Software Engineering Metrics Your Team Must Follow in 2025

For any software development company, measuring its final output is incredibly difficult. Any manager giving serious thought to it has heard disapprovals like “How can we measure the immeasurable?” or “When measure becomes a target, it stops being a good measure.”

Unlike other fields, such as manufacturing, where metrics like production output and defect rates are easily measurable, software engineering lacks objective metrics for performance. While you can track the LOC count and the number of bugs fixed, they are not necessarily accurate or reliable software engineering metrics.

So, the bad news is that success in software development is often subjective and depends on the needs and expectations of the stakeholders involved. What one considers successful may not be viewed the same by others, which makes it difficult to evaluate the performance of dev teams and the efficiency of their software engineering services.

But here’s the good news – there is an increasing number of tried-and-true software delivery performance metrics to know how your software engineering team is progressing and what is getting in the way.

In this piece, we will break them down one by one to help your team get on track and deliver production-ready software at speed and scale. Let's get going!

What are Software Engineering Metrics?

Software engineering metrics are quantitative measures used to assess and evaluate the software development process. These metrics are used to track the progress of software development projects and provide insight into the quality and efficiency of the development life cycle.

Some common engineering metrics include lines of code, code coverage, cyclomatic complexity, code churn, defect density, and testing time. Professional software developers use these metrics to identify areas of the code that are problematic, such as those that are difficult to maintain or prone to errors.

In addition to identifying potential problem areas, such software delivery performance metrics are also very useful in setting goals for engineers and tracking progress toward those goals. For example, a team may set a goal to increase code coverage by a certain percentage, and then track their progress toward that goal using metrics.

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Why are Engineering Metrics Useful?

Metrics are vital because they offer developers a clear and objective understanding of the performance of the software engineering processes.

With valuable insights and reports on the efficiency of engineering practices, dedicated developers can identify areas that require improvement and optimize workflows. They also identify potential problems early and make informed decisions to prevent them from becoming larger issues down the line.

Hence, engineering metrics and measurements are the compasses that help developers navigate through the complex and ever-evolving landscape of software development and make timely predictions. For example, you can measure:

• The time it will take to complete the project
• What the project budget should be
• Roles and responsibilities of each team member
• The desired quality of the software product

Different Types of Software Engineering Metrics

There are five broad categories of metrics in the software engineering field:

• Product metrics

Starting with software product metrics that focus on the characteristics of the software product, such as size, complexity, maintainability, and reliability. Such engineering metrics examples include lines of code, cyclomatic complexity, defect density, and code coverage.

• Process metrics

Process metrics in software engineering, including lead time, cycle time, defect arrival rate, and change requests per month, are highly useful in the software development process, like productivity, efficiency, and quality.

• Project metrics

These software engineering performance metrics deal with different aspects of the development project, like cost, schedule, and resource utilization. Budget variance, schedule variance, and resource utilization rate are all examples of project metrics.

• People metrics

If you need to assess the skills, experience, and commitment of your software engineering team, people metrics are beneficial. These include employee turnover rate, training hours per employee, and satisfaction surveys.

• Quality metrics

Quality metrics measure the quality of the software product through defects, failures, and customer satisfaction. Some of the key quality reengineering metrics are defect removal efficiency, mean time between failures, and Net Promoter Score.

Benefits of Software Engineering Metrics

So, why should your development team care about engineering metrics? An obvious answer is that there will literally be no scope for improvement if you do not have the performance data. Apart from that, here are some of the other compelling advantages of software metrics:

Measuring Progress

As we already mentioned, one of the key benefits of software metrics is that they help engineers measure the progress of a software project by providing data on the amount of work completed and the remaining work to be done.

Identifying Issues Early

Metrics enable teams to identify potential issues beforehand in development, allowing for timely intervention and resolution. This saves a huge amount of time and money in the long run.

Improving Quality

You can track the quality of code and pinpoint areas that require improvement. This is an effective way to maintain code quality and coding standards.

Managing Resources

Metrics and KPIs for engineering teams can help managers allocate resources effectively by defining areas of the project that require more attention or resources.

Facilitating Communication

Another benefit of software engineering metrics is seamless communication between cross-departmental teams. Everyone can communicate more effectively with a common goal and a shared understanding of the project's progress and goals.

Enhancing Decision-Making

Metrics can provide data-driven insights that support informed decision-making, helping teams make better choices about how to allocate resources and prioritize tasks.

List of Key Software Engineering Metrics

Here are a few software engineering metrics that have secured a sweet spot between "widely utilized," "empirically validated," and "gaming-resistant when properly implemented.” In general, the more you work on integrating these metrics in the software delivery pipeline, the better value it will generate for your team.

DORA DevOps Metrics

In 2018, Google's DevOps Research and Assessment (DORA) team created a set of four metrics to help DevOps services companies measure and improve their performance. These metrics, known as the DORA DevOps metrics, have gained popularity in recent years due to their effectiveness in measuring software delivery and operational performance.

DORA metrics empower organizations to objectively measure their DevOps performance, identify areas for improvement, and track progress over time. They are also useful in benchmarking performance against industry competitors and identifying best practices.

One main reason for the popularity of the DORA DevOps metrics is their alignment with the DevOps architecture, its principles, and tools, which emphasize collaboration, continuous delivery, and a focus on customer needs. By measuring and optimizing these metrics, software engineering firms can accelerate their software delivery cycles, reduce risk, and improve the quality of their products and services.

Take a look at the 4 DevOps metrics presented by the DORA team:

• Deployment Frequency

The deployment frequency metric is a crucial one to measure the performance of software delivery teams. It is the frequency at which a team deploys code to production or releases new features to users and you can measure it by counting the number of deployments or releases that your team makes over a given period of time, such as a week or a month.

DORA has found that dedicated development teams with high deployment frequency also tend to excel at other DORA engineering metrics, indicating that they are more effective at delivering value to their customers.

As such, it is a valuable metric for teams looking to improve their development practices and deliver software more effectively.

• Lead Time for Changes

Next is the lead time for changes - the time your team takes to develop, test, and deploy a code change into production. It measures the elapsed time from when a programmer starts working on a change to when it is deployed to production.

This metric is important because it provides a measure of the speed at which your development team can deliver new features and functionality to end users. To calculate the lead time for changes, DORA recommends measuring the time it takes from code commit to code deployment in production. This includes the time it takes to build and test the code, as well as any necessary approvals or reviews.

Hence, a shorter lead time indicates a more productive development process.

By tracking the delivery lead time for changes over time, teams can figure out what they should improve and how to optimize their development processes to deliver higher-quality code at a faster pace.

• Mean Time to Recovery (MTTR)

Mean time to recovery is another important software engineering metric for modern software engineering practices, that measures the average time it takes to recover from a service disruption or outage. By tracking MTTR, you can improve the incident response process and reduce the impact of service disruptions on your customers.

In the DORA context, MTTR typically evaluates the effectiveness of an organization's incident response process in terms of how quickly incidents are resolved and services are restored to normal operation.

So, software development firms with a shorter MTTR tend to have better incident response processes and resources to handle service disruption.

• Change Failure Rate (CFR)

The DORA change failure rate is another critical metric to assess software delivery performance.

It provides a way to evaluate the stability of the software delivery process. You can then calculate the CFR by dividing the number of changes that lead to service impairment or outage by the total number of changes made to production.

Naturally, a high CFR can indicate that the software delivery process is unstable and needs improvement.

Regularly measuring the DORA metrics change failure rate and setting targets for improvement can help organizations find improvement areas and track progress over time. By reducing the CFR, organizations can improve the stability and reliability of their software delivery process, which can ultimately lead to improved business outcomes and easier software maintenance.

Finally, as Google proposed, here is how you can convert DORA metrics into calculations at the systems level:

Agile Process Metrics

Agile software development methods emphasize continuous improvement, collaboration, and flexibility. To measure the success of agile projects and teams, there are several performance metrics that software engineers use.

Here are some examples of different types of Agile process metrics:

• Velocity

Velocity measures how much work a team completes in a sprint or iteration. Developers calculate it by adding up the story points or other units of work completed during the sprint. You can use this metric to forecast how much work a team can complete in upcoming sprints.

• Cycle Time

Cycle time is the time it takes for a task or user story to move from start to finish. It measures the amount of time that passes from when engineers start the work and when they complete it. Cycle time can help identify bottlenecks and inefficiencies in the development process.

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• Lead Time

If you want to know what time it takes for a user story or task to be completed from the time it is requested by a customer or stakeholder, the lead time metric is helpful. It can help teams identify how long it takes to deliver value to end users.

• Burndown Chart

Next in our list of Agile performance metrics for software engineers is a burndown chart - a visual form of the pending work to be completed in a sprint or iteration. It shows the progress of the team toward completing the work and can help identify if the team is on track to complete the sprint on time.

• Cumulative Flow Diagram

A cumulative flow diagram represents the amount of work in progress and finished over time. It can help identify pain points in the development process and make forecasts on the completion of the work.

• Defect Density

This metric measures the number of errors found in a specific unit of system or code. It can help teams analyze quality issues and prioritize improvements.

• Sprint Retrospective Feedback

Sprint retrospective feedback is the feedback provided by team members at the end of a sprint. Apart from improving the process, engineers use it to adjust the process for future sprints.

Security Metrics

In software engineering, the goal of security metrics is to evaluate the strength of security controls and processes, predict potential risks, and measure the overall security posture of a software system. Let's go through a few:

• Vulnerability Metrics

Vulnerability metrics help track the number and severity of vulnerabilities discovered in a system. These include the number of vulnerabilities discovered, the time it takes to remediate vulnerabilities, and the percentage of vulnerabilities that have been fixed.

• Compliance Metrics

These metrics make it incredibly easy for software engineers and software developers to review compliance with security standards and regulations such as PCI DSS, HIPAA, and ISO 27001.

For example, the percentage of systems that are compliant, the number of security incidents that violate compliance, and the frequency of security audits.

• Incident Metrics

Incident metrics include the number of incidents reported, the time it takes to resolve incidents, and the cost of responding to incidents to measure the number and severity of security incidents that occur in your system.

• Access Control Metrics

You can use this type of security metric to evaluate how effective your access control mechanism is. To prevent unauthorized access to a system. It calculates the number of successful and failed login attempts, the number of accounts with privileged access, and the time it takes to revoke access privileges.

• Threat Metrics

These software engineering metrics measure the likelihood and potential impact of different types of threats to a system, such as the impact of a DDoS attack on system availability, the probability of a successful phishing attack, and the risk posed by unpatched threats.

Production Metrics

Production metrics assess the performance and quality of software systems in the production environment. These metrics give you real-time insights on how to measure engineering team performance and integrate speed as a component.

Some examples of production metrics in software engineering include:

• Response Time

The response time metric measures how long it takes for a system to respond to a user request. It is an important metric for systems that need to process a large volume of requests, such as eCommerce websites.

• Code Churn

Code churn in software development defines the number of LOC that developers changed, added, or removed over a predetermined amount of time. An increase in code churn may be a sign that the development project needs attention.

• Error Rate

Error rate is the frequency of errors that occur during system operation so that engineers can spot defects or bugs and fix them quickly.

• Availability

As the name says, the availability metric measures the percentage of time that a system is available for use. If you have systems that need to operate continuously, such as financial or healthcare software systems, this is an essential one.

• Throughput

You can measure the amount of data that a system can process in a particular amount of time with the software metrics. It is an important metric for systems working with high volumes of data, such as social media platforms.

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Who Should Use Software Engineering Metrics?

Software engineering metrics are essential tools for any individual or organization involved in software development services since they are a surefire way to gauge the efficacy of your team and take necessary actions.

For software engineers metrics can help you identify areas of improvement in your coding practices and development process. By measuring code complexity, defect density, and other metrics, you can identify potential issues early on and take needed steps before they become critical.

Project managers can also use software engineering metrics to track the progress of their projects and make informed decisions about resource allocation and project timelines. Metrics such as code churn, time to market, and defect trends can help managers identify areas where they need to modify the software project planning and delivery strategy or properly utilize resources.

In terms of business owners and stakeholders, they can benefit from software engineering metrics by gaining insight into the quality and performance of their software products. for instance, measuring customer satisfaction, defect rates, and time to market can help business owners make informed decisions about product features, pricing, and market positioning and stay ahead of the market competition.

How to Use Software Engineering Metrics?

Before we list down the best practices of using metrics to evaluate your team performance, you must remember that software engineering metrics are a set of the finest tools to support decision-making, not as a substitute for good judgment or experience.

Always consider the context in which your organization needs to utilize the metrics and use them to complement, not replace, other sources of information and feedback.

With that being said, here is how you should start using software metrics for the optimal result:

1. Setting goals is the first priority: Determine the objectives you want to achieve with metrics. For example, you might want to improve software quality, reduce costs, increase productivity, or meet project deadlines.

2. Ensure error-free collection of the data: Make sure you are collecting the right data needed to calculate the metrics. You can use automated tools or manual processes to gather accurate data on software development activities and outputs.

3. Thoroughly interpret the results: Interpret the results of the metrics analysis to make informed decisions about how to improve software quality and performance. For instance, you may decide to implement process improvements, refactor code, or scale your software development team.

4. Act on the insights: Take action based on the insights gained from the metrics analysis. Use the data to drive continuous improvement in software development practices and achieve your goals.

5. Communicate metrics to stakeholders: It's important to communicate your metrics to stakeholders, including team members, project managers, and customers. This helps ensure everyone is on the same page and can work together to achieve project goals.

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Over to YouEveryone in the development niche knows that one of the most critical factors in building successful software is to create an all-inclusive team, share a common goal, and work collaboratively throughout the entire project. And for that to happen, you need to know how your team is performing in the first place.While many developers and engineering teams still rely on gut feelings or anecdotal evidence to assess team productivity, it can lead to inaccurate or incomplete assessments of their performance. This is where software engineering metrics come in.The metrics proposed in this post should serve as a solid starting point for any organization and we hope they help continue to adhere to the core software engineering principles in a period of rapid change.Having said that, to better reflect your own unique objectives, you might want to create your own metrics set. There is a variety of modern development metrics gaining growing popularity, such as GQMs (Goal, Metric, Question) or OKRs (Objectives and Key Results).And if you need any help in implementing these metrics or any other software engineering solutions, our seasoned team is here to work with you.Share your requirements with us now!