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The world is becoming digital. So, if you are a service provider, it is highly recommended to go with a reliable software development solution. For that, knowing Software Development Metrics is crucial.
However, the majority of the firms make the mistake of investing the entire amount on software development only. But, you are required to keep a vigilant eye on the performance and productivity of the software.
That’s where the role of Software Development Metrics comes into the picture. Here, in this article, you will know each and every aspect of Software Metrics.
Software metrics are a countable measure of software characteristics. By using Software Development Metrics, the management gets a fair idea of the quality, productivity, efficiency, and performance of the software.
In the long run, it will help you to offer an optimized and reliable solution. Let’s discuss some of the popular Types of Metrics.
LOC, also known as Lines of Code, the complexity of the code, Instruction path length, and the list will go on.
However, in the rapidly changing software development environment, formal code metrics are often regarded as relatively less useful.
Like active days, the scope of the assignment, code churn, efficiency aspect, and so on. Developer productivity metrics help you to get an insight into the amount of time and work that the developer community is offering for your ongoing project.
Like lead time, velocity, cycle time, etc. These metrics help to track the progress of the developing team in various aspects, such as the quality of shipping and features of the software.
Like MTBF: the Mean Time between Failures, and MTTR: Mean Time to Recover.
Operational metrics are often used in order to track the performance of the software during the production stage and the effectiveness of staff while maintaining it.
Like coverage of code, automated test percentage, tracking the sets of defects during production, etc.
As the name suggests, Test metrics are meant to measure how effectively the software is tested. In the long term, such tools help to improve the quality of the software.
Like CES: Customer Effort Score, NPS: Net Promoter Score, CSAT: Customer Satisfaction Score, etc.
Customer satisfaction is an instrumental tool to measure the customers’ experience and ensures the efficient interaction of users with the software.
Software quality is an evaluation of the quality aspect of the software, and you will know how good your software is performing in the real world.
Here are some of the major factors that affect the quality of the software:
A software with greater stability and low risk of failure is often considered a reliable solution.
Some of the relevant software metrics used to evaluate reliability factors are production incidents, load testing, average failure rate, mean time to recover, and the mean time between failures.
Aspects like the efficiency of the code and architecture and average load time of pages affect the performance of the software.
Software Development Performance Metrics like stress testing, application performance monitoring, load testing, and soak testing are extremely useful in order to get a fair idea about the performance of your software.
These days, the number of cybercrime activities has increased significantly. As a result, there is always a chance of data leak, privacy breach, and money laundering. A single mishap is capable of destroying your years of reputation.
Therefore, it is advisable to check the probability that the attackers might be able to gain access to your sensitive information.
In that matter, you can use software metrics like the number of vulnerabilities, resolution time period, update deployment, the severity of the security issues, etc.
It shows the efficiency of your software in order to debug, integrate with new forms of functionalities, and maintenance.
Some of the maintainability-based Software Development Metrics Examples are lines of code, static code analysis, and code complexity for getting an overall improved performance.
If you compare these four aspects, you will find that performance is the easiest aspect to measure.
On the other hand, the rest of the three are relatively tricky and complex to quantify. Therefore, you need to use appropriate metrics in order to get a complete picture.
Net Promoter Score (NPS) is one of the most popular and reliable metrics in order to measure customer satisfaction. By using these particular metrics, you can get a score somewhere between -100 to +100.
The lowest score -100 suggests that none of your customers is referring to you in its circle. On the other hand, the highest total, which is +100 represents that all of your customers are willing to refer you to others.
For instance, you get as many as 100 responses in the Net Promoter Score survey with 20 responses are between 0-6 brackets, 20 responses are between 7-8 brackets, and the rest of the 60 responses are in the bracket of 9-10.
So, the Net Promoter Score of 60 (Promoters’ number) – 20 (Detractors’ number) = 40, ignoring the responses of passives.
Team velocity is a widely popular tool that measures the story points and quantifies the size and number of product features completed by the developing team in their previous sprints.
It offers a rare insight into the value that the team is offering to its customer within a specific time period.
For instance, if a team has completed as many as 20, 21, 20, and 19 story points in its last four sprints, the average velocity will be 20, which is the mean of all these sprints.
The number 20 indicates that the team is expected to give an output of 20 in the upcoming iterations. Anything more than 20 will be regarded as an improvement.
The Release Burndown chart offers an array of information covering various aspects of software development.
The chart helps you to understand the progress in the development of the software, the remaining functionalities yet to be materialized, and the time period when you can expect the completion.
The graph tracks the progression of development by indicating the velocity, and by comparing the previous velocity, it calculates the time required for the completion of the project.
For example, The JIRA Software shown in the chart below indicates the power of the Release Burndown Chart. It shows that in 4 sprints the team has reduced the task from 43 to 26. So, as per this data, the software will release in 7 more sprints
Escaped Defects, as the name suggests, indicates the quality of the software. This metric showcases the number of issues and bugs experienced by the end-user during the production stage of the software. Escaped Defects showcases these bugs in the form of a graph.
If the graph rises in ascending order, it suggests a faulty quality process of the given software. These days, the majority of the stakeholders are taking the help of this metric in order to evaluate the quality of the software.
For example, the defects for the month JAN, FEB, MAR & APR are 3,6, 7 & 8 respectively, then there is a fault in the quality of the software. However, if the graphs in descending order, you’re on the right path.
Even today, the majority of the software developing agencies are using the regular test coverage metrics, which are not reliable enough to trust.
On the other hand, the evolution of true test coverage is significant, and gradually an increasing number of the population are accepting it. The true test coverage is efficient and trustworthy that measures unit tests exclusively.
This particular metric is helpful to know the exact number of the codebase that went through all sets of tests, such as UI automation, end-to-end acceptance tests, manual tests, and so on.
It showcases the quality gaps and the available features that did not go through all sets of test coverage.
For example, there are 20 requirements of feature, and 100 test cases have been created for that. Out of that, if 80 test cases are executed perfectly, then test coverage would be 80%.
Sprint Burndown metric is mostly used for the agile scrum. The report of this metric showcases the complexion of work during the sprint.
The best part of this particular metric is its story point-based report; therefore, you can effectively cross-check the progression of the project according to the previously agreed forecast.
Early finishes of the sprint on a consistent basis showcases a potential delay in the schedule. However, suppose the developing team misses the sprint deadline on a regular basis.
In that case, it suggests that there is mismanagement in your planning, and the developing team is under immense work pressure.
Let us understand this thing with the help of an example. Here’s a one sample Sprint Burndown Trend Chart.
From this chart, we can conclude three major things:
The throughput metric tracks the total units of work that the developing team completed during a certain period.
For instance, if the developing team aimed to eliminate the bugs present in the software in a sprint, here, on the Throughput metric, you can observe a large portion of recovered tickets that were damaged earlier.
Besides, this particular metric has the capability to identify when the team is blocked. The throughput metric score normally drops down during this period.
You can also get an idea when the developing team is overloaded by comparing the current workload against the average workload.
For example, a team is completing 20 issues per person per month with an average time of 5 days, then the throughput will be 100 for that team.
Cycle Time is an extremely popular metric often used to record the total amount of time from the very moment when the work is started on a specific domain until its completion.
The basic purpose of using this metric is to estimate at which rate you are able to provide new features to your customers.
You can also compare speed for different tasks using this metric and gradually improve upon them.
Besides, Cyber Time offers an innovative solution to find out the weak points of your team, which are affecting the overall performance.
As a result, you can fix these aspects and offer a faster solution to your customers and reach their expectation level.
For example, if you works start on 15th Oct and it ends on 22nd Oct, the cycle time to complete the work will be counted as 7 days.
Lead Time is one of a kind metric which has shown an unprecedented growth in the modern software developing sphere.
The Lead Time metric measures the difference between the software’s definition of a particular feature and its accessibility to the end-users.
This metric showcases how your software developing team is performing by now. If the result is not suitable as per your requirements, you can consider making changes in your developing team or amend the planning part.
For example, CCD is taking an order of 50 coffees a day and takes them around 5 hours to deliver all the orders. Then, the lead time will be 5 hours. If they want to decrease the lead time, then need to complete their task faster.
MTTR is also known as mean time to repair. In every software you make, there is always a chance of mistake or bug, and it is your responsibility to provide a solution for them.
In an ideal condition, you are expected to offer a quick fix solution, as more often than not, the software is in its production stage. MTTR is also used to determine the Software Testing Trends of the modern era.
The mean time to repair (MTTR) metric measures the time period you are taking in order to deploy the fixes for the software. The lesser time you take, the better result you expect in the long run.
For example, if you have spent a total of 100 hours on unplanned maintenance and during that 10 times failure has occurred, then MTTR would be 10 for this particular case.
Code Coverage is one of the very few widely accepted and efficient metrics available in the market. This metric keeps a vigilant eye on the total amount of codes that are measured in Lines of Code (LOC), which is covered by a unit test.
For example, if your software contains 1000 lines of code and out of that, only 500 lines are validated in the software, then the code coverage will be 50%. You should aim to increase the code coverage for your software.
Bug Rate metric evaluates the efficiency and quality of your developing team by measuring the bugs available on the software or while adding a particular feature. Generally, this metric calculates the average bugs generated while deploying a feature.
If you want a long term success and add a brand value to your firm, you should use this metric.
Having a number of bugs is enough to develop a bad impression for your firm. It shows your casualness and puts a question mark on the developers you have.
Besides, by using Bug Rates, you can get application health statistics and get an insight into some of the most important aspects of an application, such as response time, garbage collection, error count, transaction, CPU utilization, disk space, thread count, and the long list will go on.
For example, you have developed 25 test cases and during that 5 bugs have been reported, then the bug rate = 5/25 * 100 = 20%.
In the process of software development, sometimes, you will find an instant change in the previously planned schedule.
In such cases, more often than not, there is a disturbance in the flow of the and waste of your valuable time.
However, for the betterment of the project, you should be flexible and amend as per the requirements of the client.
Task Volume is an efficient metric that records the number of works that your software developing team can complete when they face an unexpected change. This tool also compares these works with the work in a normal environment and with average estimation.
For example, your team is able to complete 10 tasks in a month while handling unexpected changes. Now, for a normal scenario, the average estimate is 12 tasks, then you’re doing pretty well.
Getting a relatively higher number in the Recidivism metric simply suggests one thing. Someone who is in the workflow did not have a similar standard in comparison to someone who is in downstream.
As a result, it can be a decent indicator of inconsistent sets of requirements that you should investigate.
It measures a number of aspects, such as velocity, lead time, development time, and record the time period that your team is taking in order to complete the latest change in requirements. A firm having a flexible group of developers is more suitable for this metric.
For example, If the programmer has a recidivism rate of 9%, then 9% of the bugs solved by him/her comes back after a cycle. So, the less the recidivism rate, the better your software development team is.
Open/Close Rates is one of the most important agile process metrics. Once the developed application is in its production stage, issues like bugs are most likely to occur.
Though it gives a negative impression on you, you have the option to fix it faster and do some damage control.
By using the Open/Close metric, you can effectively track the number of issues reported during the production stage. You can also know how fast you are fixing them in a specified time period. However, here, the general trend makes more impact than the number you got.
At some point in time, the software will experience a crash. There are multiple reasons behind it, such as bugs, optimization problems, lack of updates, lack of hardware support, and so on.
However, it is the frequency that really matters the most in the real-life environment. The users appreciate those applications that crash less often.
Application Crash Rate metric is somewhat similar to the Mean Time Between Failure (MTBF) and Mean Time to Recover (MTTR) metrics.
Application Crash Rate metric is nothing but the number of crashes divided by the number of times you used the software. If you are getting a lesser number in this metric, it is better for you.
For example, if you have used the software for 10 times and there are 4 cases of crashes, the Application Crash Rate would be 40%.
Software quality measurement can be an extremely tricky affair. The majority of the firms prefer soft metrics; some of such Software Quality Metrics Example are revenue growth, customer satisfaction, etc.
No offense to these metrics, these inputs are indeed valuable, but as a software developing firm, it is important to track the number of defects that went to production.
By using the Defect Trend metric, you can calculate the number of bugs that escaped to the production stage. It will truly measure the quality of software that you are offering.
You can put a little additional effort and eliminate any probable chances of bugs entering the production stage. Once you find a bug, it is advisable to address it as soon as possible.
For example, if a software team finds 10 bugs within a cycle and when the software moves to the production stage, there still 3 bugs found, then the defect ratio will be 30%.
The cumulative Flow metric is a graphical representation of different kinds of tasks at different stages of the software development project. The X-axis in the graph represents the dates, while the Y-axis shows the number of story points.
The basic purpose of the Cumulative Flow Chart (CFC) is to provide an easy visualization of the tasks. The task performed in each stage of software development.
There are as many as three different categories for the tasks available in the graph. They are complete tasks, in progress, and to-do tasks.
Though there are a number of code complexity measurement metrics available. Very few can match the effectiveness of McCabe Cyclomatic Complexity Metric.
By using this particular metric, you don’t need to estimate the complexity of the code just by looking at it.
McCabe Cyclomatic Complexity Metric makes the code readable for the developers. As a result, in the long term, it will not become a problem to amend the code.
Even a number of organizations are terminating code if it does not pass the McCabe Cyclomatic Complexity Metric test. Besides, it helps during the code review process.
The agile methodology for software metrics is the best approach for modern-day software development.
However, you are required to know how to use them in an efficient manner. Here are three such agile principles that can offer you a significantly better overall experience.
In most cases, the management is the body that imposes these metrics, which is not efficient at all. According to this principle, the metrics should be imposed by the team of developers only.
As a result, they can easily assess their performance and improve their own standard, as per the need of the software. It will also eliminate any potential chances of miscommunication.
You need to understand that metrics are nothing but a number. Therefore, for the best-case scenario, you need to include them in the conversations and discuss them in the team meetings.
As a result, you can get an in-depth knowledge of the challenges that the team needs to overcome.
More often than not, the management or even the developing team uses metrics for the measurement of the software, which is not the right approach.
The basic purpose of metrics is related to software improvement. As a result, the software developing team needs to use these metrics with a hypothesis in mind.
If you observe carefully, you will find that in the traditional software projects, the software is quantified by estimates. Besides, the specification of the software would reach the required level of the users.
However, more often than not, this was not the case, and specifications were unable to meet the expectation of the end-users.
The inefficiency in the traditional waterfall software projects shifted the emphasis into in-process measurements, such as Lines of Code (LOC), man-months or active days, and so on.
Therefore, in the agile software development projects, developers put more focus on outcome metrics, such as completion of story points, customer satisfaction, and production defects.
As you might have already understood the importance of Metrics in Software Engineering. It provides much-needed assistance to the developers in order to improve the overall experience of the software.
One can use it to detect the bugs, the efficiency of workers, measuring code complexity, software quality measurements, etc.
However, you should check your requirements and then deploy software developing metrics accordingly.