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Quality Metrics In Software Engineering

When working in technology and software engineering, quality metrics offer a measurable framework to help navigate the creation and maintenance of software applications. Nowadays, the development and upkeep of software applications have reached an all-time high. The question is, how do you measure the quality of a software product? Even more, how do you measure quality during development?

Measuring quality involves assessing performance, reliability, efficiency, and user-friendliness. Apart from assessing whether a final product is successful or not, quality metrics enable software engineers to evaluate and enhance their processes continually. Established metrics help developers and managers know where they stand with a project, and can help teams identify bottlenecks or issues, monitor progress, and make better-informed decisions.

First and foremost, it’s important to ensure that the software being developed can provide value to your customers, consistently. Quality metrics measure that consistency. Any quality problem, whether that is a bug, a glitch, or something else unforeseen, is a potential threat to successful delivery of value. Unhappy customers are not simply a problem for the revenue team. Quality issues will eventually come back to the engineers – your team. It’s important to monitor quality metrics in order to minimize customer impact and ultimately to maximize customer satisfaction and retention. 

Software Quality Metrics to Track 

  1. Bugs

For the most part, bugs are an inevitable part of building software. Of course having some bugs does not inherently imply your product will not satisfy customers, but it can certainly have a big impact. By measuring bugs as a KPI, you are not trying to prevent them, but rather simply surfacing where they exist so you can catch, prioritize, and fix them in a timely manner.

Therefore, the key thing to monitor here is a breakdown of bugs by product or feature. By understanding the number and severity of bugs that exist per product or feature, and comparing that with product or feature usage among your customer base, you will have a better understanding of which bugs to prioritize fixing, and therefore where to devote your resources.

  1. Time to Resolution

Since you cannot fix every incident, bug, or failure immediately, it’s important to keep track of how long quality issues hang out in the product before being addressed. Of course, some incidents (security breaches for example) require immediate attention and should have shorter resolution times, while you can afford to wait on others. On the whole, measuring the time it takes to resolve reported bugs, failures, and other incidents will give you a sense for the team’s ability to be responsive to customer problems. Combined with a metric like net bugs, or the number of bugs reported vs. fixed which monitors how bugs are accumulating, this will give you an understanding of how well your team is managing the constant inflow of issues and how fast we can fix prioritizing quality in the product.

  1. Uptime

In today’s constantly connected world, your customers expect technology (especially SaaS) products to be available to them at all times, whenever they need it. Unplanned downtime, or even slower delivery of services during certain times can threaten the relationship with your customers.

The importance of monitoring and maximizing uptime is especially true in industries like e-commerce where failing to deliver services can equate to loss of revenue and is an immediate threat to the business. But across industries, and especially in the modern world where just about the only way to engage customers is remotely, it’s important to ensure your products perform well and are delivered reliably to your customers.


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Product Metrics In Software Engineering

Product metrics play a role in software engineering by helping developers assess a software product’s quality, performance, and overall value. These metrics provide insights for decision-making by identifying areas for improvement and evaluating the success of implemented changes. When measuring product quality, parameters like reliability, maintainability, functionality, usability, efficiency, and portability need to be considered. Organizations often adopt a product metrics framework that tailors metrics to streamline this process and ensure consistent data collection to their needs and objectives. This framework serves as a foundation for setting goals and targets while optimizing data analysis.

A framework that helps assess the performance of a product also plays a role in facilitating communication among stakeholders by providing a language to discuss progress toward goals. Product metrics examples provide insights into how the software operates. Some examples include:

  • Requirement volatility: The changes in requirements during the development process.
  • Mean time to recovery: The average time it takes to recover from an incident. 
  • Feature usage: This involves examining how users interact with features.

By monitoring these metrics, organizations can consistently improve their software products while optimizing their return on investment. Understanding the importance of product metrics in software engineering is vital to delivering high-quality software that effectively caters to user requirements. By focusing on measuring quality metrics, organizations can gain insights that inform decision-making and enhance software quality. Following structured frameworks for consistent data collection and analysis empowers teams with the necessary information for product development. Implementing these practices will ultimately lead to user software products that drive success.

Process Metrics In Software Engineering

Few technical leaders today would argue with the notion that speed to market – that is, delivering product quickly and efficiently – is paramount to success in the world of software. If you’re already confident that your team is building the right things and that those things can continually deliver their intended value to your customers, you’ve got a good base on which to seek efficiencies in process that will allow your team to move faster and increase predictability of the delivery of your commitments to the go-to-market team.

Delivering code faster is where most vendors and vocal members of the tech community focus. But delivering predictably is important to set proper expectations, drive alignment across functional teams, and allow for better execution and therefore better penetration of the market for that value your organization has worked so hard to build. There is no perfect measure of delivery speed, team efficiency and productivity, or predictability. As such, these KPIs will not be all-encompassing or perfect. Instead, they will highlight trends and therefore give a better understanding for how any process or tooling changes have affected the activity and health of your team. We’ll cover: Cycle Time & Lead Time, Deployment Frequency, and Task (or other unit of work) Resolution Rate Over Time.

Cycle Time and Lead Time

Cycle time is a common metric touted by Agile aficionados and for good reason. It measures the amount of time that elapses from the start of work on a particular task until that task is complete and ready to be shipped. Simply put, cycle time measures the time it takes to complete work on a task. By keeping track of cycle time, you can compare planned work with similar tasks that the team has completed in the past and provide an estimate for the delivery of that functionality. It will help you better predict how long features will take to build and therefore when they should be expected to ship.

Lead time is one of the key metrics that DORA (DevOps Research and Assessment group) espouses for optimizing the speed of value delivery to customers. Most often it is measured as the time between first commit and deployment, but that definition may be increasing in scope with newly available technologies and methods of measuring.

The point of Lead time is to understand the amount of time it takes between the initiation of a change request and when that change is running in production – or how quickly we can deliver value to customers.

Deployment Frequency 

Tracking how often your team does deployments can be extremely useful for understanding and improving on the speed with which you can deliver value to customers. Deployment Frequency is another DORA metric, and in true DevOps fashion, the goal is to do smaller deployments as often as possible. Small deployments will make testing and releasing easier, which will in turn drive down the time it takes to get new functionality in the hands of users.

Task Resolution Rate Over Time

As most projects are broken down into smaller bits of work that can be handled by and assigned to an engineer, it can be useful to measure how many of those pieces of work are being completed versus the number that have been created (resolution rate) over time. Many teams use a common framework in which an issue is the basic unit of work, a group of issues is an epic, a group of epics is an initiative, and so forth. In that terminology, measuring issue, epic, or initiative resolution rate gives a sense for how well your team is handling the work being assigned to them, how fast they can generally complete this work, and whether changes need to be made.

It’s important to recognize that these tasks are not a standard size. Some issues will take a day to resolve, while others will take two weeks simply due to their scope. That’s why we suggest measuring the resolution rate, and monitoring it over time to identify trends. By understanding how your resolution rate is trending you can be quicker to respond to problems that arise in the development process, and measure changes in efficiency when making changes.