Transforming QA in Agile Organizations

 

Digitization has brought in speed, convenience, accessibility, quality, and cost rationalization as major benefits for the customers. The traditional management practices are often unable to achieve those benefits in real-time. With a rapidly changing digital landscape and the need to address the challenges posed by shifting customer preferences and growing competition, enterprises are embracing the agile development methodology. According to the agile testing approach, quality assurance is more about ‘test fast’ rather than ‘test everything.’ Consequently, QA, in order to keep up with the pace-driven agile model of software development, needs to adapt. 

It needs to fully integrate into the build cycle from the traditional ‘find bugs at the end of the development’ approach. Agile testing entails the QA to be present in the end-to-end value chain, which means right from the ideation stage to the development and integration of code, product delivery, and beyond. The reason why many enterprises, even after adopting the agile way of development, continue with the traditional model of QA, is the absence of an agile culture.

To ensure the success of an agile testing approach, the QA team needs to unlearn some of the shibboleths. These may include the following:

·        Testing is a distinct process exclusive of development and delivery

·        Test automation is only for regression purpose

·        The ultimate goal of the QA team is to detect bugs

How to transform traditional QA into an agile testing framework?

QA forms a critical component in the Continuous Integration (CI) and Continuous Delivery (CD) value chain of enterprises following the agile testing methodology. And to ensure the reliability of CI/CD outcomes, QA should be embedded at every step of the build-test-delivery process. In agile-based organizations, the release management process can shift to the combined development and QA team from the operations team. This enables the QA team to view the end-to-end product delivery process thereby identifying and fixing bottlenecks (if any). Enterprises should go about transforming their QA processes by taking the following approach:

·        Increasing the level of test automation

·        Improving the testing skills of the QA team

·        Developing a strategy to incorporate AI in the agile testing methodology through analytics, RPA, and self-learning

Focus on problems to achieve better solutions: The Agile testing services should focus on the bottlenecks that prevent the integration of QA into the build cycle instead of the solution. It is only by analyzing the bottlenecks and finding a way to fix them that the QA team can deliver the final product, quickly and consistently. In doing so, the QA team can choose various agile test automation tools.

Upgrading the skillset of testers: The lack of knowledgeable agile testers is one of the reasons why enterprises shy away from implementing agile. According to the World Quality Report, around 42% of respondents cited a lack of expertise in agile testing for not implementing agile in its true form. The testers should have the programming knowledge to create test automation scripts and access the underlying business logic. They should be able to analyze the code and make improvements from the perspective of performance. Hence, before implementing test automation, upskill the QA team into the nitty-gritty of agile application testing.

Embracing test automation: One of the prominent features of implementing agile testing is automation. It helps to speed up the testing process and identifies (and fixes) glitches that are often missed during manual testing. So, not only regression testing, the QA team should focus on extending agile test automation to other test types like smoke testing. Developers should play a crucial role in enabling the QA team to set up automation or conduct exploratory testing.

Adopting RPA: Robotic Process Automation can drive high performance in the IT systems by reducing the level of end-to-end testing. It helps to automate tedious processes, reduce glitches, and remove drudge work, thereby allowing the QA team to focus more on exploratory testing or other important activities. It is more about automating the processes by using the correct functionality.

Real-time testing: Although test virtualization can mimic the test scenarios and parameters on the cloud, real-time testing is a different ballgame altogether. It allows testers to identify the functional issues, which can only be found in the real world. Real-time testing can be handy when it comes to testing during peak periods and is a valuable proposition for brands to expand their test coverage.

Conclusion

Organizations are becoming agile to stay competitive and deliver the best user experience to their users. However, traditional QA needs to adapt to the build ecosystem that agile entails. The first step in this transition is embracing a culture change where QA becomes a cumulative responsibility of both the development and testing teams.

The different types of Test Automation Frameworks

 

 

 Testing remains a critical component of any software development process. This is because it ensures the identification and removal of all bugs in the code, the delivery of superior customer experiences, greater adoption of the software in the market, and increased profitability for the enterprise. The process of testing has undergone considerable improvements in the last few years with the automated testing approach being adopted for its slew of benefits. As opposed to manual testing, a test automation strategy automates the testing of software applications to speed up the development process and make the software application glitch-free, efficient, and reliable. However, to implement test automation, enterprises need to utilize test automation frameworks to drive faster releases of quality products.

What is a test automation framework?

To begin with, a framework is a structure of protocols, rules, and guidelines, which can help an enterprise to derive the optimum benefits for a concept or idea. In the same vein, the structure called a test automation framework helps to execute and generate test results. The key components of such a framework are test tools, equipment, test scripts, automation engineers, and procedures. The framework determines if the test results are in alignment with the expected results. Being independent of the software application, a framework can be expanded according to the testing needs of any application and helps to improve test coverage and the quality of products. 

What are the benefits of a test automation framework?

Using such a framework in executing QA automation testing garners the following benefits for the team.

• ·        Better test efficiency
• ·         Better speed and reliability
• ·         Optimization of resources
• ·         Remote testing
• ·         Reduced manual intervention
• ·         Parallel testing
• ·         Bug fixing at an early stage
• ·         Enhanced test coverage
• ·         Code reusability
• ·         Less maintenance cost
• ·         Increased ROI

What are the different types of automated frameworks?

Automated testing services use different types of frameworks to derive the best test outcomes. However, it is important to select the right type for testing the software application under consideration.

# Linear automation framework: The simplest of all frameworks is also known as a record-and-playback framework. Here, the testers need not write the custom test codes and the test process is mentioned in sequential order. It is mainly used for introductory level testing and converts medium or small-sized manual scripts into their corresponding automation scripts. However, on the flip side, the scripts cannot be reused as the data is hardwired into them.

Advantages

·         The tester does not need to be an expert in test automation as there is no need to write any custom code.

·         The testing process takes less time

·         The test workflow is simple to understand as the scripts are written in a sequential order

·         Arguably the best framework to start with automated software testing thanks to its record-and-playback features.

# Module-based framework: Based on Object-Oriented Programming or OOPs, the framework uses abstraction as its concept. According to this, the application under test is divided into various modules wherein each module comprises individual test scripts. Since the modules are separated using the abstraction layer, any changes made to the individual modules do not impact others. The flip side of this framework is that it requires the knowledge of programming language to set up.

Advantages

·         Since the framework comprises of several modules or sections, the cost and ease of maintenance are less.

·         Easy to create new driver scripts.

·         Can be scaled easily and should any defect be found the rest of the overarching module does not need to be touched.

# Library architecture testing framework: Here, tasks with similarities to the test script are identified followed by the testers executing the function-based grouping of similar tasks. Thereafter, the library stores the sorted functions that can be called by the test scripts upon requirement. The framework needs more time and technical expertise to be set up.

Advantages

·         Better reusability of codes compared to the ‘record and playback’ model

·         High level of modularization leading to easy maintenance and scalability of test scripts

# Data-driven framework: In this type of automated testing approach, the inputs and expected results are stored in separate files. Also, a single driver test can perform all test cases with various data sets. The framework entails the segregation of test data and test script logic facilitating code reusability.

Advantages

·         Test executable using multiple data sets

·         Any changes made to the test script do not impact the test data

·         Any number of scenarios can be tested by changing the data sets

# Keyword-driven testing framework: This application-independent framework separates test data and script logic followed by storing the data and keywords externally in a different location. It is more suitable for automated web testing and needs the selection of keywords and data tables.

Advantages

·         Does not require deep knowledge of scripting

·         Reusability of code as a keyword can be used across test scripts

·         Test scripts can be developed independently of the software application being tested

Conclusion

To facilitate faster release of quality software applications under the Agile and DevOps methodologies, choosing the right test automation framework is critical. The criteria to choose any test framework may include the reusability of test scripts, minimum human intervention, and quick identification of glitches, among others. 

 Article Original source:

https://dev.to/

 

What constitutes the process of Software Quality Assurance?

  

 To ensure the quality of the software product, software quality assurance is conducted comprising activities like planning, setting up the metrics, formal technical reviews, setting up multiple testing strategies, change control, report and documentation.

In a rapidly growing digital landscape built on complex software applications, system software suites, state-of-the-art hardware systems, networks, and internet technologies, the customers have become very demanding. The demand is for quality products with attributes such as speed, security, cost-effectiveness, usability, and convenience. Software quality assurance is the process to evaluate these attributes by testing software applications based on a set of parameters. It majorly tests whether the software application under development fulfils all criteria that the initial plan entailed. A QA software testing process validates the functioning of all processes, modules, methods, work items, and activities as per pre-defined metrics. It also checks if the software application complies with the industry defined standards such as ISO 9000, CMMI, SOX, ISO 27001, and PCI DSS, among others.
The process of software quality assurance is comprehensive and entails the end-to-end lifecycle of the software development and delivery process. There may be situations when the software conforms to the explicit requirements but does not meet the implicit requirements. These situations are emblematic of suspected software quality and require the hiring of software quality assurance services for mitigation.

Objectives of quality assurance and testing

QA testing services follow the below-mentioned objectives:

• Ensure the software fully complies with the protocols and meets all quality parameters before delivery

• Customers should get a superior experience while browsing the software and using its various features and functionalities

• The software should be well-structured and understandable by any developer or tester

In a competitive business landscape where the requirement is for delivering quality products faster to the market, the software quality assurance process should be continuous. This entails the adoption of the agile way of software development wherein cross-functional teams work in tandem within a QA enabling culture. The other aspects of pursuing software quality assurance methods are implementing test automation and provisioning the requisite test environment.

What activities belong to the Software Quality Assurance process?

The software quality assurance testing process entails the following activities:

Planning: At the outset, the testing team along with other stakeholders prepares a test plan outlining the test activities to be performed. The activities typically include the identification of evaluations, the performance of audits and reviews, identifying the applicable standards, tracking and documenting the errors, and feedback offered to the development team.

Setting up the metrics: The quality assurance and testing team identifies and sets up suitable metrics against which the quality of the application is evaluated. This helps in better monitoring and improving the effectiveness and efficiency of the testing process as per its overall objective. The examples may include measuring the capacity, quality level, performance, design features, dimension, amount, or some other attributes of the software application.

Formal Technical Reviews (FTR): This process evaluates the design and quality of the prototype. Here, the technical team is consulted about the software’s quality requirements to detect glitches early on in the SDLC. The FTR helps to reduce rework in the later phases and works as a quality control mechanism. The FTR verifies if the software application under test meets specific quality requirements as per predefined standards.

Setting up a multi-testing strategy: This ensures the software quality assurance testing process is not dependent on a single testing approach. With a multiple-testing strategy, the software application is tested from various angles to achieve better quality. These include black-box and white-box testing, system testing, unit testing, regression testing, and acceptance testing, among others.

Change control: Here, a mix of manual and automated testing procedures is used to create a mechanism for change control. Through the validation of change control, the nature of change and its impact are evaluated to maintain software quality during the phases of development and maintenance. The change control activity determines the impact of change brought about by fixing a defect(s) and verifies whether the change is in accordance with the objectives of the project.

Reports and documentation: The entire process of software quality assurance testing is documented and shared with the stakeholders for further analysis. The documented reports include test results, review reports, audit results, and change results, among others.

Conclusion

Software quality assurance is the lynchpin to achieve the success of the software product based on its adoption by the customers. It consists of several processes, activities, techniques, and standards, which determine if the software product aligns with the business objectives and performs to its desired level.  

 

Article Source:
https://www.softwaretestingmaterial.com/

What is the role of Cloud Testing in IT modernization?

 

 

Cloud testing has become an inevitable component in the digital transformation process of business enterprises. It delivers a slew of benefits such as on-demand provisioning of test resources, no setting up of costly on-premise test environments, reducing CapEx, and accelerating the time to market, among others. 

In the software development ecosystem, testing has often been considered as an adjunct process, which organizations willy-nilly need to put up with to meet their business objectives. Further, the testing process executed through a dedicated in-house infrastructure may be used sporadically. However, given the growing complexities of business applications, organizations may find it difficult to set up and maintain on-premise testing facilities mimicking real-time environment. And even with the requisite infrastructure, organizations may still find it difficult to achieve scalability and operational flexibility to meet ROI.

This is where cloud-based testing can offer benefits like lower investment costs, easy accessibility to test resources, enhanced collaboration, on-demand flexibility, better efficiency, and reduced time to market. However, cloud testing may have challenges in the form of a lack of data security and standards, especially in a public cloud set up. So, stakeholders should explore the advantages of cloud testing services while being aware of the challenges.

Why choose a cloud application testing approach?

In addition to cloud computing, organizations are willing to embrace cloud application testing in view of the below-mentioned advantages.

Testing means new environment: Every new software development project has new testing needs. These necessitate the setting up of new testing environment, which is capital-intensive. Besides, in-house test labs are known to remain idle and underutilized, which make them a costly proposition. However, provisioning similar environments on the cloud when needed and paying for the limited time and resources they are used can save costs.

Testing can allow businesses to run as usual: A cloud application testing approach does not necessarily require the use of sensitive corporate data, which makes it safe. Since such testing has a minimal impact on the running of day-to-day business operations, it can be considered as an effective model of testing.

Addresses the testing complexities: Software applications are becoming complex, distributed, and dynamic to address the digital transformation initiatives of organizations. To test such applications (web or mobile-based) effectively, they need to be tested on a multiplicity of operating systems, devices, networks, browsers, and hardware configurations.

Besides, testing various functionalities of such applications in real-time would require the involvement of a large number of concurrent users spread across geographies and time zones. And no points for guessing that addressing such challenges by setting up in-house testing environments would entail huge capital expenditures. However, cloud-based test automation can be provisioned on-demand to address the above-mentioned challenges, thereby lowering the CapEx significantly. Importantly, the time, effort, and resources saved can be used for core business pursuits.

Organizations big or small must embrace IT modernization as a tenet to stay competitive. A cloud testing strategy allows them the flexibility to provision/decommission the testing environments based on their demand or the absence of the same. Hence, organizations end up accruing significant cost benefits by NOT investing in the following areas:

• Setting up a test infrastructure
• Provisioning of tool licences
• Configuring and maintaining test environments

Cloud has the ability to transform CapEx into OpEx and reduce costs. However, the quantum of cost benefits would depend on factors such as the type of cloud model (public, private, or hybrid), type of tests, and configuration of the test environment. Another lure to adopt cloud testing, besides cost optimization, is the availability of a standardized test environment. The standardization includes the presence of a library and compliance with service level agreements.

Creating on-premise test environments for a single application can be time-consuming and may delay the software application’s time to market. Whereas on-demand provisioning of cloud-based testing environments can be quick as they already exist in the cloud. With cloud testing, organizations do not need to figure out about finding servers, getting licenses for testing tools, and installing them. Instead, they can easily access virtual labs that are scalable and ready-to-use. These labs come with a host of test tools, operating systems, storage, and middleware to create test environments that mimic the real-world. Here, testers can execute testing with minimal or no writing of test scripts thereby shortening the product life cycle.

Other benefits of adopting cloud application testing

In modernizing the IT infrastructure of an organization, cloud-based testing entails a slew of benefits.

• Pay only for things that are used
• Reduces the product development lifecycle and speeds up deployment
• Standardized systems in use
• Latest functionality on offer
• Encourages collaboration, anytime and anywhere

Conclusion

Traditionally, testing has been given short shrift by most organizations in favor of development. However, the imperatives of creating product differentiation in the market by generating superior customer experiences have allowed organizations to provision on-demand cloud-based testing resources with a host of benefits.

Article Source:

https://devdojo.com/ 

Best practices for Salesforce Integration Testing

 
 

 Enterprises are digitizing in a big way to streamline their operations and deliver the best quality products to their customers. And when customers are the main force behind the success of an enterprise, ignoring their interests or downplaying their queries/issues can be an unmitigated disaster. Salesforce is a powerful Customer Relationship Management (CRM) software that helps enterprises to recognize and manage customer interactions throughout the product lifecycle. As a popular CRM tool, Salesforce is highly robust, customizable, configurable, and extensible. Comprising several applications, Salesforce helps businesses to reinforce customer relations and interactions, and client retention thereby leading to their growth.

Any CRM platform like Salesforce has become important in today’s business milieu where enterprises need to manage their relationship with customers once a product is delivered. The platform provides systems, technologies, strategies, and practices to reinforce customer interaction throughout the product lifecycle. Salesforce has myriad applications with which it needs robust integration and interoperability to run various functionalities. This calls for executing Salesforce integration testing covering all modules namely, accounts, campaigns, reports, leads, and contacts, among others.

Why Salesforce testing?

The CRM suite ensures proper management of customer interactions with the organization. It is only by understanding and addressing the concerns of the customers that organizations can ensure customer satisfaction and stay competitive. Salesforce application testing helps to validate the functionalities and their configurations as per the agreed business objectives. Such testing allows for early identification (and fixing) of glitches in the application development process thereupon ensuring the product addresses the needs of the customers.

Best practices for Salesforce integration testing

As mentioned above, Salesforce is the sum-total of applications that execute various functionalities aimed at addressing customer issues and strengthening the interaction. However, these applications should have proper integration among themselves and with the mother software suite (Salesforce) to deliver superior outcomes. Hence, a proper Salesforce testing framework should be established to take care of the integration issues. The best practices to follow while pursuing such testing are mentioned below:

# Collate information: Collate a comprehensive list of all test case scenarios and possible technical exceptions. For each scenario, the expected results and actions to be performed should be documented. Thereafter, test data should be created to validate each scenario.

# Right testing tools: To get the best results, use the right debugging tools offered by the latest browsers combined with the test classes. For example, you may use a powerful object-oriented and case-sensitive proprietary programming language called Apex to execute programmed functions like updates, deletions, custom links, and record insertion, among others.

# Follow naming conventions: Before writing test cases for Salesforce test automation, it is important to name the test methods appropriately. The test methods should comprise the below-mentioned parts:

·         Name of the method – insert/delete/update/undelete

·         Information about the test path – null contact or valid

# Total coverage: Even though the Salesforce directive is to cover about 75% of the code while conducting unit tests, one should aim at covering 100% of the code. Test all cases (positive or negative) as well as data (present or absent). Follow the below-mentioned tips to ensure 100% test coverage.

·         Refresh the code coverage numbers while running Salesforce automated testing

·         Rerun the tests when there has been an update in the business

·         The test coverage depends on the number of code lines. So, if the codes lines are added or deleted, the coverage percentage will be impacted accordingly.

# Test cases with classes and controllers: Developers, in order to make coding portable, organized, readable, and reusable, often create separate classes and controllers for each function. So, even though this enhances the readability of the code, there is not much improvement in its efficiency. Portability can be achieved when the test code is in the original class and there are minimal chances of missing a test class during migration from sandbox to production.

# Agile approach: In this approach, the software application is developed in small incremental builds wherein testers work concurrently and iteratively (using test automation) to evaluate the code.

# Synchronization with current operations: One of the principal features of any distinct Salesforce functional testing is its synchronization with the current operations. So, it is important to verify the test results against reference data signifying quality.

Conclusion

Since Salesforce functionalities add value to the organization, they need to be validated against expected parameters and reference data. Thus, a proper Salesforce integration testing plan should ensure the application build simplifies, streamlines, and enhances the business systems. 

Article Original Source:
https://www.sfdcpoint.com/

 

How Software Testing can be benefited from the use of AI

 

 

Enterprises operating in the digital realm can achieve success if they ensure their software applications are updated as per the latest trends and customer preferences. This forces the IT teams to be faster and agile, and adopt measures to align their work culture to meet the demands of the business. No wonder they are adopting Agile and DevOps methodologies to speed up software development and delivery besides fostering collaboration. Agile and DevOps have quality assurance embedded in them leading to continuous testing of the code build.
 
Continuous testing ensures that any change in code is implemented instantaneously and effectively. It also places iterative QA across the SDLC thereby accelerating the build quality. However, continuous testing in the omnichannel environment can be riddled with issues such as a lack of visibility of requirements across processes, siloed automation, and a high volume of tests, among others. To address these issues and drive quality at speed across the SDLC, it is important to adopt an AI-based testing approach.
 
How can AI facilitate continuous testing?
 
Artificial Intelligence can remove manual intervention and smoothen the process of continuous testing. In AI testing, QA teams can initiate the test cycle to identify and fix bugs based on insights drawn from past events and historical data sets. AI-driven testing ensures that only a robust code is moved across the SDLC thereby foregrounding quality as the centrepiece of software development. Even though the testing activities are automated in continuous testing, the code needs to be signed off manually to move across quality gates based on the test results. This siloed automation can disrupt the flow of code in the SDLC. However, with AI test automation, the code checking at quality gates is done automatically and code progression is managed by analyzing the test results. This makes the workflow fully automated. By triggering QA processes with artificial intelligence, the testing teams can achieve the following:
 
Automation of quality gates: Given that the AI algorithm can determine the course of code progression based on historical data, the testing teams can allow/entrust the AI testing services with facilitating code progression. Conversely, the AI engine can prevent code progression if it finds a high probability of outage or disruption to be caused by the presence of bugs.
 
Identification of root causes: AI-based testing can analyze the patterns and correlations in a build to identify the root causes of defects. Thereafter, the AI engine can orchestrate remedial tests to reduce the margin of errors in the build.
 
Focus on brand assurance: With an AI testing framework, test automation is made all-pervasive and intelligent. This allows the QA teams to glean insights from historical data, business acumen, and customer inputs, thereby shifting the QA focus to brand assurance and competitiveness.
 
Predictive analysis: AI-based testing can analyze the existing customer data to understand how the user behavior and needs will evolve in future. These insights will give the software development and QA teams to come up with suitable features and functionalities to be ahead of the curve.
 
API test evaluation: The performance of a software application depends to a large extent on the quality of interactions between various modules connected with databases and servers, among others. By evaluating the performance of the APIs, the testers can validate if the connection between various modules in the application is stable. They also check if the requests are processed accurately and the customers will get the correct outcome post a specific interaction. Artificial intelligence led testing can analyze the functionality of the APIs and large volumes of data to detect risks and create precise test cases.
 
Scriptless test automation: Even though test automation has revolutionized the QA process, the writing of test scripts to automate various test processes can be a challenge. Besides, the scripts need to be maintained as well for further usage thereby escalating the cost. However, an AI testing framework can create test cases automatically leaving the QA specialists to focus on other areas of software testing. Often developers writing test cases do not have the time to explore additional possibilities for the test cases. Consequently, they may end up writing test cases they are familiar with rather than writing the ones that can generate the least redundant data. AI-driven testing can run a minimal number of tests to understand the kind of impact (positive or negative) a code change can entail. With limited manual intervention, the artificial intelligence led testing can ensure no redundant data and bottlenecks are there in the application.
 
Conclusion
 
Artificial Intelligence can open up new avenues for testing software applications. In a day and age where the speed and quality of applications go hand-in-hand to generate superior user experiences, reduce costs, and improve profitability, AI-based testing has become an enabler for enterprises to stay competitive.

Article Source:
https://medium.com/