Software Defect Management: Overview, Best Practices & AI Impact
Software defect management is a critical part of the software development cycle. In contrast to the software testing phase, software defect management starts with the delivery of software and requires careful logging and analysis of errors. Timely response and remediation of these errors, prevents new defects from being introduced, removes existing bugs from the product and adds knowledge to the system to improve its quality in the long term.
What is Software Defect Management?
Software defect management is a term that describes a defined process that software developers use to detect, prevent and remove the bugs in a software. The aim of this process is to ensure that there are minimal defects in the software. Software defect management tools can be used to reduce the number of bugs in the code, thereby improving the software quality.
Types of Software Defects
Software defects are failures of programs to perform as expected. Software defects are unpredictable and can cause a lot of problems. A tested software is supposed to work correctly, but every now and then a bug slips through the cracks. The kind of bugs that occur depend on the stage of development the software was at when it was released:
New code / new functionality : These kinds of bugs arise when you add a new feature or create new code. In this case, you should know what kind of bugs to expect.
Old code : Bugs in old code are much harder to find. You don’t know when or why they occurred, so it’s hard to predict whether this one is still present in your new version of the code.
Unstable environment : Software can also break because its environment isn’t stable enough for it to run as expected. If an application runs on an unstable operating system, for example, it might break because the OS crashes every hour.
There are two types of software defects: functional and non-functional.
- Functional defects focus on a program’s lack of functionality. These include bugs that cause the program to crash or data loss; problems with the user interface; incorrect calculation results and more.
- Non-functional defects focus on the performance of the software, such as crashes, resource usage, load time and response time. If you don’t fix them, they will result in motivating your users against using your product and in the worst case scenario, sub-optimal performance can lead to very unsatisfied or unhappy customers creating a negative impact on your business.
It is important to fix both functional and non-functional issues in order to create an exceptional product that will satisfy your customers’ needs.
Why Is Defect Management Important?
Software defects are always a cause of concern, they can ruin the experience for the software product user and can turn into a nightmare for the software creators. The sooner a defect is detected, the cheaper it is to fix it. Therefore, a defect management process is very important for any organization that develops software products. It is an important part of the software quality assurance activity and aims at improving product quality by reducing the number of defects in software. This is achieved by integrating defect prevention activities into the development lifecycle, configuring defect tracking tools, implementing and educating developers on defect reporting procedures and fixing defects as soon as possible.
Software Defect Management Steps
When a software defect is discovered, the software defect management process begins. The software defect process consists of several steps that are required to be completed before the software defect can be closed. The following steps are the basic outline of the process:
- Step 1: Reporting of the defect
- Step 2: Defect verification and classification
- Step 3: Creation of a defect report (also called fault log)
- Step 4: Defect removal
- Step 5: Test case creation and testing
- Step 6: Post-release review/regression testing/verification
Each organization has its own standards for each step in the software defect management process. The aim is to ensure that defects are detected as early as possible through an effective testing process and that they do not reach production level until it is verified that they have been removed.
How Software Defect Management Tools Work?
Software defect management tools, sometimes called defect tracking tools or bug tracking tools, are used by development teams to manage defects as they are reported. Defects are tracked from their creation through the process of investigation, isolation, verification and resolution.
Testers can use these defect tracking tools to enter new defects, review existing defects and monitor the progress of previously identified defects.
Most popular software defect management tools have features that allow you to:
- Track bugs by creating a “case" for each one. When you create a case for a bug, enter information about the bug such as its type, summary and status. Some software defect management tools allow you to attach files to bugs so other team members can see screenshots or code that demonstrate the problem. Defects can also be assigned to specific team members for further investigation.
- Assign priority levels to bugs and track their progress throughout the life cycle of the project. Set priorities based on your company’s criteria and filter defects based on priority level. Many software defect management tools provide reports that list all high-, medium- or low-priority defects in a variety of ways — by project, by tester or by priority level.
- Create categories for defects and then assign multiple defect cases to one category. This makes it easier for developers to fix the bugs.
Good software defect management tools should be able to do the following:
- Identify every defect in your software
- Automate defect reporting and tracking
- Provide defect prioritization based on impact and cost of repair
- Enable easy communication with customers about known defects and their status
- Inspect for patterns and trends that could lead to new defects
Key Software Defect Metrics
Defect metrics provide a basic way to measure the effectiveness of testing. They can indicate how much effort is necessary for effective test design, execution, and reporting.
Testers can use these defect metrics as an early indicator that their test cases need to be improved. These metrics are also helpful in determining whether more testing is necessary when a project is approaching its deadline. Some of the most common defect metrics include:
Defect Density: It is the number of defects of a type divided by the number of lines of source code (or another unit) containing the defects. The defect density metric is often referred to simply as “defects per KSLOC." Defect density is useful in tracking trends over time and in comparing different products or components within a product.
Defect Severity: It measures how severe a given defect is by using a numbering system. This metric is useful when prioritizing defects, as higher severity defects need to be fixed sooner than lower severity defects do.
Defect Detection Rate: The DDR measures the effectiveness of a given test case at detecting defects in the software being tested. It’s calculated by dividing the number of total defects detected by the total number of tests executed for that test.
Bug Fix Rate: It is the number of bugs discovered in production divided by the number of bugs that have been fixed in the same period. This metric is important because it’s clear whether your team is discovering more defects than they fix and also whether they’re fixing more bugs than they’re discovering.
An ideal Bug Fix Rate would be 1:1, where every bug that is reported and assigned to a developer for fixing is also fixed within the same period.
5 Best Practices or Tips For Effective Software Defect Management Process
The following Software Defect Management tips or best practices will help you manage your defects effectively.
1) Identify the possible defects in the software by reviewing requirements, design documents, source code, test cases and other analysis reports.
2) Review the issues thoroughly and analyze them to come up with a defect report. To ensure that defects are not repeated again, document the defect report and update it periodically.
3) Prioritize each defect based on its impact on users. The priority can be determined based on severity or priority, risk or occurrence probability, or user impact as well as other such criteria.
4) Document all defects and provide to respective stakeholders who can fix them. Also, schedule a status review meeting with them to identify the status of these defects and their progress which will help you know if they have been resolved or not.
5) Make sure that all defects are thoroughly tested before releasing.
AI in Software Defect Management
The purpose of the software defect management process is to find the defects in software during its development and testing stages before the software product reaches the hands of its users. The main challenge in software defect management is that it is difficult to ensure that all the defects in a large software project are found.
The use of artificial intelligence for software defect management helps overcome this challenge by providing automated tools for testers to find and fix defects quickly. Artificial intelligence can be used to learn the usage patterns of users as they use the software to understand happy path scenarios and scenarios that lead to failures. Such a learning process can help in identifying an error as it occurs and assign a criticality level to the issue. This helps in reducing the crucial amount of time spent in triaging and assigning defect severity to an issue. Over time a well trained algorithm can learn patterns of usage to predict defects and errors before they occur. While AI can definitely not replace a well trained QA expert yet, it can help with identifying patterns of usage in a live application where software teams depend on manual error reporting to identify issues in a reactive manner, enabling a proactive approach to identifying issues and mitigating problems for the end user.
An AI enabled defect detection process in a live environment provides a great benefit to software development and QA teams by allowing them to focus their efforts in improving the overall software development process with real-time feedback about issues experienced by users, improving the overall productivity of the teams while also improving the user experience of the customer.
Qualetics: Your AI enabled Software Quality Analytics and Defect Monitoring Platform
At Qualetics, we believe that AI enabled defect management is not only possible but also a viable approach for software development teams today. That’s why we have built an AI driven Software Quality Analytics platform that can help you improve your software product quality and your end user experience.
Our platform helps you collect data from multiple sources and process it in real-time to extract actionable insights such as your software product’s quality index and defects experienced by users segmented by application features and products. Our self-learning algorithm also constantly monitors activity across the application to identify defects and assign a severity index to alert the software development and product teams about issues experienced by users in real-time.
To learn more about our AI Platform or to book a demo, contact us here.
