What is software reliability in software engineering?
Software reliability is the probability of failure-free operations in a computer program for a specified period of time in a specified environment.
It is critical for validation in order to determine characteristics in terms of system performance, functional compatibility, maintenance, competency, installation coverage and process documentation continuance.
Software reliability helps you to identify and fix bugs, improve performance, and test features. By performing a variety of reliability tests through different environments you can ensure that the software functions exactly how it should.
In the world of software engineering, it takes a lot of work to achieve such a high level of reliability, and system engineers are going above and beyond to achieve an up-to-date software application.
Why do software reliability metrics matter?
As teams grow, products then need to scale, and software reliability metrics become even more crucial to measure.
Software reliability metrics enable teams to have an insight into how their product is performing and what the customer side is experiencing.
The purpose of software reliability metrics is to get rid of bugs in the program so you don’t have a failing product. Without reliability metrics, it would be extremely hard to identify where exactly the issue is and how to solve it.
That’s why adding reliability metrics enables teams to be able to view every aspect of the product and have the relevant data required to fix issues.
6 Software Reliability Metrics That Matter
There are 6 reliability metrics that matter, these are:
- Mean Time to Failure (MTTF)
- Mean Time to Repair (MTTR)
- Mean Time Between Failure (MTBR)
- Rate of occurrence failure (ROCOF)
- Probability of Failure on Demand (POFOD)
- Availability (AVAIL)
1. Mean Time to Failure (MTTF)
Mean Time to Failure (MTTF) is sometimes referenced as Mean Time For Failure (MTFF) and is the length of time a piece of software can last in operation.
As a metric, MTTF provides insight into the length of time a product can reasonably perform based on varied testing environments.
2. Mean Time to Repair (MTTR)
Mean Time to Repair (MTTR) ‘mean time to’ means you’re looking at the average time between two events.
MTTR is a maintenance metric that when used measures the average time between events required to troubleshoot any repairs needed with failed equipment.
It gives an insight into just how quickly a maintenance team can respond and repair unplanned breakdowns.
3. Mean Time Between Failure (MTBR)
Mean Time Between Failure (MTBR) is one of several related metrics that are used to help provide information on operating reliability for products and systems.
MTBR can often be defined as the average operating time between repairs for a product or set of products.
4. Rate of occurrence of failure (ROCOF)
The rate of occurrence of failure (ROCOF) gets used to model the trend in the failure interarrival times.
When we have a repairable system, we want the ROCOF to be improved and the failure interarrival times to be increased.
Failure times can often be quite random so it is necessary to conduct a statistical test that can be used to determine if there is a statistically significant trend.
5. Probability of Failure on Demand (POFOD)
The probability of Failure on Demand (POFOD) is the likelihood that the system will fail when a request is made.
An example of this is POFOD of 0.001 means that 1 in 1000 may result in failure.
6. Availability (AVAIL)
Availability (AVAIL) is the measurement for how likely a system will be available to a user within a specific time period.
It measures the likelihood of availability of a system for users over a period of time. This metric can help teams understand the software’s reliability on a wider scale and how it may affect their customer’s experience.
How can software reliability be improved?
Software reliability can be improved by a much clearer understanding of metrics to measure, and the characteristics of software. It can become costly to companies when developers are using inadequate processes. Using better development processes and knowing which metrics to track empowers you to improve team culture and improve reliability.
Software Reliability Techniques
Using software reliability techniques is important because both kinds of modelling methods focus on observing and accumulating failure data.
There are two types of software reliability techniques, these are Prediction Modelling and Estimation Modelling.
Prediction Modelling is an analysis that is used to predict the rate at which an something may fail. A reliability prediction is normally based on an established model for either electronic or mechanical components.
The prediction model provide procedures for calculating the failure rate for any components that are tested.
Estimation techniques include such methods to system reliability throughout a product life cycle.
The main purpose of reliability is estimation, demonstration and testing. It is this which is used to determine whether a certain product has met a certain level of reliability required with the statistical level.
SLAs, SLOs, and reliability metrics
These acronyms - SLAs, and SLOs are the primary metrics of Site Reliability Engineering (SREs).
SLA is an agreement between a service provider and the customer or user regarding service deliverables. An SLA provides the consumer with a clear understanding of the product or service for both its functionality, reliability and performance.
Google’s Life lessons define an SLA as, ‘An SLA normally involves a promise to someone using your service that its availability should meet a certain level over a certain period, and if it fails to do so then some kind of penalty will be paid.’
SLOs which stand for Service Level Objective is an objective measure of a product’s reliability, or performance goals.
They are numerical performance targets that a developer should also adhere to, these are important when building and scaling a product.
Software reliability models
Software reliability models predict how software reliability should improve over time when errors are discovered and repaired.
These types of models help teams decide how much time should be devoted to various testing. The objective is to test and debug a system till the required level of reliability is reached.
Types of software reliability models include:
- Shooman model
- Basic execution time model
- Littleword - Verrell model
- Goel - Okumonto model
- Musa - Okumonto
- The bug seeding model
- Logarithmic Poisson time model
- Jelinski and moranda model