Software Reliability Metrics - Types | Benefits

The reliability of a system or component is defined as its capacity to carry out its intended functions under known circumstances for a predetermined amount of time.

Digital managers, project managers, and other technology professionals rely on software reliability to help them determine how well systems function.

Software reliability refers to a critical component of computer system availability, indicating whether users can expect a software program to perform consistently.

Software reliability is the likelihood that a software system will carry out its intended function in a specific environment for a specific number of input cases, presuming that the input and hardware are error-free.

It's essential to use reliability metrics to discover problems in software design. The metrics can be used to improve software product performance and development.

According to the Encyclopedia of Physical Science and Technology, software reliability can be defined as;

“The probability of failure-free operation of a computer program in a specified environment for a specified time.”

The importance of software reliability metrics in determining the success of a product shouldn't be underestimated. The ramifications of poor-quality software can be far-reaching and, sometimes, impossible to recover from.

Discovering potential issues before releasing a software product can spare your business from costly expenses associated with rework. More importantly, it can help protect from major bugs and vulnerability issues that can irreversibly impact your brand reputation and consumer trust.

Read on to get an in-depth look at the various types of software reliability metrics. We also show how each one can improve your next software release and software development process at large. 

What are reliability metrics in software engineering?

Reliability metrics are quantifiable (or countable measures) of performance used to figure out areas where the software needs improvements. Integrating software reliability metrics into a business's development model is essential to a product’s success. 

One of the most challenging questions in terms of software development is:

How can we tell that a software release is ready to deploy?

This is a critical concern, but it's hard to answer with total certainty.

Companies naturally want to provide customers with updated releases. However, there can be a fine line between a product ready for customer use and one that still has undetected bugs. That's where software reliability metrics come in. 

Software reliability metrics are used during the software development process to determine the quality of a software’s functioning at any given point in time.

They are ways of measuring software and associated processes to provide development teams with valuable information about the performance of different aspects of the software.

Why do software reliability metrics matter?

Software reliability metrics are essential because they directly reflect the experience the end-user will have of X product. Releasing a poor-quality product in any industry risks damaging a brand’s reputation and creating enormous financial expenses.

It's easy to see how this applies to physical products. If you purchase a defective gadget or find out your new car is being recalled, you'll likely think twice about buying anything from that company in the future.

The same applies to the digital realm, where software products are released with bugs and glitches or other issues that ruin the execution time and digital experience. 

A report by the Consortium for Information and Software Quality (CISQ) found that U.S. companies lost over $2 trillion dollars in 2020 as a result of poor quality software.

Huge expenses like this come as a result of operational software failures, security vulnerabilities, and other bugs discovered by end-users after a product's release.

The goal of testing and interpreting software metrics is to understand where your software isn't up to par so that you can improve the quality and maintainability.

These metrics also help predict the quality of the product once you've addressed major issues and the software development project is complete.

Several purposes for using software reliability metrics include:

• Increasing return on investment (ROI)
• Identifying bugs and other issues
• Integrating new code
• Managing workflows 
• Reducing employee workload
• Reducing costs

Software reliability metrics and observability metrics are among the best methods a company can use to determine reliability measurement and overall product quality.

Metrics are critical for; quality assurance, management, debugging, performance, and forecasting costs. 

Few stats when it comes to software testing;

• The software market size surpassed $40 billion in 2020. (Global Marketing Insights)
• The U.S. testing industry is worth $6.3 billion as of 2021. (Ibis World)
• 20% of the demand for software testing comes from the Federal and State governments. (Ibis World)
• IT and telecom hold 20% of the software testing market share. (Global Market Insights)
• 35% of companies hire or use non-testers for software testing. (The QA Lead)
• 44% of IT companies automated 50% of testing in 2020. (RWS) 
• 24% of companies saw an instant increase in ROI once they started automated testing. (Software Testing News)
• Only 5% of companies use fully automated testing. (Software Testing News) 
• Up to 56% of software testers are self-taught. (The QA Lead)

Common types of reliability metrics

There are dozens of reliability metrics you can choose from, but not every measurement will be useful to all companies and products across the board.

The most valuable software reliability metrics for your company will vary a bit depending on your industry, the type and function of your software product, and the overall goals and objectives of your business.

Nevertheless, the following six measurements can be used together to provide a fairly comprehensive sense of the overall reliability of your software. 

Mean Time to Failure (MTTF)

MTTF examines the amount of time between two occurrences of failure in software usage under normal operating conditions. The metric is an average of the time elapsed between two failures over the total number of failures.

Software failures are almost unavoidable, but this number attempts to quantify how long the software can operate without experiencing a failure. However, it doesn't look at the time it takes to fix the error and get the software running again. 

This is a vital, safety-critical metric because it helps developers understand how long a software can perform before failing. It also helps predict failures going forward. 

Mean Time to Repair (MTTR)

When software fails, it takes time to fix the error. MTTR measures the average time it takes to track the cause and repair the software fault.

Developers use this metric to understand the length of time needed to fix an error once a failure occurs. Teams look to this number to better understand their working process for reliability and find ways to improve it. 

Rate of Occurrence of Failure (ROCOF)

ROCOF is the number of failures that appear in a given time interval (i.e., the number of unexpected events over a specific time of operation).

This helps developers understand the frequency of failure occurrence. While other metrics measure lengths of time between events, ROCOF measures how often the event happens. The value is a ratio of the total amount of failures per the length of time they happen in. 

Mean Time Between Failure (MTBF)

MTBF uses previous observations and data to figure out the average time between failures. The number is derived by adding together the MTTF and MTTR metrics.

MTBF values are used to calculate overall failure rates for both repairable and non-repairable products.

For example, an MTBF of X denotes that once a failure occurs, the next failure is expected to appear sometime after X hours have passed. 

Probability of Failure on Demand (POFOD)

POFOD refers to the probability that the software will fail when a certain action happens. This can be used in systems where actions or services are requested at an infrequent pace.

It doesn’t involve real-time measurements like other attributes, but it gives developers a sense of how often a failure can be expected versus how many times a request will be successful in a product’s life cycle.

Availability (AVAIL)

AVAIL of software measures the possibility of availability of the system for use over a specified period of time. It calculates the number of failures that happen during a specific period and considers the length of downtime that results when a failure happens.

This is an important metric for software that causes major effects or damage when outages occur, such as telecommunication and operating systems.

Knowing the total time that software could be unavailable over a specific time frame helps teams understand what the repercussions might be. 

How businesses benefit from leveraging these metrics

Software reliability metrics give stakeholders a way to plan and forecast the software development process.

Investing in this aspect of the development process allows the software quality to be easily measured and improved upon. Leveraging these metrics increases a team’s chances of releasing high-quality software.

This attention to quality can increase productivity and help establish a sense of continuous improvement across a company culture. 

We at Adservio are passionate about creating high-quality software and helping enterprises achieve more with our world-class software engineering and quality control. ‍

Reach out to our team of experts to find out how we can help your business benefit from leveraging software reliability possibilities.