time, cost, and so on, are collected using data from previous projects and utilised as an estimate for the new initiative. The project manager monitors the project's progress on a regular basis, and effort, time, and cost are compared to the initial effort, time, and cost. These indicators can help lower development costs, efforts, hazards, and time. The project's quality can also be improved. With an improvement in quality, there is a decrease in the number of errors, time, cost, and so on.

Types of Software Metrics

• Internal metrics: Internal metrics are used to measure properties that are deemed more important to a software developer than the users. Lines of Code (LOC) is one example.
• External metrics: External metrics are used to measure features that are deemed more important to the user than the software developers, such as portability, reliability, functionality, usability, and so on.
• Hybrid Metrics: Metrics that mix product, process, and resource metrics are known as hybrid metrics. Cost per FP is an example, where FP stands for Function Point Metric.

Advantages of Software Metrics

• The software system design technique can be analyzed in comparison to other designs.
• Using software metrics, the properties of various programming languages can be explored for study and comparison.
• Software metrics in software engineering can be used to create software quality requirements.
• Software system compliance with requirements and standards can be verified.
• It is possible to infer the effort required to design and develop software systems.
• The code's complexity can be calculated.
• It is possible to decide whether or not to divide a complex module into smaller ones.
• It is possible to direct the best use of resource managers.
• It is possible to make design trade-offs and compare maintenance and software development expenses.

Disadvantages of Software Metrics

• It isn't easy to apply measurements in all situations. In some circumstances, it is difficult and costly.
• It is challenging to validate historical or empirical evidence used for verification and argumentation.
• Although software products can be managed, technical staff performance cannot be measured using software metrics.
• The available tools and working environment are utilized to define and derive software metrics, and there is no standard for doing so.
• Certain variables are estimated using predictive models and are not always known.