Quality Experience Metrics An Intelligent Approach to Predictive and Consistent Quality for Enterprises

By Jagadish Anandhan

Software Testing Methodology

Software testing methods are defined as testing strategies and types that ensure the application under test (AUT) meets the customer's expectations. Test methods include functional and non-functional testing to confirm the AUT. Each test method has a defined test objective, test strategy, and test approach.

In software design, software measurement is based on a number of software measurements, and these software measurements are called measurements of different functions of the software. Software quality assurance ensures software quality. Software quality assurance is applied continuously throughout the software development process.

High quality creates an effective and efficient strengthening cycle.


Software Quality Experience Metrics

According to IEEE Standard 1061-1992, A methodology for establishing quality requirements and identifying, analyzing, implementing, and validating the product and process of software quality metrics is defined.

Software quality experience metrics provide a quantitative approach to measuring the quality and efficiency of the software development and testing process. It helps the team monitor software quality at each stage of the software development cycle and also provides information to control and reduce errors.

Quality experience metrics are a subgroup of software metrics focusing on product, process, and project quality aspects. They are more closely related to process and product measurements than project measurements.

Our Offerings

Here at Trigent, we can classify the metrics based on the business outcomes it helps measure.

The image below is a representation of how it can be depicted.


You may want to select metrics that measure different outcomes.

Product Quality

Product quality is how well the product meets customer needs, fulfills its purpose and CX expectations, and meets industry standards. When evaluating product quality, companies consider several factors, such as whether the product solves a problem, works efficiently or suits customer goals.

The following metrics are used to define product quality:

Defect Leakage Analysis (DLA) Metrics - It is used to identify the effectiveness of quality assurance testing. DLA metric helps us identify if we are missing any feature test cases that caused defects to leak to Production. A low DLA percentage means our testing processes are solid.
Test Coverage Metrics - Traceability Traces user requirements covered with test cases. The goal is to have 100% of the requirements covered with tests.
Customer Satisfaction

Customer satisfaction with a product is based on the quality of the product, customer experience (CX), and its services. It reflects the health of your business by showing how well your products or services resonate with buyers.

The following metrics are used to define customer satisfaction:

Out Of Service Level Agreement (SLA) Metrics - When the bugs violate the internal Service Level Agreement, this metric is implemented. This also helps teams proactively prioritize and triage their backlog. These metrics make sure no requirements are violating Service Level Agreements.
Product Health Metrics - These metrics will help you to measure the health of your product as well as the success of your strategy.
Cycle Time (or Speed)

Cycle time measures the elapsed time when work starts on an item until it is ready for delivery.

The following metrics are used to define Cycle Time:

Bug Cycle time - This metric measures when you start working on the bug to when the bug fix is ready to be deployed.
Automation Execution Duration Metrics - This metric measures how long it takes to run automated tests. With the help of Unit Testing, test automation metrics provide a helpful way to determine the return on investment (ROI), understand what parts of test automation are working and what are not, and improve metrics.
Development Quality

Development quality identifies key performance indicators and processes that drive stability through code quality improvement.

The following metrics are used to define Development Quality:

Root Cause Analysis (RCA) Metrics - The point of filing a TPS (Trouble in Production System) is to respond and document the occurrence of any incident. The most important part is holding a post-mortem meeting and carrying out RCA (Root Cause Analysis). The goal of the metric is to measure how successful Engineering is in these best practices.
Code Quality Index (CQI) - Code quality metrics are several variables used to measure and determine if code is of high quality.
Engineering Score - Quality Score is estimated on how well the engineering has performed. Based on Quality Metrics, each product gets a score where a score of 1 is the lowest, and a score of 10 is the highest. This metric will be calculated for the entire Engineering. This will make the teams know about the quality of the software.

Dashboard view of Trigent’s Quality Experience Metrics


Metrics will be calculated weekly and evaluated Quarterly. A weekly engineering score will be calculated per project, as well as an overall engineering quality score. Teams that achieve a badge from scoring in the rubric move on to the following badge. This way, the team can understand and control the quality of the software and ensure it further.


These automated metrics data are pulled from Jira, TestRail, Jenkins execution, and repository to calculate a score that represents the health of the project.



The core aspect of software development and maintenance is software quality metrics. Software quality metrics also relate to the quality of a software development project, such as the procedures you use to design and test software platforms. These quality metrics are the aspects of software development programs that describe usability, efficiency, and functionality.

Software engineering teams usually have a set of metrics that they use during the QA phase to ensure that their software meets all user requirements before releasing the product.


  • Functional Assurance: Applying software metrics ensures that programs work correctly.
  • Meeting Customer Needs: Software quality metrics ensure all features meet customer expectations and needs.
  • Limitation of Errors: By measuring software performance using various metrics, developers can limit the number of bugs post-production.
  • Process Improvement: By gathering information about the quality of software products and processes, developers can develop best practices for development.
  • Attract New Users: When developers use analytics to learn about software quality, they can improve software features such as interface, functionality, and design to attract customers.

Business Needs

Quality Experience Metrics can be used for product-based and service-based clients. The quality metrics allow the customers to see the health of the project. The customer can be a product-based or a service-based customer. Also, it enables you to view the progress of the project.

Quality Experience Metrics enable the customers to see whether Trigent is doing the correct thing at the correct time. It also enables the customer to understand how many issues occur in functional testing, system testing, user acceptance testing (UAT), and post-production. Quality metrics display the time taken to fix these issues and the cost to fix them.

Benefits (Qualitative/ Quantitative)

Starting from a developer to higher management, the quality metrics would provide the time taken for each and every process in the software development life cycle (SDLC) and software testing life cycle (STLC). In turn, this will ensure complete transparency about the project right from the developer to the higher management.

The metrics would also enable a customer to validate and measure the quality of the software (Quality Assurance) based on the number of defects raised by the testing team during the development cycle. Also, this will enable the customer to validate the understanding of the requirement and what a developer has to develop, what a tester has to test, and whether the developer performs testing before sharing the fix or feature with a tester. A customized auto-generated email can be sent to all the stakeholders/customers to view the status of the project.

In the end, Trigent is able to generate a fully automated report without any manual intervention. Also, the customer is able to integrate the CI/CD pipeline with a dashboard that will display all types of quality metrics and project scoring according to the customer’s needs.


A dashboard with insights into all data points(Metrics) that are accessible to everyone.


List the technologies and components used in the solution are as follows:

  • Google spreadsheets
  • Github - Quality Metrics tool code (Python)
  • Jenkins - CI/CD
  • Grafana - Data display Dashboard (popular tools splunk, datadog)
  • Data source - Jira, Testrail

Note: Flexibility to use any tool as per client’s requests