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thedigitallover · 4 months

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Effective Software Quality Assurance

Effective Software Quality Assurance (SQA) is pivotal in ensuring the delivery of high-quality software products. Several principles guide the successful implementation of SQA processes, fostering a culture of excellence and reliability throughout the software development lifecycle.

Early Integration of SQA: The foundation of effective SQA lies in its early integration into the software development process. By embedding quality assurance from the project's inception, teams can identify and address potential issues at the earliest stages, minimizing the impact on later phases. This proactive approach not only reduces the cost of fixing defects but also enhances overall product stability.

Comprehensive Test Planning: Thorough test planning is a cornerstone of SQA. This involves defining clear objectives, scope, resources, and timelines for testing activities. A well-structured test plan ensures that all aspects of the software, from functionality to performance and security, are systematically evaluated. Test planning should be adaptable, considering changes in requirements and project dynamics.

Adherence to Standards and Best Practices: Following industry standards and best practices is essential for achieving consistency and reliability in software development. This includes adherence to coding standards, documentation practices, and testing methodologies. Consistency in applying established norms fosters collaboration, eases knowledge transfer, and contributes to the creation of maintainable and scalable software.

Continuous Process Improvement: Software development is an evolving process, and SQA should reflect this dynamism. Continuous process improvement involves regularly assessing and refining SQA processes to enhance efficiency and effectiveness. Feedback loops, retrospective analyses, and metrics tracking contribute to the identification of areas for improvement, allowing teams to adapt and evolve in response to changing requirements and challenges.

Risk-Based Testing: Prioritizing testing efforts based on risk is a fundamental principle of SQA. By identifying and assessing potential risks, teams can allocate resources more effectively. High-risk areas receive more extensive testing, ensuring that critical aspects of the software are thoroughly validated. This risk-centric approach enables teams to focus on delivering a product that meets both functional and non-functional requirements.

Automation Integration: Automation plays a crucial role in streamlining repetitive and time-consuming testing processes. While not all testing activities can be automated, incorporating automation where feasible enhances efficiency and test coverage. Automated tests facilitate rapid feedback, enabling quick identification and resolution of issues. However, it's essential to strike a balance and recognize scenarios where manual testing remains indispensable.

Collaboration and Communication: Effective communication and collaboration between development, testing, and other stakeholders are vital for SQA success. Clear channels of communication ensure that everyone is on the same page regarding project goals, requirements, and changes. Collaborative efforts foster a shared understanding of quality objectives, promoting a collective responsibility for delivering a high-quality product.

In conclusion, embracing these principles forms a robust foundation for effective Software Quality Assurance. By prioritizing quality throughout the development lifecycle, teams can consistently deliver software that meets or exceeds user expectations, ultimately contributing to the success of the overall project.

#effective Software Quality Assurance #Software Quality Assurance #sqa

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sbscglobal · 6 months

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#cloud-based software #global software development #industry specific solutions #enterprise software development #ecommerce #ecommerce solutions #it solutions for healthcare #full-stack development #it consulting #it solutions for finance #Software Maintenance and Support #IoT Software Development #Software Quality Assurance #Top Software Developers #IT Outsourcing Services #Mobile App Development #Web Application Development #Full-Stack Development

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agilesyseng · 10 months

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Jama Connect: Batch process user license changes

Sometimes, software is well design and has useful features, which are well document.

I was pleasantly surprised by Jama Connect, the software that I've used both at SKAO and ALMA to manage requirements. I tried to change many licenses at once... and just by searching on the help for batch process user licenses I got to this help page:

(By the way, how many software packages have open, linkable help? Yeah, not that many!)

And surely enough, I just followed the instructions and it worked!

How bad is our general environment when something so basic works... and it amazes us?

#SystemsEngineering #RequirementsManagement #JamaConnect #software #software quality assurance

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mariasuzie23 · 3 days

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DataEdge, which specialises in software testing and QA services, uses cutting-edge testing tools to help businesses deliver high-quality software applications on time.

#software testing services #quality assurance #software testing services usa #software quality assurance #software testing and quality assurance #software quality assurance services company

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nitor-infotech · 10 months

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Quality Engineering Roles and Responsibilities

Quality engineering roles and responsibilities involve ensuring the quality and reliability of software products throughout the development lifecycle.

Here are some common roles and responsibilities within quality engineering:

Quality Engineer/Analyst:

Develop and execute test plans, test cases, and test scripts

Identify and track software defects and issues

Conduct various types of testing, including functional testing, regression testing, performance testing, and security testing

Collaborate with cross-functional teams

Automate test cases using test automation frameworks and tools

Analyze test results, generate test reports, and provide recommendations for improvements and enhancements

Test Automation Engineer:

Develop and maintain test automation frameworks and infrastructure

Design, develop, and execute automated test scripts

Collaborate with development teams

Identify opportunities for test automation

Monitor and maintain automated test suites

Conduct code reviews for test automation scripts

Analyze test automation results and provide feedback

Performance Test Engineer:

Design and execute performance and load testing strategies

Identify performance bottlenecks, scalability issues, and potential areas for optimization

Develop and maintain performance test scripts, scenarios, and test data

Use performance testing tools

Analyze performance test results, identify trends, and provide recommendations for improving application performance

Collaborate with development and infrastructure teams

Security Test Engineer:

Conduct security assessments and penetration testing

Perform security testing activities, including threat modeling, security code reviews, and security-focused test case development

Use security testing tools to identify and exploit security vulnerabilities, such as OWASP ZAP, Burp Suite, or Nessus.

Collaborate with development teams

Stay updated with security threats, vulnerabilities, and industry best practices to ensure the security of software applications

Test Manager/Lead:

Plan, organize, and manage the overall testing effort for software projects

Define testing strategies, methodologies, and best practices

Coordinate and prioritize testing activities across multiple projects or teams

Allocate testing resources, monitor progress, and ensure timely delivery of test deliverables

Manage test environments, test data, and test infrastructure

Provide leadership and guidance to the testing team, mentor junior team members, and foster a culture of quality and continuous improvement

Quality engineering professionals are expected to have good communication and collaboration skills, critical thinking abilities, attention to detail, and a continuous learning mindset to stay updated with evolving technologies and industry trends.

Learn more about our Quality Engineering services - https://bit.ly/3JADGtr

#quality engineering #quality assurance engineer #data quality #software quality assurance

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imonitor · 1 year

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How Quality Assurance Software Ensures Superior Product Quality?

quality and takes you one step closer to achieving continuous improvement. But what exactly is software quality assurance, and how can it help your business?

Traceability and visibility

Traceability and visibility are two key components of quality assurance software. They provide an overview of the entire production process, from raw materials to finished products, so that you can easily trace any errors or inconsistencies back to their source.

You can use traceability data to identify potential improvements in your manufacturing process by comparing it with other similar projects or benchmarks--and then implement those changes immediately.

For example, if you notice that your new product line has higher rates of defects than others in its category (or even other products produced by different companies), this could mean that there's something wrong with either your design or production process; using QA software will help pinpoint exactly where these issues lie so that they can be resolved as soon as possible!

Automated testing

Automated testing is a type of software testing, which involves the use of software to control the execution of tests and the comparison of actual outcomes to predicted outcomes. Automated testing can be used to test all levels of an application, including requirements, design, and code.

The advantage of automated testing is that it provides consistent results by running tests repeatedly in an automated fashion.

Collaborative reporting

One of the most important features of quality assurance software is collaborative reporting. This means that all team members have access to the same information and can share their findings with each other, which leads to better communication and decision-making. Collaborative reporting also allows you to track data in real time so that you have an accurate picture of what's happening on your project at any given moment.

Continuous Quality Improvement

Continuous Quality Improvement (CQI) is a process of improving the quality of products and services in an ongoing manner. The goal is to make sure that defects are prevented, rather than detected after they have occurred. In other words, CQI ensures that you are constantly making improvements toward delivering better products or services for your customers.

The first step towards implementing CQI is identifying what needs to be improved and why it's important for your business. You can then set goals for yourself as well as specific targets that need to be met in order for these improvements to take place successfully. Once these goals have been set out clearly and everyone involved knows what their role is within this process, it's time for them all to work together towards achieving those targets!

Conclusion

Quality Assurance is the process of ensuring that products, services, and processes meet customer requirements. It involves testing a product or service to make sure it meets specifications and standards. Quality assurance can be defined as a set of activities or procedures carried out at different stages in the production cycle to ensure that quality standards are met throughout the whole process. Quality assurance software provides a complete overview of the current state of your product

Source Link: https://qualityassurancesoftwarenz.blogspot.com/2023/04/how-quality-assurance-software-ensures.html

#software quality assurance

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qprofessionals · 18 days

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Empowering Businesses through Software Quality Assurance

In today's hyper-competitive business environment, the quality of your software can make or break your success. That's why at Quality Professionals, we're dedicated to empowering businesses with top-notch software quality assurance services. Our comprehensive approach to QA ensures that your software not only meets but exceeds industry standards for reliability, performance, and security. With Quality Professionals on your side, you can unleash the full potential of your software and drive your business forward with confidence.

#software testing services #quality assurance software #software companies #automating testing #qa consulting companies #mobile application testing #mobile app testing services #software quality assurance

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scvnthorpe · 1 year

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No seriously, Focus on Testability

How preparing to test leads into everything else

(No but seriously, I can't find any currently existing tags for test driven development. Testing yes. TDD no!, apparently not!)

So, why isn't TDD the norm?

Now, this is important. TDD gets a lot of praise in theory, but does that mean it's the actual norm for what people do? Consider the following:

It’s embraced as a way to maintain high code coverage and write better code, and 41% of the developers who responded to the survey said their organizations have fully adopted TDD. However, when asked the same question in a slightly different way (“How often do you write tests before writing the code under test?” — the definition of TDD) only 8% of developers said they do this at least 80% of the time.

Something's kinda sus: why, if TDD is so highly regarded as a standard, aren't more people actually doing it?

People often say it slows them down in terms of productivity, but research indicates that this simply isn't the case! My guess is, it feels like a lot of upfront thinking for a lot of people to do. You have to know, somewhat, what it is you want to do and what the broad structure of messages within your program is going to look like (and believe me, that can change suddenly and dramatically especially if you're working with shit you've never really used before). Cue flashbacks to horrific UML sketching exercises and Waterfall esque development lifecycles.

Seriously, fuck that shit.

But it's also true, particularly in fields where automated testing period just isn't as universally accepted (yes, AAA games. It's AAA games), that many environments see Dev and QA/testing as separate software design concerns to be handled by separate teams a bit like how many people see Dev and Ops as separate concerns in software delivery. So, why make development do the testing in the first place? Where does QA fit into this? Apart from the fact that we've already established that leading with automated tests can increase the speed and quality of your work, the fact is that QA are some of the most overworked and under-loved parts of the industry. Leaving at least the unit and feature tests to the devs (because trust me, there are several levels of testing you can do) leaves more than enough higher-level testing and well, quality assurance, for QA to do.

Of course, these are just two major detractions to TDD proper that I wanted to clear up, but once one has decided on TDD there's also a litany of places where I've personally experienced friction. But, not only can these problems be overcome, but implementing all of the workarounds involved creates a battery of happy little accidents for your architecture.

So now, I'm going to cover some of the discoveries I've made while working through various issues in code testability.

1 - Smaller components are easier to simulate

Now, here's the kicker. The bigger a unit of code and the more complex the logic is, the harder it is going to be to change or to apply to novel problems within your project. Back in my bootcamp days I can remember working on a toy project to simulate a bank account - bank statements and all - and feeling like I was struggling to really grasp how to mock out the printing of a bank statement! As it so happened there were a bunch of dependencies on the internal state of the bank account object itself, such that in order to verify the correctness of the bank statement you'd need to know the internal state of the bank account itself. At the time I found the testing framework's tools for mocking/stubbing way too limited in the complexity of their behaviour, but you also shouldn't be reaching into internals to test shit to begin with! That's a recipe for brittle tests that don't permit radical change.

However, things really clicked into place when a colleague suggested I make the bank statement into a new object.

This not only gave me the opportunity to test bank statement functionality as an isolated unit, but also meant I could just stub out the bank statement functionality when testing the main bank account object!

But of course, stubbing out different parts of your program and doing injection to achieve isolation in this manner can be a real damn pain in the ass if operating under the classic OOP style. So if you ever find yourself blaming TDD (or even just testability) to be the problem, sometimes you should consider a solution...

1.5 - An aside on testing with time

But first, I'd like to mention that a tricky dependency with code testing is time. Now, there are a number of libraries for pausing or otherwise modifying time in a test environment - timecop for Ruby, freezegun for Python - and I've reached for these whenever I've needed to test some time gap, as far as feature testing goes at least. However, maybe there's a better way? Instead of reaching in and pausing time itself in the program's environment, perhaps we could have an object passed in from which to get the time - with the standard time object as the default - and inject a stub of this object when testing? In fact, in many cases maybe we'd rather inject a function to be called to get the current time rather than a whole ass object? Speaking of which...

2 - Consider mixing up your paradigm

As we've seen hitherto, the smaller and more straightforward you make individual components of your system the easier it is to swap them out with inert copies when it comes to testing: this allows you to test certain classes in isolation even if they usually require members of some other class in order to function in the wild as previously seen, but can also work with other dependencies such as RNG or time.

However, there comes a point where fucking around with injecting dependencies, class instances and object state simply doesn't yield enough benefit for the additional overhead.

From my own experience building a rather simple income tax calculator, I used a singleton instance to take the tax bracket configurations and then calculate the resulting tax given the income provided. Said singleton was also storing the result in an instance variable which was causing problems for subsequent tests with this same instance, which is where I realised I'd be better off incorporating a more functional approach in this case.

In functional programming, the focus is on producing units of code that always yield the same output given the same inputs and as such one doesn't deal in mutable state at all. This makes such code a natural candidate for terse tests that get right to the point without as much (or any) auxiliary setup.

Moreover, it's possible to pass dependencies at the point of call as you would any other argument in order to modify the behaviour: in fact, when the dependency in question is a function, the function being called is known in the functional programming world as a higher-order function. Likewise, in a test environment you can simply pass a 'stub' version of the function depended on at the time of calling. Thus, dependency injection, and thus stubbing/mocking, becomes a little easier too for the absence of instantiating other classes within a class and other such clusterfucks.

Besides, often the best OO programming begins to look a lot like functional. Seriously, google that shit.

3 - A little abstraction loosens a lot of coupling

I must admit, this next solution isn't something I've actually implemented but it is one that lives with me to this day.

For this one, I'm reminiscing on my days working with SQLAlchemy. What would tend to happen is that I would get the database session object directly, pass it into another object with data relating to the incoming HTTP request, and then call the method on that object which related to the SQLAlchemy query that was needed to perform the appropriate database operation. Now, I'd say this is a decent amount of abstraction; I and the others I was building this thing with could keep all those queries somewhere other than the main file defining the API endpoints.

But testing was a whole different beast: here, we essentially needed to prepare a test database (which is common practice) and because we were using something quite lightweight in development it actually wasn't unfeasible to just generate a .db file with each test run and then nuke the thing once finished. But, well, this was also a pain in the ass to do...

For data insertions, updates or deletions it made legitimate sense to at least somehow simulate the db and check for some change in its contents (but my thoughts on this continue). But a lot of requests were simply for data fetching, and yet still I found myself generating, pre-populating and then querying a whole ass database for the data - which again, is a lot when you are concerned first and foremost with testing your endpoints, not your database specifically.

The best solution I can think of currently is to have the SQLAlchemy session remain internal to another object/module entirely, and then only concern the API code with grabbing the result of a method on such an object/module given the relevant incoming data. This way, I can simply have the method required for the test be injected as a default parameter value into the endpoint function and stub it with a different callback when testing. I'd argue it's stuff like this that allows me to consider SQLAlchemy as a library rather than strictly a framework, but that's a post I've already made...

But that being said this is far from my final thought on the matter and following the rabbit hole of testability through to better modularity etc. is a continuous process.

In turn, I tend to like to think in extremely abstract terms and to draw things out on paper before I set to work on things a lot of the time, but a lot of people seem to prefer designing primarily by writing out a So, how can you balance doing your tests before your implementation with getting from idea to keystroke right away?

4 - Types, and other code signature tips for typists

I have to say right off the bat, I'm not that deeply enthusiastic about type declarations and declarations for their own sake - that is to say, I'm not yet convinced that I can use types themselves to define every aspect of the behaviour of my code.

Perhaps, judging from the words of some of my peers, there are some dazzling developments in type theory that are yet to come to my attention and a fortiori are yet to really become all the rage in the software world, but for the time being if I really want to know that I get a given, specific outcome for some given, specific input given particular conditions are met... I'll write a test. But that's me.

But again, how do we get a broad design into our editor without implementing before we even test?

A trick that I sometimes like to do when setting up to do something - bear in mind, I like to sketch things out on paper first - is to define a set of class or functions which just return a placeholder value but take the arguments I want to pass.

So if I can feel I need a function to doSomething, but I don't want to code blind, but I also feel like typing it out to get an idea of what it is, the best place to start is with what arguments it takes and what kind of data it returns. But again, we need a little more to go off of for inputs and outputs than just the names, especially if we have all sorts of potential data types we could use to represent these.

And this, in my view, is where type signatures really help to clarify roughly how a piece of code should be used in, and what it does for, a system, before you define the actual behaviour at all. From there you can write a failing test, and it's red, green, refactor from there!

Once those rough details are in place, we then have a basis for which we can start writing our tests! One must consider that this certainly isn't the procedure I always reach for, but it might tickle your fancy a little if you're considering TDD but feel weird writing your tests before you even really know what the interface for your code looks like!

It's also worth mentioning where type signatures can support smarter and more extensive tooling - such being the reason that Typescript exists (apparently) - and this will often catch silly little errors that would have stopped your code even attempting to behave properly. Testability is about speed of feedback, and hey, that spills over beyond TDD.

Moreover, as much as the Rust language currently carries the mark of a fierce dispute over the restrictiveness of trademark policy, it's rich type system allows the compiler to produce machine code that's comparable to C++ without the soul-crushing insanity. Cargo also comes with an in built test runner. Fancy that!

So, in conclusion...

Making your code testable may feel like it's conflicting with your design at first, but more often than not it can serve to push you towards a better way of assembling software. You get code that's more modular, code that can have new features added to it without having to wait and see if something else was broken as a result, code in which you can switch out even potentially rather big dependencies without having to scour the entire codebase, code that draws on tips and insights from a range of paradigms to do the most straightforward implementation possible given the need for testability vs code that's wedded dogmatically to just one paradigm...

And again, there are ways you can dip your toes into TDD or at least focus more on testability, to practice the spirit of the thing if not the exact letter!

In the end, you can get to the point where you're writing tests for your code that don't have to worry about specific internal details at all (well, most of the time).

That's how you get safety nets, not guard rails.

#tdd #test driven development #software #coding #software engineering #programming #software development #software design #computer science #code #software testing #software quality assurance

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