March 22, 2024 By Meenakshi Hora 4 min read

Quality Assurance (QA) is a critical component of the software development lifecycle, aiming to ensure that software products meet specified quality standards before release. QA encompasses a systematic and strategic approach to identifying, preventing and resolving issues throughout the development process.

However, various challenges arise in the QA domain that affect test case inventory, test case automation and defect volume. Managing test case inventory can become problematic due to the sheer volume of cases, which lead to inefficiencies and resource constraints. Test case automation, while beneficial, can pose challenges in terms of selecting appropriate cases, safeguarding proper maintenance and achieving comprehensive coverage. Defect volume is a perpetual concern, impacting software quality and release timelines.

Overcoming these challenges demands a thoughtful and proactive approach to streamline test cases, optimize automation effectiveness and minimize the volume of defects in the QA process. Balancing these aspects is crucial for delivering high-quality software products that meet user expectations and industry standards.

How IBM helps

To reduce test case volume, it’s essential to focus on test case optimization. This process involves identifying redundant or overlapping test cases and consolidating them to cover multiple scenarios. Prioritizing test cases based on critical functionalities and potential risks to streamline the testing effort is also important. Additionally, leveraging risk-based testing allows teams to allocate resources where they are most needed, optimizing coverage without compromising quality. Test case automation effectiveness can be enhanced through careful planning and continuous maintenance.

Another way is to choose the test cases wisely for automation, focusing on repetitive, time-consuming and critical scenarios. It is also necessary to regularly update automated test scripts to adapt to changes in the application, making sure they remain relevant and reliable. A proactive approach for defects involves implementing robust testing methodologies, such as shift-left testing, where testing activities are initiated earlier in the development process. Conducting thorough code reviews, employing static analysis tools and emphasizing collaboration between development and testing teams to catch and address defects early.

IBM® brings in all this through The IBM IGNITE Quality Platform (IQP), which is a DevOps-enabled single sign-on platform that leverages AI capabilities and patented methods to optimize tests. The platform brings in shift left methodologies that promote faster automation with healing capabilities and predict and prevent defects, which in turn drive high-quality delivery that supports the end to end testing lifecycle of an organization.

It consists of the following pillars:

Administer:

Supported through an Integrated Platform that manages multiple tenants, users, applications, projects and all necessary functional and technical configurations needed across the testing journey, centrally at one place. Likewise, it supports quality plan journey that aims to reduce defects. It is also integrated with quality recommendations that flow in from other components and multiple third-party integrations, which include leading git-based repositories, test and defect tools and cloud-based web and mobile testing tools

Optimize:

Aimed towards creating the optimal set of testcases with 100% coverage and bring in a shift left in surfacing defects early.

  1. Requirement analytics (RA): NLP-based tool for analysis of requirements to identify ambiguity, drive in shift left and determine complexity. It also aids semi-automatic identification of key attributes for the optimization journey.
  2. Search tag & model (STAM): Text-based analytics tool for quick analysis of a huge number of existing tests to identify redundancy and identify key attributes for the optimization journey.
  3. *Optimization (TO): *Combinatorial Test Design Methodology-based tool that enables building an optimized test plan with maximum coverage from existing requirements, existing tests, YAML and even relational data. Also includes reusability via attribute pool and functional context modelling concepts.

Automate:

Aimed to quickly generate and automate and execute multiple tests unattended on various data, environments and platforms.

  1. Test Generation (TG): Helps generate both TO model-based and nonmodel-based tests, ready for both manual and automated testing. It also supports custom BDD generation for client-based frameworks, automatic BDD script generation through recording mechanism and quick conversion of custom selenium-based frameworks to IQP specific automation.
  2. Optimized Test Flow Automation (OTFA): Cucumber-based scriptless test automation framework supporting automation of Web, Mobile, REST, SOAP based applications, with a built-in test healing capability and integrated Jmeter-based performance testing and visual testing.

Analyze:

Trained in understanding a client’s defect patterns—cognitive test components drive quicker resolution, provides insight, and makes predictions around defects, which in turn gives preventive recommendations across Agile and traditional engagements. It also supports in better planning and reduced test cycles using defect prediction capability.

  1. Defect classify (IDC): Plug-in solution for on-the-go classification and automatic assignment of defects to aid faster defect analysis and resolution.
  2. Defect Analytics (IDA): Designed using defect reduction methodology that understands the semantics of the defects and provides prevention recommendations to reduce them further.
  3. Defect Predict (IDP): Assesses and predicts defect trend in a test cycle aiding better planning and test management.

Our differentiated automation approaches

Prioritizing optimization over automation: This is our strategy to mitigate waste snowball effect by adopting multiple shift-left methodologies. We leverage a modern framework that is Behaviour-Driven Development (BDD) enabled and incorporates low-code practices. Our approach extends to comprehensive automation covering Web, Mobile, API and SOAP-based applications, seamlessly integrated with performance testing.

Embracing a philosophy of continuous testing, our strategy is to intricately weave all functions into the DevOps pipeline, promoting a cohesive and efficient development lifecycle. Beyond this, our commitment extends to cloud deployment and Software as a Service (SaaS) offerings, driving scalability, flexibility and accessibility in a rapidly evolving technological landscape.

Evidence of success of usage of IGNITE Quality and Test

Our primary focus is on driving tangible value to our clients through a strategic approach that involves reducing testing efforts while concurrently instilling confidence in our clients. Our proficiency extends across multiple technologies, which puts in place a comprehensive and adaptable solution that aligns with the diverse needs of our clients. By consistently delivering results and earning the trust of our clients, we have established ourselves as leaders in the industry, dedicated to providing solutions that make a meaningful impact.

Email Amit Singh, Global Sales Leader, Quality Engineering and Testing, for more
Was this article helpful?
YesNo

More from Automation

Deployable architecture on IBM Cloud: Simplifying system deployment

3 min read - Deployable architecture (DA) refers to a specific design pattern or approach that allows an application or system to be easily deployed and managed across various environments. A deployable architecture involves components, modules and dependencies in a way that allows for seamless deployment and makes it easy for developers and operations teams to quickly deploy new features and updates to the system, without requiring extensive manual intervention. There are several key characteristics of a deployable architecture, which include: Automation: Deployable architecture…

Understanding glue records and Dedicated DNS

3 min read - Domain name system (DNS) resolution is an iterative process where a recursive resolver attempts to look up a domain name using a hierarchical resolution chain. First, the recursive resolver queries the root (.), which provides the nameservers for the top-level domain(TLD), e.g.com. Next, it queries the TLD nameservers, which provide the domain’s authoritative nameservers. Finally, the recursive resolver  queries those authoritative nameservers.   In many cases, we see domains delegated to nameservers inside their own domain, for instance, “example.com.” is delegated…

Using dig +trace to understand DNS resolution from start to finish

2 min read - The dig command is a powerful tool for troubleshooting queries and responses received from the Domain Name Service (DNS). It is installed by default on many operating systems, including Linux® and Mac OS X. It can be installed on Microsoft Windows as part of Cygwin.  One of the many things dig can do is to perform recursive DNS resolution and display all of the steps that it took in your terminal. This is extremely useful for understanding not only how the DNS…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters