What are the most cost-effective ways to ensure software quality assurance?

Ask adequate questions to understand the requirement fully and focus on obtaining the accuracy for the items below: Detailed SRS documents ensure requirements are unambiguous. User stories bring clarity from the user's perspective, guiding development. RTMs link requirements to deliverables for full traceability. Priorities help in resource allocation. Prototypes act as early visual confirmations. Business processes contextualize requirements in real workflows. Data and System models provide a clear blueprint for developers. Change requests document adaptations Stakeholder sign-off locks down the scope, ensuring all parties are aligned. Expect the unexpected and establish a proactive contingency plan to manage potential risks.

Automate repetitive testing tasks, conduct thorough code reviews, and implement continuous integration to catch issues early. Additionally, invest in comprehensive test plans and training for your QA team. Regularly update documentation to maintain clarity and consistency in your processes.

Software quality is defined by user requirements and standards regulate if these requirements are met. Testing is the main component to check and validate software quality as per user demand. And, launch of beta version is the best step to check how users feel about it. Let the users test it live and give their feedback on it. In parallel keep updating and don't forget to do white-box testing as well on developer's end as well for performance check and quality code.

Here are key strategies: Agile Methodologies: Adopt Agile for iterative development and early defect detection. Automated Testing: Use tools like Selenium for efficient, repeatable testing. CI/CD Pipelines: Implement Continuous Integration and Deployment for regular, automated testing. Peer Reviews and Pair Programming: Encourage code reviews and pair programming for early error detection and knowledge sharing. Static Code Analysis: Utilize tools like SonarQube to identify potential issues early. Test-Driven Development (TDD): Write tests before code to ensure a testable and robust codebase. User Feedback and Beta Testing: Involve end-users for real-world testing insights.

In my experience, defining clear and realistic requirements are fundamental to software life cycle and testing life cycle both. Also, it’s imperative we revisit them at different phases to ascertain what we are building is akin to what was defined as a feature. Acceptance criteria in the user stories becomes the key tangible item for both Dev & QA

Improve software quality assurance by embracing agile and iterative methods in development. These methods emphasize delivering functional software incrementally, adapting to changes, and ongoing collaboration with stakeholders. By adhering to these principles, you can reduce the risks and costs associated with software defects. Early and frequent testing, rapid issue resolution, and continuous value delivery to users are the advantages of adopting agile and iterative approaches.

In my agile projects, I've seen QA significantly improved by: Embedding SQA practices into every sprint from the start. Automation tests and CI/CD tools have been a game-changer, allowing us to focus on intricate test cases and rapid releases respectively. Cross-team collaboration has enriched our testing, uncovering nuances early on. Start with high-point stories as if they fail, reassess and adapt, embody Agile’s “fail fast” approach that ensures, any detours are quickly corrected before moving on to next story. Risk-based testing guided us to allocate efforts wisely, and constant user feedback loops ensured our product evolved in the right direction. Reflecting on past defects has been helpful in refining our QA strategies.

As much as agile and iterative methods ensure the collaboration and quality of the product, it also brings in the much dreaded 'scope creep'. This inturn takes the product life cycle through unnecessary transformations that wasn't planned in the first place.

By doing:Early Testing,Automated Testing,Code Reviews,Regression Testing,Performance Testing,Regression Testing,Continuous Integration (CI) and Continuous Deployment (CD)

Not only agile methods but going a step further, the adoption of principles as mentioned in Accelerate can continue. Something that significantly improved the quality of the teams I lead, and consequently reflected in the quality of the produced code, was the adoption of engineering and business metrics, including the Four Key Metrics. Teams that embraced indicators such as MTTR, Lead Time, defect rate, latency, availability, conversion rate, end-to-end, among others depending on the context, experienced a considerable enhancement in the quality of their deliveries. Moreover, they optimized their processes through strategies that encompass the capabilities outlined in the Accelerate model.

Automation should focus on few basic tenets: - Reduce repetitive tasks - Realistic use cases identified to be automated - Less point of failures - Focus on systemic and End-to-End scenarios. In the industry we see scenarios where investment is being done on automation mindlessly with the aim of reducing resourcing. The focus should be on automating actionable, repeatable and point to point scenarios to begin with. You can’t automate everything!!

Automated testing is a great way to ensure quality of a software without spending big bucks. Automated testing should be implemented in layers. A basic suite should be configured which can be run on developer's machine to ensure the usual issues are not push to remote system. A functional suite should be executed before a code is merged in main branch to ensure it is compatible. This is usually executed when a merge request is raised. Once a code is merged a final functional suite should run to generate a full report of the new version with all use cases or business functions available. This will ensure a viable build is ready for UAT testing.

Automated testing has a direction correlation with an organization's software development maturity and it heavily influences the DORA metrices. A strong automation suite ensures companies moving towards continuous deployment and deliver high value to its customers. But it's hard ain't it ? The requirements keep changing and that consumes so much energy and time automation same thing over and over again. That's where I suggest using AI based automation that is adaptive to changes on Xpaths, class selectors and with a no code approach pretty much anyone including the product managers can produce automation tests. This strategy has helped me achieve a high performance CD pipeline.

Code reviews involve peers inspecting each other's code for defects, adherence to coding standards, and overall quality. This collaborative approach not only helps identify and fix issues early but also promotes knowledge sharing within the development team.

Adopting tools with this purpose is highly positive when embraced as a culture of monitoring and continuous improvement within the team. Using them not only for analysis in the development cycle but also as a routine where the team can delve into applications within their domain, generate actionable insights that reflect in the backlog, and benefit from the learnings.

Typechecking, linting, security and best practices analysis are your best friends. Everything that monitors your code before it is pushed anywhere else from your local environment is an absolute code hygiene this days. The trick is too tailor the analysis rules so that you get errors only on the parts that you wouldn’t ignore. When static analysis is perceived only as formality / white noise, it does more bad than good.

UAT shouldn’t just be a formal sign off vehicle. We should focus on as much client engagement and feedback to reduce defect leakage into production. Also, it’s critical to validate integration tests. These tests should be linked to acceptance criteria and defined in collaboration with business owners. Product team should be POC with clients to gauge user feedback and close out the loop. This is the stage where the product becomes a reality.

Leverage the Strong proxies and deployment strategies like canary deployments for rolling out features to a subset of users in form of AB tests. There are tools that allow you to achieve this like Istio proxy.

Here are some strategies to maintain a cost-effective software development culture: Agile Methodologies: Adopt Agile for iterative development and early defect detection. Automated Testing: Use tools like Selenium for efficient, repeatable testing. CI/CD Pipelines: Implement Continuous Integration and Deployment for regular, automated testing. Peer Reviews and Pair Programming: Encourage code reviews and pair programming for early error detection and knowledge sharing. Static Code Analysis: Utilize tools like SonarQube to identify potential issues early. Test-Driven Development (TDD): Write tests before code to ensure a testable and robust codebase. User Feedback and Beta Testing: Involve end-users for real-world testing insights.

Make sure you hire the right talent to do the work. Look for proven experience in the problem space being addressed. Do your reference checks, don’t just hire or bring in a third party just because you like their vibe! Then again do resource people for cultural fit with your team or organization. People that get on well together are more productive. Don’t try and do software development that your own people aren’t experienced at. Team them up with experts to help their skills development.

In my experience, it’s usually best to start testing early to ensure some issues don’t morph into bigger problems later on…the dev team MUST write unit tests for all their tasks even before embarking on the traditional end to end tests.

Implementar testes por etapa, de modo a aumentar a qualidade do software desenvolvido. Cada etapa, desde o teste unitário até o teste funcional deve ser testado de forma a agregar valor e diminuir a quantidade de testes funcionais necessários. Tornando assim o software manutenível.

Maintaining documentation, such as architecture decisions, "as-is" and "to-be" views, is also a relevant consideration that contributes to code quality improvement. The practice helps identify bottlenecks and challenges, provides a current understanding of the system like data flows, components, and integrations, facilitates decision-making, and offers numerous other benefits. Making documentation a part of the deliverables also contributes to enhancing team knowledge.