The Best Test Data Management Practices in an Increasingly Digital World

A quick scan of the application landscape shows that customers are more empowered, digitally savvy, and eager to have superior experiences faster. To achieve and maintain leadership in this landscape, organizations need to update applications constantly and at speed. This is why dependency on agile, DevOps, and CI/CD technologies has increased tremendously, further translating to an exponential increase in the adoption of test data management initiatives. CI/CD pipelines benefit from the fact that any new code that is developed is automatically integrated into the main application and tested continuously. Automated tests are critical to success, and agility is lost when test data delivery does not match code development and integration velocity.

Why Test Data Management?

Industry data shows that up to 60% of development and testing time is consumed by data-related activities, with a significant portion dedicated to testing data management. This amply validates that the global test data management market is expected to grow at a CAGR of 11.5% over the forecast period 2020-2025, according to the ResearchandMarkets TDM report.

Best Practices for Test Data Management

Any organization focusing on making its test data management discipline stronger and capable of supporting the new age digital delivery landscape needs to focus on the following three cornerstones.

Applicability:
The principle of shift left mandates that each phase in an SDLC has a tight feedback loop that ensures defects don’t move down the development/deployment pipeline, making it less costly for errors to be detected and rectified. Its success hinges to a large extent on close mapping of test data to the production environment. Replicating or cloning production data is manually intensive, and as the World Quality Report 2020-21 shows, 79% of respondents create test data manually with each run. Scripts and automation tools can take up most heavy lifting and bring this down to a large extent when done well. With production quality data being very close to reality, defect leakage is reduced vastly, ultimately translating to a significant reduction in defect triage cost at later stages of development/deployment.

However, using production-quality data at all times may not be possible, especially in the case of applications that are only a prototype or built from scratch. Additionally, using a complete copy of the production database is time and effort-intensive – instead, it is worthwhile to identify relevant subsets for testing. A strategy that brings together the right mix of product quality data and synthetic data closely aligned to production data models is the best bet. While production data maps to narrower testing outcomes in realistic environments, synthetic data is much broader and enables you to simulate environments beyond the ambit of production data. Usage of test data automation platforms that allocates apt dataset combinations for tests can bring further stability to testing.

Tight coupling with production data is also complicated by a host of data privacy laws like GDPR, CCPA, CPPA, etc., that mandate protecting customer-sensitive information. Anonymizing data or obfuscating data to remove sensitive information is an approach that is followed to circumvent this issue. Usually, non-production environments are less secure, and data masking for protecting PII information becomes paramount.

Accuracy:
Accuracy is critical in today’s digital transformation-led SDLC, where app updates are being launched to market faster and need to be as error-free as possible, a nearly impossible feat without accurate test data. The technology landscape is also more complex and integrated like never before, percolating the complexity of data model relationships and the environments in which they are used. The need is to maintain a single source of data truth. Many organizations adopt the path of creating a gold master for data and then make data subsets based on the need of the application. Adopting tools that validate and update data automatically during each test run further ensures the accuracy of the master data.

Accuracy also entails ensuring the relevance of data in the context of the application being tested. Decade-old data formats might be applicable in the context of an insurance application that needs historic policy data formats. However, demographic data or data related to customer purchasing behavior applicable in a retail application context is highly dynamic. The centralized data governance structure addresses this issue, at times sunsetting the data that has served its purpose, preventing any unintended usage. This also reduces maintenance costs for archiving large amounts of test data.

Also important is a proper data governance mechanism that provides the right provisioning capability and ownership driven at a central level, thereby helping teams use a single data truth for testing. Adopting similar provisioning techniques can further remove any cross-team constraints and ensure accurate data is available on demand.

Availability:
The rapid adoption of digital platforms and application movement into cloud environments have been driving exponential growth in user-generated data and cloud data traffic. The pandemic has accelerated this trend by moving the majority of application usage online. ResearchandMarkets report states that for every terabyte of data growth in production, ten terabytes are used for development, testing, and other non-production use cases, thereby driving up costs. Given this magnitude of test data usage, it is essential to align data availability with the release schedules of the application so that testers don’t need to spend a lot of time tweaking data for every code release.

The other most crucial thing in ensuring data availability is to manage version control of the data, helping to overcome the confusion caused by conflicting and multiple versioned local databases/datasets. The centrally managed test data team will help ensure single data truth and provide subsets of data as applicable to various subsystems or based on the need of the application under test. The central data repository also needs to be an ever-changing, learning one since the APIs and interfaces of the application keeps evolving, driving the need for updating test data consistently. After every test, the quality of data can be evaluated and updated in the central repository making it more accurate. This further drives reusability of data across a plethora of similar test scenarios.

The importance of choosing the right test data management tools

In DevOps and CI/CD environments, accurate test data at high velocity is an additional critical dimension in ensuring continuous integration and deployment. Choosing the right test data management framework and tool suite helps automate various stages in making data test ready through data generation, masking, scripting, provisioning, and cloning. World quality report 2020-21 indicates that the adoption of cloud and tool stacks for TDM has witnessed an increase, but there is a need for more maturity to make effective use.

In summary, for test data management, like many other disciplines, there is no one size fits all approach. An optimum mix of production mapped data, and synthetic data, created and housed in a repository managed at a central level is an excellent way to go. However, this approach, primarily while focusing on synthetic data generation, comes with its own set of challenges, including the need to have strong domain and database expertise. Organizations have also been taking TDM to the next level by deploying AI and ML techniques, which scan through data sets at the central repository and suggest the most practical applications for a particular application under test.

Need help? Partner with experts from Trigent to get a customized test data management solution and be a leader in the new-age digital delivery landscape.

4 Rs for Scaling Outsourced QA. The first steps towards a rewarding engagement

Expanding nature of products, need for faster releases to market much ahead of competition, knee jerk or ad hoc reactions to newer revenue streams with products, ever increasing role of customer experience across newer channels of interaction, are all driving the need to scale up development and testing. With the increased adoption of DevOps, the need to scale takes a different color altogether.

Outsourcing QA has become the norm on account of its ability to address the scalability of testing initiatives and bring in a sharper focus on outcome-based engagements. The World Quality Report 2020 mentions that 34% of respondents felt QA teams lack skills especially on the AI/ML front. This further reinforces their need to outsource for getting the right mix of skill sets so as to avoid any temporary skill set gaps.

However, ensuring that your outsourced QA gives you speed and scale can be a reality only if the rules of engagement with the partner are clear. Focusing on 4 R’s as outlined below while embarking on the outsourcing journey, will help you derive maximum value.

  1. Right Partner
  2. Right Process
  3. Right Communication
  4. Right Outcome

Right Partner

The foremost step is to identify the right partner, one with a stable track record, depth in QA, domain as well as technology, and the right mix of skill sets across toolsets and frameworks. Further, given the blurring lines between QA and development with testing being integrated across the SDLC, there is a strong need for the partner to have strengths across DevOps, CI/CD in order to make a tangible impact on the delivery cycle.

The ability of the partner to bring to table prebuilt accelerators can go a long way in achieving cost, time and efficiency benefits. The stability or track record of the partner translates to the ability to bring onboard the right team which stays committed throughout the duration of the engagement. The team’s staying power assumes special significance in longer duration engagements wherein shifts in critical talent derails efficiency and timelines on account of challenges involved with newer talent onboarding and effective knowledge transfer.

An often overlooked area is the partner’s integrity. During the evaluation stages, claims pertaining to industry depth as well as technical expertise abound and partners tend to overpromise. Due care needs to be exercised to know if their recommendations are grounded in delivery experience. Closer look at the partner’s references and past engagements not only help to gain insight into their claims but also help to evaluate their ability to deliver in your context.

It’s also worthwhile to explore if the partner is open to differentiated commercial models that are more outcome driven and based on your needs rather than being fixated on the traditional T&M model.

Right Process

With the right partner on board, creating a robust process and governing mechanism assumes tremendous significance. Mapping key touchpoints from the partner side, aligning them to your team, and identifying escalation points serve as a good starting point. With agile and DevOps principles having collaboration across teams as the cornerstone, development, QA, and business stakeholder interactions should form a key component of the process. While cross-functional teams with Dev QA competencies start off each sprint with a planning meeting, formulating cadence calls to assess progress and setting up code drop or hand off criteria between Dev and QA can prevent Agile engagements from degrading into mini waterfall models.

Bringing in automated CI/CD pipelines obviates the need for handoffs substantially. Processes then need to track and manage areas such as quality and release readiness, visibility across all stages of the pipeline through reporting of essential KPIs, documentation for managing version control, resource management, and capacity planning. At times, toolset disparity between various stages and multiple teams driving parallel work streams creates numerous information silos leading to fragmented visibility at the product level. The right process should focus on integration aspects as well to bridge these gaps. Each team needs to be aware and given visibility on ownership at each stage of the pipeline.

Further, a sound process also brings in elements of risk mitigation and impact assessment and ensures adequate controls are built into SOP documents to circumvent any unforeseen event. Security measures is another critical area that needs to be incorporated into the process early on, more often it is an afterthought in the DevOps process. Puppet 2020 State of DevOps report mentions that integrating security fully into the software delivery process can quickly remediate critical vulnerabilities – 45% of organizations with this capability can remediate vulnerabilities within a day.

Right Communication

Clear and effective communication is an integral component of QA, more so when DevOps, Agile, and similar collaboration-heavy initiatives are pursued achieving QA at scale. Effective communication at the beginning of the sprint ensures that cross-functional teams are cognizant of the expectations from each of them and have their eye firmly fixed on the end goal of application release. From then on, a robust feedback loop, one that aims at continuous feedback and response, cutting across all stages of the value chain, plays a vital role in maintaining the health of the DevOps pipeline.

While regular stand-up meetings have their own place in DevOps, effective communication needs to go much beyond to focus on tools, insights across each stage, and collaboration. A wide range of messaging apps like Slack, email, and notification tools accelerate inter-team communication. Many of these toolkits are further integrated with RSS feeds, google drive, and various CI tools like Jenkins, Travis, Bamboo, etc. making build pushes and code change notifications fully automated. Developers need notifications when a build fails, testers need them when a build succeeds and Ops need to be notified at various stages depending on the release workflow.

The toolkits adopted by the partner also need to extend communication to your team. At times, it makes sense for the partner to have customer service and help desk support as an independent channel to accept your concern. The Puppet report further mentions that companies at a high level of DevOps maturity use ticketing systems 16% more than what is used by companies at the lower end of the maturity scale. Communication of the project’s progress and evolution to all concerned stakeholders is integral irrespective of the platforms used. Equally important is the need to categorize communication in terms of priority and based on what is most applicable to classes of users.

Documentation is an important component of communication and from our experiences, commonly underplayed. It is important for sharing work, knowledge transfer, continuous learning and experimentation. Code that is well documented enables faster completion of audit as well. In CI/CD based software release methodology, code documentation plays a strong role in version control across multiple releases. Experts advocate continuous documentation as core communication practice.

Right Outcome

Finally, it goes without saying that setting parameters for measuring the outcome, tracking and monitoring those, determines the success of the partner in scaling your QA initiatives. Metrics like velocity, reliability, reduced application release cycles and ability to ramp up/ramp down are commonly used. Further, there are also a set of metrics aimed at the efficiency of the CI/CD pipeline, like environment provisioning time, features deployment rate, and a series of build, integration, and deployment metrics. However, it is imperative to supplement these with others that are more aligned to customer-centricity – delivering user-ready software faster with minimal errors at scale.

In addition to the metrics that are used to measure and improve various stages of the CI/CD pipeline, we also need to track several non-negotiable improvement measures. Many of these like deployment frequency, error rates at increased load, performance & load balancing, automation coverage of delivery process and recoverability helps to ascertain the efficiency of QA scale up.

Closely following on the heels of an earlier point, an outcome based model which maps financials to your engagement objectives will help to track outcomes to a large extent. While the traditional T&M model is governed by transactional metrics, project overlays abound in cases where engagement scope does not align well to outcome expectations. An outcome based model also pushes the partner to bring in innovation through AI/ML and similar new age technology drivers – providing you access to such skill sets without the need for having them on your rolls.

If you are new to outsourcing, or working with a new partner, it may be good to start with a non-critical aspect of the work (for regular testing or automation), establish the process and then scale the engagement. For those players having maturity in terms of adopting outsourced QA functions in some way or the other, the steps outlined earlier form an all inclusive checklist to ensure maximization of engagement traction and effectiveness with the outsourcing partner.

Partner with us

Trigent’s experienced and versatile Quality Assurance and Testing team is a major contributor to the successful launch, upgrade, and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Trigent is an early pioneer in IT outsourcing and offshore software development business. We enable organizations to adopt digital processes and customer engagement models to achieve outstanding results and end-user experience. We help clients achieve this through enterprise-wide digital transformation, modernization, and optimization of their IT environment. Our decades of experience, deep domain knowledge, and technology expertise delivers transformational solutions to ISVs, enterprises, and SMBs.

Contact us now.

Poor application performance can be fatal for your enterprise, avoid app degradation with application performance testing

If you’ve ever wondered what can possibly go wrong’ after creating a foolproof app, think again. Democrats’ Iowa Caucus voting app is a case in point. The Iowa caucus post-mortem pointed towards a flawed software development process and insufficient testing.

The enterprise software market is predicted to touch US$230,134.0m in 2021, and the revenue is expected to grow with a CAGR of 9.1% leading to a market volume of US$326,285.5m by 2025. It is important that enterprises aggressively work towards getting their application performance testing efforts on track to ensure that all the individual components that go into the making of the app provide superior responses to ensure a better customer experience.

Banking app outages have also been pretty rampant in recent times putting the spotlight on the importance of application performance testing. Customers of Barclays, Santander, and HSBC suffered immensely when their mobile apps suddenly went down. It’s not as if banks worldwide are not digitally equipped. They dedicate at least 2-3 percent of their revenue to information technology along with additional expenses on building a superior IT infrastructure. What they also need is early and continuous performance testing to address and minimize the occurrence of such issues.

It is important that the application performs well not just when it goes live but later too. We give you a quick lowdown on application performance testing to help you gear up to meet modern-day challenges.

Application performance testing objectives

In general, users today, have little or no tolerance for bugs or poor response times. A faulty code can also lead to serious bottlenecks that can eventually lead to slowdown or downtime. Meanwhile, bottlenecks can arise from CPU utilization, disk usage, operating system limitations, or hardware issues.

Enterprises, therefore, need to conduct performance testing regularly to:

  • Ensure the app performs as expected
  • Identify and eliminate bottlenecks through continuous monitoring
  • Identify & eliminate limitations imposed by certain components
  • Identify and act on the causes of poor performance
  • Minimize implementation risks

Application performance testing parameters

Performance testing is based on various parameters that include load, stress, spike, endurance, volume, and scalability. Resilient apps can withstand increasing workloads, high volumes of data, and sudden or repetitive spikes in users and/or transactions.

As such, performance testing ensures that the app is designed keeping peak operations in mind and all components comprising the app function as a cohesive unit to meet consumer requirements.
No matter how complex the app is, performance testing teams are often required to take the following steps:

  • Setting the performance criteria – Performance benchmarks need to be set and criteria should be identified in order to decide the course of the testing.
  • Adopting a user-centric approach – Every user is different and it is always a good idea to simulate a variety of end-users to imagine diverse scenarios and test for use cases accordingly. You would therefore need to factor in expected usage patterns, the peak times, length of an average session within the application, how many times do users use the application in a day, what is the most commonly used screen for the app, etc.
  • Evaluating the testing environment – It is important to understand the production environment, the tools available for testing, and the hardware, software, and configurations to be used before beginning the testing process. This helps us understand the challenges and plan accordingly.
  • Monitoring for the best user experience – Constant monitoring is an important step in application performance testing. It will give you answers to what, when, and why’ helping you fine-tune the performance of the application. How long does it take for the app to load, how does the latest deployment compare to previous ones, how well does the app perform while backend performances occur, etc. are things you need to assess. It is important that you leverage your performance scripts well with proper correlations, and monitor performance baselines for your database to ensure it can manage fresh data loads without diluting the user experience.
  • Re-engineering and re-testing – The tests can be rerun as required to review and analyze results, and fine-tune again if necessary.

Early Performance Testing

Test early. Why wait for users to complain when you can proactively run tests early in the development lifecycle to check for application readiness and performance? In the current (micro) service-oriented architecture approach, as soon as the component or an interface is built, performance testing at a smaller scale can allow us to uncover issues w.r.t concurrency, response time/latency, SLA, etc. This will allow us to identify bottlenecks early and gain confidence in the product as it is being built.

Performance testing best practices

For the app to perform optimally, you must adopt testing practices that can alleviate performance issues across all stages of the app cycle.

Our top recommendations are as follows:

  • Build a comprehensive performance model – Understand your system’s capacity to be ready for concurrent users, simultaneous requests, response times, system scalability, and user satisfaction. The app load time, for instance, is a critical metric irrespective of the industry you belong to. Mobile app load times can hugely impact consumer choices as highlighted in a study by Akamai which suggested conversion rates reduce by half and bounce rate increases by 6% if a mobile site load time goes up from 1 second to 3. It is therefore important that you factor in the changing needs of customers to build trust, loyalty, and offer a smooth user experience.
  • Update your test suite – The pace of technology is such that new development tools will debut all the time. It is therefore important for application performance testing teams to ensure they sharpen their skills often and are equipped with the latest testing tools and methodologies.

An application may boast of incredible functionality, but without the right application architecture, it won’t impress much. Some of the best brands have suffered heavily due to poor application performance. While Google lost about $2.3 million due to the massive outage that occurred in December 2020, AWS suffered a major outage after Amazon added a small amount of capacity to its Kinesis servers.

So, the next time you decide to put your application performance testing efforts on the back burner, you might as well ask yourself ‘what would be the cost of failure’?

Tide over application performance challenges with Trigent

With decades of experience and a bunch of the finest testing tools, our teams are equipped to help you across the gamut of application performance right from testing to engineering. We test apps for reliability, scalability, and performance while monitoring them continuously with real-time data and analytics.

Allow us to help you lead in the world of apps. Request a demo now.

Bandwidth testing for superior user experience – here’s how?

The bandwidth Testing process simulates a low internet bandwidth connection and checks how your application behaves under desired network speed.

Considering a scenario where a specific application’s home page always loads in milliseconds in office premises this may not be the case when an end-user with low network speed accesses the application. To enhance user experience and get to know the application load times at specific network bandwidth speeds, we can simulate it and identify specific component/service call which is taking more time and can be improved further.

Prerequisites:

Bandwidth testing using Chrome browser. You should set your ‘Network’ panel in the chrome browser as per the below requirements.

Setup:

  1. Go to Customize and control Google Chrome at the top right corner and click More tools, then select Developer tools
    • Or press keyboard shortcut Ctrl + Shift + I
    • Or press F12
  2. Then click the ‘No throttling’ dropdown and choose Add… option under the Custom section.
  3. Click Add custom profile
  4. You will need to enter profile name in order to click on Add button. For example, ‘TestApp 1 MBPS’.
  5. Fill in the Download, Upload, Latency columns as below and click Add.

Example for 100Kbps:

Download (kb/s)Upload (kb/s)Latency (ms)
10050300

Example for 1Mbps:

Download (kb/s) Upload (kb/s)Latency (ms)
102451250

Example for 2.5Mbps:

Download (kb/s)Upload (kb/s)Latency (ms)
2600150030

Configuring Chrome is a one-time affair. Once Chrome has been configured for bandwidth testing, use the same settings by selecting the profile name [TestApp 1 MBPS] from the No Throttling drop-down.

Metrics to be collected for bandwidth testing:

  • Data transferred (KB)
  • Time taken for data transfer (seconds)

Using Record network activity option in the Chrome browser, you can get the above attributes.

Note: Toggle button “Record network log”/”Stop recording network log” and button “Clear” are available in the network panel.

It is best practice to close all the non-testing applications/tools in the system and other tabs from Chrome where the testing is performed.

Steps for recording network activity:

  1. Open Developer Tools and select the Network tab.
  2. Clear network log before testing.
  3. Make sure Disable cache checkbox is checked.
  4. Select the created network throttling profile (say ‘TestApp 1 MBPS’).
  5. Start recording for the steps to be measured as per the scenario file.
  6. Wait for the completion of step and page is fully loaded to check the results
  7. Data transferred size for each recorded step will be displayed down in the status bar as highlighted. The size will be in byte/kilobyte/megabyte. Make note of it.
  8. Time taken for data transfer will be displayed in the timeline graph. The horizontal axis represents the time scale in a millisecond. Take the
  9. Maximum time. Take approximate value from the graph and make note of it.

Here is the sample screenshot taken for login process of snapdeal application page in which specific js component (base.jquery111.min.js) loading took 4.40s and also while searching for any product searchResult.min.js took 4.08s which can be improved further for better user experience.

This Bandwidth Testing Process helps in every possible way to improve user experience by identifying specific component or API calls which are taking more time to load and it helps developers to fix those specific components.

Your application’s performance is a major differentiator that decides whether it turns out to be a success or fails to meet expectations. Ensure your applications are peaked for optimal performance and success.

Trigent’s experienced and versatile Quality Assurance and Testing team is a major contributor in the successful launch, upgrade and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Responsible Testing – Human centricity in Testing

Why responsibility in testing?

Consumers demand quality and expect more from products. The DevOps culture emphasizes the need for speed and scale of releases. As CI/CD crisscrosses with quality, it is vital to engage a human element in testing to foresee potential risks and think on behalf of the customer and the end-user.

Trigent looks at testing from a multiplicity of perspectives. Our test team gets involved at all stages of the DevOps cycle, not just when the product is ready. For us, responsible testing begins early in the cycle.

Introduce the Quality factor in DevOps

A responsible testing approach goes beyond the call of pre-defined duties and facilitates end-to-end stakeholder assurance and business value creation. Processes and strategies like risk assessment, non-functional tests, and customer experiences are baked into testing. Trigent’s philosophy of Responsible Testing characterizes all that we focus on while testing for functionality, security, and performance of an application.

Risk coverage: Assessing the failure and impact early on is one of the most critical aspects of testing. We work along with our clients’ product development teams to understand what’s important to stakeholders, evaluate and anticipate risks involved early on giving our testing a sharp focus.

Collaborative Test Design: We consider the viewpoints of multiple stakeholders to get a collaborative test design in place. Asking the right questions to the right people to get their perspectives helps us in testing better.

Customer experience: Responsible Testing philosophy strongly underlines customer experience as a critical element of testing. We test for all promises that are made for each of the customer touchpoints.

Test early, test often: We take the shift-left approach early on in the DevOps cycle. More releases and shorter release times mean testing early and testing often that translates into constantly rolling out new and enhanced requirements.

Early focus on non-functional testing: We plan for the non-functional testing needs at the beginning of the application life cycle. Our teams work closely with the DevOps team’s tests for security, performance, and accessibility – as early as possible.

Leverage automation: In our Responsible Testing philosophy, we look at it as a means to get the process to work faster and better. Or to leverage tools that can give better insights into testing, and areas to focus on testing. The mantra is judicious automation.

Release readiness: We evaluate all possibilities of going to the market – checking if we are operationally ready, planning for the support team’s readiness to take on the product. We also evaluate the readiness of the product, its behavior when it is actually released, and prepare for the subsequent changes expected.

Continuous feedback: Customer reviews, feedback speaks volumes of their experience with the application. We see it as an excellent opportunity to address customer concerns in real-time and offer a better product. Adopting the shift-right approach we focus on continuously monitoring product performance and leveraging the results in improving our test focus.

Think as a client. Test as a consumer.

Responsibility in testing is an organizational trait that is nurtured into Trigent’s work culture. We foster a culture where our testers imbibe qualities such as critical thinking on behalf of the client and the customer, the ability to adapt, and the willingness to learn.

Trigent values these qualitative aspects and soft skills in a responsible tester that contribute to the overall quality of testing and the product.
Responsibility: We take responsibility for the quality of testing of the product and also the possible business outcomes.

Communication: In today’s workplace, collaborating with multiple stakeholders, teams within and outside the organization is the reality. We emphasize not just on the functional skill sets but the ability to understand people, empathize with different perspectives, and express requirements effectively across levels and functions.

Collaboration: We value the benefits of a good collaboration with BA/PO/Dev and QA and Testing – a trait critical to understand the product features, usage models, and work seamlessly with cross-functional teams.

Critical thinking: As drivers of change in technology, it is critical to developing a mindset of asking the right questions and anticipating future risks for the business. In the process, we focus on gathering relevant information from the right stakeholders to form deep insights about the business and consumer. Our Responsible Testing approach keeps the customer experience at the heart of testing.

Adaptability & learning: In the constantly changing testing landscape, being able to quickly adapt to new technologies and the willingness to learn helps us offer better products and services.

Trigent’s Responsible Testing approach is a combination of technology and human intervention that elevates the user experience and the business value. To experience our Responsible Testing approach, talk to our experts for QA & Testing solutions.

Learn more about responsible testing in our webinar and about Trigent’s software testing services.

Improve the quality of digital experiences with Performance Engineering

Quality at the heart of business performance

“In 2020, the key expectation is fast, reliable, and trustworthy software.” *

As businesses embrace the Agile/DevOps culture and the emphasis on CI/CD is growing, quality assurance is seen as a standalone task, limited to validating functionalities implemented. When QA and Testing is an afterthought in an Agile/DevOps culture, the result is a subpar consumer experience followed by an adverse impact on the revenue pipeline. Poor customer experience also directly impacts brand credibility and business equity. While UI/UX are the visible elements of the customer experience, product, or service performance is a critical element that is often neglected. Performance Testing identifies the gaps that are addressed through Performance Engineering.

Small steps, significant gains – the journey towards Performance Engineering

The deeper issue lies in the organization’s approach towards quality and testing – it is considered an independent phase rather than looked upon as a collaborative and an integrated approach. Performance engineering is a set of methodologies that identifies potential risks and bottlenecks early on in the development stage of the product and addresses them. It goes without saying that performance is an essential ingredient in the quality of the product, there’s a deeper need for change in thinking – to think proactively, anticipate early in the development cycle, test and deliver a quality experience to the end consumer. An organization that makes gradual changes in its journey towards performance engineering stands to gain significantly. The leadership team, the product management, and the engineering and DevOps at different levels need to take the shift-left approach towards performance engineering.

Make Performance Engineering your strategic priority today

Despite the obvious advantages, performance testing is typically a reactive measure that is addressed after the initial launch. However, organizations need to embrace performance engineering measures right from the design phase, start small, and take incremental steps towards change.

Covid-19 has rapidly changed the way consumers behave globally. Businesses caught onto remote working; consumers moved shopping, entertainment, banking, learning, and medical consultations online. Consider the quantum jump in usage triggered by the pandemic.

The dramatic increase in the use of digital services has covered decades in days.**

Companies that adopted scalability and performance centric design have moved swiftly to capture the market opportunity.

With multiple user-interfaces across sectors being the norm and the increasing complexity of digital experiences, it is critical for businesses to get it right the first time in order to gain and retain customers’ trust.

As cloud migrations continue, whether rehosting the app on an IaaS or rebuilding a new approach, performance engineering ensures that migrated systems withstand sudden surges in usage. According to a Sogeti and Neotys report, 74% of the load testing infrastructure is operated in the cloud today. Cloud infrastructure providers ensure reliability but they may not be aware of the performance metrics that matter to the business and their impact. As organizations move from monolithic systems to distributed architectures provided by an assortment of companies, corporate leaders need to recognize the importance of performance engineering and embrace it to deliver the right solutions for the first time.

Our approach to Performance Engineering philosophy

At Trigent, we put the customer experience at the heart of planning the entire testing cycle. Our performance engineering practices align with ‘metrics that matter’ to businesses in the DevOps framework. While testing identifies the gaps in performance, the onus of architecting it right lies on the DevOps engineering team with proactive inputs from QA and Testing.

Performance engineering is also a way of thinking, the ability to plan for performance at the time of design, right at the beginning. As for quality, besides testing for functionality, anticipating potential bottlenecks helps us assess the process in its entirety in the beginning.

Asking some of these customer-centric questions early on shifts the perspective right at the outset. Ask them early, and you’re on your way to a performance engineering culture.

Parameters that matter

‘Will my application meet the defined response-time requirements of my customers?’

Consider an app that doesn’t respond within the expected standards of the customer; the chances of that application making it to the customer’s phone screen is pretty slim.

‘Will the application handle the expected user load and beyond?’

An application that tested well with 10 users may fail when that number is multiplied by a thousand or two.

We take the viewpoints of multiple stakeholders, consider parameters that matter to the customer, and assess impact early on.

Customer experience matters

Performance Engineering takes into account the overall experience of the end-user and their environment.

Asking pertinent questions such as ‘Will my users experience acceptable response times, even during peak hours?’ or ‘Does the application respond quickly enough for the intended users?’ does well to anticipate potential pitfalls in network usage and latency.

‘Where are the bottlenecks in my multi-user environment?’

Understand the real environment of the user and their challenges to provide a quality user experience.

Early Focus

The non-functional aspects are integrated into the DevOps and an early focus on performance enables us to gain insights into architectural issues.

‘How can we optimize the multi-user application before it goes live?
‘How can we detect errors that only occur under real-load conditions?

Quick course corrections help optimize performance and make the product market-ready. Besides faster deployment, quality assurance gives our clients an added advantage of reduced performance costs.

Architect it right

‘What system capacity is required to handle the expected load?’
‘Will the application handle the number of transactions required by the business?’

Important questions like these focus on architecting the product for performance. As part of the performance engineering methodology, our teams consistently check and validate the capabilities at the time of developing the product or scaling it up. We take the shift-left and shift-right approach to anticipate, identify, and remove bottlenecks early on. Getting the architecture right enables us to deliver and deploy a high-quality product every time.

Performance engineering done right is sure to improve the planning-to-deployment time with high-quality products. Plus, it reduces performance costs arising out of unforeseen issues. A step-by-step approach in testing makes sure organizations move towards achieving performance engineering. Talk to our experts for scalable performance engineering solutions for your business.

Learn more about Trigent software testing services.


Reference:
* The State of Performance Engineering 2020 – A Sogeti and Neotys report
** Meet the next-normal consumer – A McKinsey & Company report

Trigent excels in delivering Digital Transformation Services: GoodFirms

GoodFirms consists of researched companies and their reviews from genuine, authorized service-buyers across the IT industry. Furthermore, the companies are examined on crucial parameters of Quality, Reliability, and Ability and ranked based on the same. This factor helps customers to choose and hire companies by bridging the gap between the two.

They recently evaluated Trigent based on the same parameters, after which they found the firm excels in delivering IT Services, mainly:


Keeping Up with Latest Technology Through Cloud computing

Cloud computing technology has made the process of meeting the changing demands of clients and customers. The companies who are early adopters of the changing technologies always achieve cutting-edge in the market. Trigent’s cloud-first strategy is made to meet the clients’ needs by driving acceleration, customer insight, and connected experience to take businesses to the next orbit of cloud transformation. Their team exhibits the highest potential in cloud computing that improves business results across the key performance indicators (KPIs). The Trigent team is instilled with productivity, operational efficiency, and growth that increases profitability.

The team possesses years of experience and works attentively in the cloud adoption journey of their clients. The professionals curate all their knowledge to bring the best of services to the table. This way, the clients can seamlessly achieve goals and secure their place as a modern cloud based-enterprise. Their vigorous effort has placed them as the top cloud companies in Bangalore at GoodFirms website.

Propelling Business with Software Testing

Continuous efforts and innovations are essential for businesses to outpace in the competitive market. The Trigent team offers next-gen software testing services to warrant the delivery of superior quality software products that are release ready. The team uses agile – continuous integration, continuous deployment – and shift-left approaches by utilizing validated, automated tools. The team expertise covers functional, security, performance, usability, accessibility testing that extends across mobile, web, cloud, and microservices deployment.

The company caters to clients of all sizes across different industries. The clients have also sustained substantial growth by harnessing their decade-long experience and domain-knowledge. Bridging the gap between companies and customers and using agile methodology for test advisory & consulting, test automation, accessibility assurance, security testing, end to end functional testing, performance testing the company holds expertise in all. Thus, the company is dubbed as the top software testing company in Massachusetts at GoodFirms.

Optimizing Work with Artificial Intelligence

Artificial intelligence has been the emerging technology for many industries during the past decade. AI is defining technology by taking it to a whole new level of automation where machine learning, natural language process, and neural networks are used to deliver solutions. At Trigent, the team promises to support clients by utilizing AI and providing faster, more effective outcomes. By serving diverse industries with complete AI operating models – strategy, design, development, and execution – the firm is automating tasks. They are focused on empowering brands by adding machine capabilities to human intelligence and simplifying operations.

The AI development teams at Trigent are appropriately applying the resources to identify and govern a process that empowers and innovate business intelligence. Besides, with their help with continuous processes enhancements and AI feedback systems, many companies have been increasing productivity and revenues. Therefore, helping clients to earn profit with artificial intelligence, the firm would soon rank in the list of the artificial intelligence programming company at GoodFirms.

About GoodFirms

GoodFirms, a maverick B2B Research and Reviews Company helps in finding Cloud Computing, Testing Services, and Artificial Intelligence firms rendering the best services to its customers. Their  extensive research process ranks the companies, boosts their online reputation and helps service seekers pick the right technology partner that meets their business needs.

Responsible Testing in the Times of COVID

As a software tester, I have ensured that software products and applications function and perform as expected. My team has been at the forefront of using the latest tools and platforms to enable a minimal defect product for the market release. We are proud to have exceeded industry standards in terms of defect escape ratios.

The health scare COVID has interrupted almost all industries and processes, but society is resilient, never gives up, and life (and business) must go on. We are up to the task and giving our best in adapting to the testing times and situations.

Testing times for a software tester

While we have leveraged existing resources and technology to run umpteen tests in the past, the current pandemic that has enveloped the world has put us in unchartered territory. While our clients understand the gravity of the situation, they also need to keep their business running. We now work from home and continue testing products just like before without interruption. There have been challenges, but we have ensured business continuity to protect our client from any adverse impact of this disruption. From our testers struggling to adapt to the new world order, I would like to share how we sailed through these trying times. It might help you do what you do best, test!

Ensure access, security/integrity

As testers, we work in different environments such as on-prem, on the cloud, or the client-side cloud environment. Working from a secure office environment, we have access to all environments. It is not the same anymore, as we now use public networks. The best and most secure way to access governed environments is to connect via a VPN to access different environments securely. VPN’s offer secure, pre-engineered access and provide additional levels of bandwidth and control.

Use cloud-devices for compatibility tests

Testing applications for different platforms and devices is simpler at the workplace as we have ready access to company-owned devices (some of which are expensive). It’s not the same when working from home. Besides, these devices cannot be a shared resource. The unavailability of devices cannot act as a blockade. I am leveraging the cloud using resources such as SauceLab, Devicefarm alongside options such as simulators and emulators configured on my system.

Augment access speed for reliable testing

One concern working from home is the need for a dependable, high-speed internet connection. However, I signed up with a service provider offering verified speed. I buttressed my connectivity by arranging for an alternate internet connection from a different service provider with similar bandwidth capability. I made a distinction between these networks as network1 and network2, ensuring that the networks get utilized for the designated purpose, and bandwidth issues avoided.

Coordinate test plans with collaboration utilities

In the initial days of the work-from-home arrangement, I found it difficult to coordinate with the team and there were productivity concerns. This is when we decided to chalk a schedule to address coordination issues. We decided to better utilize the messenger tools provided to us for seamless communication. As a first step towards making optimal use of these messenger tools we drew guidelines on the do’s and don’ts to optimally use our time. This article penned by a senior colleague worked as a handy reference on using one such communication tool.

The future looks uncertain with Covid’s impact deepening by the day. In these times when everything looks uncertain we as responsible testers can play our role in ensuring that we are available to our partners and help products and apps reach their respective audience.

Can Machine Learning Power the Future of Software Testing?

Machine learning in software testing

Software testing professionals today are under immense pressure to make faster risk-based, go-live decisions, what with DevOps practices having shrunk the time to deliver test results. What was expected every two weeks is now expected umpteen times in a day.

The job of a tester has also become more demanding due to increasing complexities in applications. Testers are now expected to deliver a go/no go decision that compliments fast-paced development and deployment.

A recent piece announcing the launch of a data-driven ML-powered engine to assist testers sounds promising, but will it deliver on the promise?

Kawaguchi’s reasoning behind his new venture is based on the way different industries have benefited by using data to drive processes and efficiencies. He opines that the same can be replicated in the software industry, specifically to the practice of software testing.

Through Launchable, Kawaguchi plans to utilize machine learning to help provide quantifiable indicators that help testers perform risk-based testing and get a clear understanding of the quality and impact of the software when ready for deployment.

A machine learning engine is expected to predict test cases that could fail due to changes in the source code. Knowing in advance about test cases that are poised for failure would allow testers to run a subset of tests in an order that would minimize the feedback delay.

Our view on the use of machine learning in software testing

As testers, skeptics we are!!

Whilst there is no doubt that time to deliver has become a significant constraint for testers and automation helps to speed things up, the selection of tests to automate is still an expert-driven process.

When the quantum of changes are small and changes localized, we may probably be able to have an AI algorithm, that through a reduced set of features, can arrive at an intelligent risk assessment.

However, as testers, we have also seen that a small quantum of changes can result in a large regression impact. In this case, the feature set we may need to assess may be insufficient.

What if the quantum of change is large. The features that the algorithm needs to consider may not be limited to code alone, but also depend on a lot of external factors, including business considerations to drive the test focus decision. That makes the data points required for decision making, sizable.

To date, the ability of AI to replace human instinct and interplay is yet to be proven!

Until such a time, that one understands the features considered to assess risk. The biases that the algorithm may have absorbed while being trained. And that AI can replace critical thinking is proven – this will be one more output that will need to get assessed for the possible risk it can pose to the decision-making process.

Kosuke Kawaguchi is confident about his approach. That’s the claim he made when he announced the launch of his startup. We have eagerly signed up for a beta here, and will keenly observe the impact that these set of AI algorithms have on software testing.

Here’s to more innovations in this sphere!!

Learn more about Trigent software testing services or functional testing services.

Can your TMS Application Weather the Competition?

The transportation and logistics industry is growing dependent on diverse transportation management systems (TMS). This is true not only for the big shippers but also for small companies triggered by different rates, international operations, and competitive landscape. Gartner’s 2019 Magic Quadrant for Transportation Management Systems summarizes the growing importance of TMS solutions when it says, “Modern supply chains require an easy-to-use, flexible and scale TMS solution with broad global coverage. In a competitive transportation and logistics environment, TMS solutions help organizations to meet service commitments at the lowest cost.

For TMS solution providers, the path to developing or modernizing applications is not as simple as cruising calm seas. Their challenges are myriad and relate to ensuring systems that organize quotes seamlessly (no jumping from phone to a website). They need to help customers to select the ideal carrier based on temperature, time, and load to ensure maximized benefits. Very importantly, they need to help customers to track shipments while managing multiple carrier options and freight. Customers look for answers, and TMS solutions should be able to provide customers the best options in carriers. All this does not come easy and while developing and executing the solution is half of it, the more critical half lies in ensuring that the system’s functionality, security, and performance remain uncompromised. When looking for a TMS solution, customers look for providers who can present a clear picture of the total cost of ownership. Unpredictability is a no-no in this business which essentially means that the solution is implemented and tested for 100 percent performance and functionality.

Testing Makes the Difference

The TMS solution providers who will be able to sustain their competitive edge are the ones who have tested their solution from all angles and are sure of its superiority.

In a recent case study that explains the importance of testing, a cloud-based trucking intelligence company provides solutions to help fleets improve safety and compliance while reducing costs invested in a futuristic onboard telematics product. The product manages several processes and functions to provide accurate and real-time information such as tracking fleet vehicles, controlling unauthorized access to the company’s fleet assets, and mapping real-me vehicle location. The client’s customers know more about their trucks on the road using pressure monitoring, fault code monitoring, and remote diagnostics link. The onboard device records and transmits information such as speed, RPMs and idle time, distance traveled, etc. in real-time to a central server using a cellular data network.

The data stored in the central server is accessed using the associated web application via the internet. The web application also provides a driver portal for the drivers to know/edit their hours of service logs. Since the system deals with mission-critical business processes, providing accurate and real-time information is key to its success.

The challenge was to set up a test environment for the onboard device to accurately simulate the environment in the truck and simulate the transmission of data to the central server. Establishing appropriate harnesses to test the hardware and software interface was equally challenging. The other challenges were the simulation and real-time data generation of the vehicle movement using a simulator GPS.

A test lab was set up with various versions of the hardware and software and integration points with simulators. With use-case methodology and user interviews, test scenarios were chalked out to test the rich functionality and usage of the device. Functional testing and regression testing of new releases for both the onboard equipment and web application were undertaken. For each of the client’s built-in products, end-to-end testing was conducted.

As a result of the testing services, the IoT platform experienced shortened functional release cycles. The comprehensive test coverage ensured better GPS validation, reduced preventive cost by identification of holistic test cases, reduced detection cost by performing pre-emptive tests like integration testing.

Testing Integral to Functional Superiority for TMS 

As seen in the case study above, developing, integrating, operating, and maintaining a TMS is a challenging business. There are several stakeholders and a complex process that includes integrated hardware, software, humans, and processes performing myriad functions, making the TMS’s performance heavily reliant on its functioning. Adding complexity is the input/output of data, command, and control, data analysis, and communication. As a result of its complexity and the importance of its functioning in managing shipping and logistics, testing is an essential aspect of a TMS.

Testing TMS solutions from the functional, performance design and implementation aspect will ensure that:

  • Shipping loads are accurate, and there are no unwelcome surprises
  • Mobile status updates eliminate human intervention and provide real-time updates.
  • Electronic record management to ensure the workflow is smooth and accurate
  • Connectivity information to eliminate issues with shift changes and visibility
  • API integration to seamlessly communicate with customers.
  • Managing risk for both the TMS and the system’s partners/vendors.

TMS software providers need to offer new features and capabilities faster to be competitive, win more customers, and retain their business. Whether it relates to seamless dispatch workflows, freight billing or EDI, Trigent can help. Know more about Trigent’s Transportation & Logistics solutions

Five Business Benefits of On-Demand Testing

Constantly shifting economic conditions has resulted in businesses tightening their IT budgets to control costs and remain competitive. However, while budgets are limited, expectations from IT managers are only growing larger. Most companies today have an online presence, and they need to frequently upgrade and innovate their offerings to stay competitive. This has led to new features, apps, and products being unleashed at a rapid space. There is also an uncompromising world of usability that requires released products and apps to be fault-free. However, the bottom line is, budgets remain controlled.

On-demand testing or Testing as a Service (TaaS) is a realistic option for stringent budgets and tight deadlines. Reliable service providers, who offer on-demand testing, have the capabilities for testing in cloud-based or on-premise environments. More often than not, these providers have a wide array of tools, assets, frameworks, and test environments.

End-to-end testing services that you need on on-demand basis.

On-demand testing is offered by companies that are confident of taking on the responsibility of transferred ownership. For QA and IT managers, the risks attached to testing and the costs for tools can be assigned to service providers thereby immediately diminishing both risk and added expenditures.

Unlike other services, on-demand testing is demanding in its expectations. Those offering this service cannot afford to escape, bugs, slipped deadlines, and, therefore, the advantages far outweigh the effort involved in sourcing the right partner.

Some of the benefits of On-Demand Testing are:

1. As costs are negotiated and finalized with the partner, the probability of unexpected expenses is brought down considerably. There is a commitment agreed upon and that helps in better budget allocation. There are instances where clients have experienced over 50 percent savings in costs. However, the savings are dependent on the choice of the service provider.

2. Dynamic and scalable testing requirements benefit from on-demand testing, where the partner’s team can depute several test engineers on to the job, reducing testing time drastically. For example, imagine a small number of 3-5 in house engineers who are caught up in multiple projects, to a dedicated team of any number of test engineers focused on a single project. The advantage in terms of time spent can itself become a key advantage.

3. On-demand testing is especially useful for load, performance, and last-mile testing where real-life scenarios need to be created. With real-life test environments at their disposal, service providers are capable of maximizing test coverage and results in limited time frames.

4. Time-to-market can be reduced when partners are involved, as they will help to plan and schedule test cycles without any delays. In such cases, the saved time can be at least 30 percent.

5. Reliable on-demand testing service providers offer standardized infrastructure, frameworks, and pre-configured environments to ensure that configuration errors do not creep in after release.

Trigent’s SwifTest is a pay-as-you-go software testing service that is best suited to gain instant access to qualified professional software testers without any long-term contracts. Trigent will perform end-to-end functional testing of your web or mobile applications. Our service is offered on inclusive environments of mobile devices, operating systems, and browsers – to help you validate your product at a pace faster than traditional outsourced testing service. Our certified testing specialists will ensure all user functions (links, menus, buttons, etc.) are working properly on target devices and browsers. We’ll perform exploratory testing and follow your specified test steps. This Development-QA follow-the-sun model reduces project duration and increases responsiveness. You pay only for the time that you engage our QA engineers/team-as little as one day (8 hours) / a week / or a month.
Read More

Getting Started with Load Testing of Web Applications using JMeter

Apache JMeter:

JMeter is one of the most popular open source testing tools for load and performance testing services. It simulates browser behavior, sending requests to the web or application server for different loads. Volume testing using JMeter on your local machine, you can scale up to approximately 100 virtual users, but you can go up to more than 1,000,000 Virtual Users with CA BlazeMeter, which is sort of a JMeter in the cloud.

Downloading and Running the Apache JMeter:

Requirements:

Since JMeter is a pure Java-based application, the system should Java 8 version or higher.

Check for Java installation: Go to Command prompt, type `Java –version’, if Java is installed it will show as the Java version as below.

Related: Improved time to market and maximized business impact with minimal schedule variance and business risk.

If Java is not installed, download and install Java from the following link: “http://bit.ly/2EMmFdt

Downloading JMeter:
  • Download the latest version of JMeter from “Apache JMeter
  • Click on apache-jmeter-3.3.zip from Binaries.

How to Run the JMeter:

You can start JMeter in 3 ways:

  • GUI Mode
  • Server Mode
  • Command Line

GUI Mode: Extract the downloaded Zip file in any of your drives, go to the bin folder D:apache-jmeter-3.2bin–> double click on “jmeter” windows Batch file.

After that will appear the JMeter GUI as shown below:

Before you start recording the test script, configure the browser to use the JMeter Proxy.

How to configure Mozilla Firefox browser to Use the JMeter Proxy:

  • Launch the Mozilla Firefox browser–> click on Tools Menu–> Choose Options
  • In Network Proxy section –> Choose Settings
  • Select Manual Proxy Configuration option
  • Enter value for HTTP Proxy as localhost or you can enter your local system IP address.
  • Enter the port as 8080 or you can change the port number if 8080 port is not free
  • Click on OK. Now your browser is configured with the JMeter proxy server.

Record the Test Script of Web Application:

Add a Thread Group to the Test Plan: Test Plan is our JMeter script and it will tell about the flow of our load test.

Select the Test plan –> Right click–> Add–> Threads (Users) –> Thread Group

Thread Group:

Thread group will tell about the user flow and will simulates like how user will behave on the app

The thread group has three important properties, which influence the load test:

  • Number of threads(users): This will tell about the number of Virtual users that JMeter will attempt to simulate, let’s say for ex:1,10,20 or 50 etc
  • Ramp Up Period (in seconds): The duration of time that you want to allow the Thread Group to go from 0 to n (20 here) users, let’s say 5 seconds.
  • Loop count: No of times to execute the test, 1 means the test will execute for 1 time.
2. Add Recording controller to the thread group: Recording controller should have all the recorded HTTP Request Samples.

Select the thread group –> right click–> Add –> Logic Controller –> recording controller

3. Add the HTTP Cookie Manager to the thread group:

Http Cookie manager is to use cookies on your web app

4. Add View Results tree to the thread group: View results Tree used to see the Status of the Http Sample Requests on Executing the Recorded Script.

Thread group –> Add–> Listeners–> View Result Tree

5. Add Summary Report: Summary report will show the test results of the script

Thread group –> Add –> Listeners –> Summary Report.

6. Go to the WorkBench and Add the HTTP(S) Test Script Recorder: Here you can start your test script recording.

WorkBench –> Right click –> Add–> Non Test Elements –> HTTP(S) Test Script Recorder.

Check whether the port 8080 (this should be same as which we have set for the browser port number) is available or busy in your system. If it’s busy change the port number.

7. Finally click the Start button –> you can see the popup –> click ok

8. How to Record the browsing files from the Web App:

If your test script is having option like browse any files, keep your files in bin folder of JMeter and do recording of browse files.

Go to the Mozilla Browser–>Start your Test for Ex:login page or any navigation, do not close the JMeter while recording the script. The script will record as below in Recording Controller.

Save the Test Plan with .jmx extension.

Run the Recorded Script: Select the Test Plan–>Press ctrl+R from the Key board or Start Button on Jmeter.

while executing the script ,at the top right corner a circle will display in green color along with the time box which will show how much time the script is executing. Once the Execution completed the Green circle will turn to Grey.

Test Results: We can see the Test Results in many ways like, View Results Tree, Summary Report, and Aggregate Graph.

View Result Tree

Summary Report:

After executing the test script, go to Summary Report–>click on Save Table data and save the results in a .csv or xlsx format.

Though we will get the test results in Graphical view and Summary report etc, executing Test Scripts Using JMeter GUI is not a good practice. I will discuss the execution of JMeter Test Scripts with Jenkins Integration tool in my next blog.

Read Other Blog on Load Testing:

Load/Performance Testing Using JMeter

Artificial Intelligence (AI) and Its Impact on Software Testing

Enterprises impacted by ‘Digital Disruption‘ are forced to innovate on the go, while delighting customers and increasing operational efficiency. As a result, software development teams who are used to time-consuming development cycles do not have the luxury of time any longer. Delivery times are decreasing, but technical complexity is increasing with emphasis on user experience!

Continuous Testing has been able to somewhat cope with the rigorous software development cycles, but keeping in mind the rapid speed with which innovation is transforming the digital world, it might just fall short. What is therefore needed is the ability to deliver world-class user experiences, while maintaining delivery momentum and not compromising on technical complexity. To meet the challenges of accelerated delivery and technical complexity requires test engineers to test smarter instead of harder.

So what has all this got to do with Artificial Intelligence (AI)?

The fact is, AI and software testing were never discussed together. However, AI can play an important role in testing and it has already begun transforming testing as a function and helping development teams to identify bug-fixes early, assess, and correct code faster than ever before. Using Test Analytics, AI-powered systems could generate Predictive Analytics – to identify specific areas of the software most likely to break.

Before delving into AI-based software testing, it might be good to understand what AI actually means. Forrester defines AI as “A system, built through coding, business rules, and increasingly self-learning capabilities, that is able to supplement human cognition and activities and interacts with humans natural, but also understands the environment, solves human problems, and performs human tasks.”

Related: Improved time to market and maximized business impact with minimal schedule variance and business risk

AI is providing the canvas for software testing but its uses have to be defined by testers. Some engineers have already tested their imagination and they use AI to simplify test management by creating test cases automatically. They know that AI could help to reduce the level of effort (LOE) while ensuring adherence to built-in standards.

AI could also help to generate code-less test automation, which would create and run tests automatically on a web or mobile application. AI-based testing could identify the ‘missing requirement’ from the Requirements document, based on bug-requirement maps.

Machine learning bots are capable of helping with testing especially with end-user experience taking the front seat in testing. When trying to understand the role of bots in software testing, we need to bear in mind the fact that most applications have some similarities, i.e. size of a screen, shopping carts, search boxes, and so forth. Bots can be trained to be specialists in a particular area of an app. AI bots can manage tens of thousands of test cases when compared to regression testing which can handle much lesser numbers. It is this ability of AI testing that elevates its importance in the DevOps age where iteration happens on-the-go.

To summarize, while bots do some of the routine stuff, testers can focus on more complex tasks, taking the monotony out of testing and replacing it with the word ‘exciting’.

Learn more about Trigent’s automation testing services.

Read Other Blog on Artificial Intelligence: 

The Impact of Artificial Intelligence on the Healthcare Industry

Getting Started – Selenium with Python Bindings

Introduction

Selenium Python binding provides a simple API to write functional/acceptance tests using Selenium WebDriver. Through Selenium Python API you can access all functionalities of Selenium WebDriver in an intuitive way. Selenium Python bindings also provide a convenient API to access Selenium WebDrivers such as Firefox, IE, Chrome, etc. The current supported Python versions are 2.7, 3.5, and above. In this blog, I will explain the Selenium 3 WebDriver API and in the next one, I will explain how to install and configure PyDev in Eclipse.

What is Python?

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It’s high-level built in data structures, combined with dynamic typing and binding, makes it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy-to-learn syntax emphasizes readability, and, therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form, free of charge, for all major platforms, and can be freely distributed.

Related: Define, Implement, Migrate and Script Automated Tests for End-to-end Automation of Applications Spanning Multiple Technologies.

What is Selenium?

Selenium is an open-source automation tool to test your web application. You can do this in various ways. For instance:

  • Selenium supports multiple languages such as Java, C#, Python, Ruby etc..
  • Selenium has components like, IDE, WebDriver.

Downloading Python bindings for Selenium

You can download Python bindings for Selenium from the PyPI page for the Selenium package. However, a better approach would be to use pip to install the selenium package. Python 3.6 has pip available in the standard library. Using pip, you can install selenium like this: `pip install selenium’. You may consider using virtualenv to create isolated Python environments. Python 3.6 has pyvenv which is almost the same as virtualenv.

Detailed instructions for Windows users

Note: You should have an Internet connection to perform this installation.

  1. Install Python 3.6 using the MSI available in python.org download page.
  2. Start a command prompt using the cmd.exe program and run the pip command as given below to install selenium.

C:Python35Scriptspip.exe install selenium.

Advantages of Python in Selenium

  1. Compared to other languages, Python takes less time to run the script and complete the execution.
  2. Python uses indentation, not braces ({}), making it easy to understand the code flow.
  3. Python is simpler and more compact.

Simple Usage

If you have installed Selenium Python bindings, you can start using it from Python in the following way:

from selenium import webdriver
 from selenium.webdriver.common.keys import Keys
 driver = webdriver.Firefox()
 driver.get("http://www.python.org")
 assert "Python" in driver.title
 elem = driver.find_element_by_name("q")
 elem.clear()
 elem.send_keys("pycon")
 elem.send_keys(Keys.RETURN)
 assert "No results found." not in driver.page_source
 driver.close()

If you found this interesting, don’t miss my next blog, ‘Install and Configure PyDev in Eclipse’.

Read Other Selenium related blogs:

Web Application Testing with Selenium WebDriver

Introduction to Selenium with C Sharp

The Six Principles of Security Testing

The philosophy of Responsible Testing is driven by a defined process that provides an additional layer of security for the software product. Read here. 

Security Testing ensures that an application is protected from malicious activities and maintains functionality as intended. It helps applications to ensure that their sensitive data/information is not subjected to any breach.

If an application is not secure and a hacker finds a vulnerability in the application, it will be exploited, with predictable outcomes such as:

  • Damage to an organization’s brand name
  • Negative impact on customer impression with the added risk of relationship loss.
  • Added costs related to fixing the vulnerability post-production

Related: Identify and Mitigate Security Risks with Proven Security Testing Strategies

The Six Principles of Security Testing to Secure the Environment:

  1. Confidentiality: This is equivalent to privacy, and it has a set of rules which limits access to information. It protects against disclosure of information to unintended recipients, and is designed to prevent sensitive information from reaching the wrong people. It ensures that only the designated person gets the information and access will be restricted to those authorized to view the data in question.
  2. Integrity: It involves maintaining the consistency, accuracy, and trustworthiness of data over its entire life cycle, and allows transferring accurate and desired information from senders to intended receivers. It ensures that data cannot be altered by unauthorized people (for example, in a breach of confidentiality).
  3. Authentication: This confirms the identity of a user and allows a user to have confidence that the information he receives originated from specific known sources.
  4. Authorization: It specifies access rights to the users, based on the user role.
  5. Availability: Ensures the readiness of the information on requirement. To simplify, information must be available to authorized person(s) when they require it. Availability is best ensured by rigorously maintaining all hardware, performing hardware repairs immediately when needed and maintaining a correctly functioning operating system environment that is free of software conflicts. [ref: http://whatis.techtarget.com/definition/Confidentiality-integrity-and-availability-CIA]
  6. Non-repudiation: This ensures there is no denial from the sender or the receiver for sent /received messages. It exchanges authentication information with provable time stamp, for example, `session id’ and so forth.

Confidentiality, Integrity and Availability, also known as the CIA triad, is a model designed to guide policies for information security within a company. The model is also sometimes referred to as the AIC triad (Availability, Integrity and Confidentiality) to avoid being confused with the Central Intelligence Agency. [Ref: http://whatis.techtarget.com/definition/Confidentiality-integrity-and-availability-CIA]

There are different techniques which are used in Security Testing:

  • SQL Injection: This technique consists of injecting a SQL query using input fields of the application as a hacker can perform a CRUD operation in the application if the DB is not secure.
  • Broken Authentication and Session Management: Authentication and session management includes all aspects of handling user authentication and managing active sessions. When authentication is not implemented correctly or it is broken, it empowers hackers to compromise passwords or session ID’s or to exploit other implementation flaws using other users’ credentials.
  • Cross-Site Scripting (XSS): This is a type of injection which allows attackers to inject Client side script, malicious scripts or URLs into web applications. A cross-site scripting vulnerability may be used by attackers to bypass access controls such as the same-origin policy.
  • Insecure Direct Object References: This occurs when an application provides direct access to objects based on user-supplied input. As a result of this vulnerability attackers can bypass authorization and access resources in the system directly, for example database records or files.
  • Security Misconfiguration: This is one of the easiest targets for hackers because it is commonplace. Configuration weaknesses are usually found in web applications like weak or default passwords, out-of-date software, unnecessary features that are enabled, and unprotected files or databases.
  • Sensitive Data Exposure: This remains a major concern affecting almost every company around the globe that uses web applications. This occurs when an application does not adequately protect sensitive information from being disclosed to attackers. It includes information such as Credit card/Bank Account, health records, personal Information etc.,
  • Missing Function Level Access Control: One should verify the functional level access rights for all requested actions by a user. If it is not checked, unauthorized users may be able to penetrate critical areas of web applications without proper authorization.
  • Cross-Site Request Forgery (CSRF): A Cross-site Request Forgery, aka CSRF or one-click attack, is a diffused security issue where unauthorized commands are sent from the user’s browser to a web site or a web application. CSRF attack can force the user to perform state changing requests like transferring funds, changing their email address and so on.
  • Using Components with Known Vulnerabilities: Vulnerabilities in third-party libraries and software – OS itself, CMSs used, the web server, plugins installed – are extremely common and could be used to compromise the security of systems using the software. Known Security vulnerabilities are gaps in security that have been identified either by the developers/vendor of the product, used by the user/developer or by intruder/hacker.
  • Un-validated Redirects and Forwards: This occurs when an attacker is able to redirect or forward a user to an untrusted site when the user visits a link located on a trusted website. Without proper validation, attackers can redirect victims to phishing or malware sites. This vulnerability is also often called Open Redirect.