How to Overcome Platform Quality and Reliability Challenges

Software testing is a crucial part of product development. Every product must go through multiple and meticulous testing before being placed in the hands of the end-user or a customer.

However, as the pace of application delivery demands have accelerated, enterprises continue to deal with a range of platform quality and reliability challenges with software testing programs, such as:

  • Shorter release cycles while maintaining quality; long-running regression cycles leading to long test execution cycles. Nearly 60% of North American enterprises want production releases every two weeks or less, but only 30% of test cases are automated.
  • Multiple test configurations, environments, and experiences leading to testing errors.  It is hard to get an end-to-end view of test programs with so many tools, frameworks, and technologies.
  • They want speed to value, and product quality, but are under pressure to deliver high-quality applications. Add multiple changes to applications with every release, and they run into the “Wall of Confusion” between agility and stability.
  • They are looking for cost efficiency, but are faced with decreasing testing budgets, the high cost of test environment and execution infrastructure.
  • They recognize the need for improved speed and robustness in DevSecOps and the release process, but the compressed time pressure puts test data preparation at risk.

To address these problems, we need Test Automation Frameworks, which are a set of guidelines that institutionalize the creation of test cases and optimize its execution.

Test Automation Frameworks generate test reports which capture the required artifacts for the next best action, such as type of error, automation, configuration, data, and application defect. The framework in principle should help automate the entire workflow using the DevSecOps principle

Test Automation Framework is a conceptual part of automated testing that helps testers to use resources more efficiently. A framework is defined as a set of rules or best practices that can be followed systematically to ensure the desired results.

The following frameworks are used in Automation Testing:

  • Linear Scripting Framework, also referred to as the record and playback model is a scripting driven framework. The creation and execution of test scripts are done individually and in an incremental manner where every new interaction is added to the automation tests.
  • Modular Testing Framework: Independent test scripts based on the modules are developed to test the software. An abstraction layer takes care of the modules to be hidden from the application during the test.
  • Data-Driven Testing Framework: A separate file in tabular format is used to store both the input and the expected output results. A single driver script can execute all the test cases with multiple sets of data.
    • This driver script contains navigation that spreads through the program, covering both readings of data files and logging of test status information.
    • Furthermore, equivalence partitioning and boundary value analysis help create data-driven tests that lead to rather high code coverage while keeping the data sets small.
  • Keyword Driven Testing Framework: An application-independent framework uses data tables and keywords to explain the actions to be performed on the application under test. This is also referred to as a keyword-driven test automation framework for web-based applications and can be stated as an extension of a data-driven testing framework.
  • Hybrid Testing Framework: The combination of modular, data-driven, and keyword test automation frameworks based on the combination of many types of end-to-end testing approaches.
  • Test-Driven Development Framework (TDD): Uses automated unit tests to drive the design of software and separates it from any dependencies.
    • TDD defines use cases, increases the speed of tests,e and improves the confidence that the system meets the requirements; in addition to making sure that it is working adequately compared to traditional testing.
  • Behavior Driven Development Framework (BDD): Tests are based on system behavior. Testers can create use cases in simple English language helping non-technical people to analyze and understand the tests quickly.
    • Automated testing tool for software such as FitNesse, a behavior-driven development framework is built around decision tables.

Testing frameworks are centered around helping design test cases with better coverages.

  • Deriving test cases directly from a requirement specification or black box test design technique.
  • Boundary Value Analysis BVA software testing techniques
  • Equivalence Partitioning EP
  • Decision Table Testing
  • State Transition Diagrams
  • Use Case Testing
  • Deriving test cases directly from the structure of a component or system:
  • Statement Coverage
  • Branch Coverage
  • Path Coverage
  • LCSAJ Testing
  • Deriving test cases based on tester’s experience on similar systems or testers intuition:
  • Error Guessing
  • Exploratory Testing

Test coverages help identify test conditions that are otherwise difficult to recognize.

These challenges can be avoided by adopting the right framework and using testing techniques to ensure better coverages. However, today test cases can be made predictable, by an understanding of the code and the entire SDLC.

This is accomplished by starting from the requirement gathering phase until the end state of incidence in production.

Create “breadcrumbs” that allow you to identify every part of the application, from critical functions to dependencies; understand correlations, important vs. non-important parts; used vs. most used. Study historical data, which helps to determine areas that require attention and the level of test coverages needed.

Based on these “breadcrumbs”, predictability allows you to project/predict what will happen if changes are being made to certain areas of the applications. This will help in predicting “builds” as outcomes. For example, if the model was a success and if not, then what are the reasons for its failure. Once the frameworks are equipped with an accurate, predictable model, companies can plan better, save time, and cost, and go to market faster.

In conclusion, it is safe to say software testing frameworks can be instrumental in helping enterprises achieve better productivity.

Watch this space for the next installment as we talk about shifting left with automation testing.

Infogain’s Ramendeep Singh presents “Testing Digital Platforms” at TESTFEST USA by TESTCON

Infogain’s Ramendeep Singh, VP Solutions and Global Head Business Assurance will present “Testing Digital Platforms” at TESTFEST on December 10th, 2020. He will discuss how testing platforms is changing testing practices. He will also elaborate on why testing platforms is different than testing applications.

TestFest is a series of software testing mini-conferences coming up in USA, South Africa, Australia, England, Philippines, Brazil, Singapore and India with 8 hours of live amazing sessions distributed over 2 days. This event will bring together hundreds of experienced like-minded people, who seek to improve their skills to fit new market requirements and stay tuned with the latest trends! The summit will provide an excellent platform to keep up-to-date with the latest industry trends, exchange experiences, discuss and deliberate ideas and benefit from networking opportunities.

To get insights, register now for more information, or contact us for a consultation.

Infogain Partners with Appvance to Offer AI-driven Advanced Automated Testing

Los Gatos, CA, September 22, 2020: Infogain, a leading provider of technology solutions and an expert in software platform engineering, has announced a strategic partnership with Appvance.ai, the leader in AI-driven test generation. The new partnership will help global businesses tap into the disruptive power of AI-led quality engineering services.

This partnership will strengthen Infogain’s PAQman solutions, which use machine learning driven predictive analytics to enable advanced automated testing. The PAQman Automation module reduces test creation effort by 60%, enabling the use of a single script across all web and mobile OS platforms with multi-locator features. Furthermore, it keeps ‘dev’ and ‘test’ in sync at all times with the help of progressive in-sprint test automation. Implemented along with DevSecOps, PAQman functions as a continuous delivery platform for the organization, lowering costs, and accelerating time to market.

Welcoming the move, Infogain’s Chief Technology & Strategy Officer Nishith Mathur, said, “The team and I are excited to partner with Appvance as we help engineering organizations globally access and harness the disruptive power of AI-driven solutions.  Our clients are already using Infogain’s PAQman solution; our Appvance partnership will help them further reduce test creation effort and runtime regression loads, improving staff, and test automation scripts productivity.”

Commenting on the partnership, Appvance’s Chief Executive Officer Andre Liao said, “Appvance IQ’s patented Machine Learning technologies can autonomously find bugs and write scripts by learning the application and optionally refining tests by analyzing actual user activity 100,000 times faster than human scriptwriters. We are looking forward to collaborating with Infogain and our joint clients who are motivated to transform their Quality Assurance processes, surfacing far more bugs faster with 90% less human effort. We are excited to join forces with Infogain, who possess deep domain expertise in software development and platform engineering.”

Infogain has invested in next-generation QA components such as immersive technologies and cloud-native application testing. Infogain was positioned as a ‘Major Contender’ in Everest Group’s Next-generation Quality Assurance (QA) Services PEAK Matrixä® Assessment 2020 and is recognized as the third-fastest growing engineering services provider in Everest Group’s Engineering Services Top 50TM 2020.

About Infogain

Infogain is a Silicon Valley headquartered company with software platform engineering and deep domain expertise in travel, retail, insurance, and high technology industries. We accelerate the delivery of digital customer engagement systems using digital technologies such as cloud, microservices, robotic process automation, and artificial intelligence to our clients.

Infogain delivers positive business outcomes for Fortune 500 companies and digital natives, using rapid prototyping and a solid foundation of DevSecOps-based software platform engineering that ensures high-quality and on-time delivery. A ChrysCapital portfolio company, Infogain has offices in California, Washington, Texas, London, Dubai, India, and Singapore, with delivery centers in Austin, Kraków, New Delhi, Bangalore, Pune, and Mumbai.

About Appvance

Appvance is the inventor of AI-driven testing, which is revolutionizing the $120B software QA industry. The company’s premier product is Appvance IQ™, the world’s first AI-driven, unified test automation system for web and mobile applications. AIQ empowers enterprises to improve the quality, performance, and security of their most critical applications while transforming the efficiency and output of their testing teams and lowering QA costs. Appvance is headquartered in Santa Clara, California, with additional offices in Rochester, NY, Costa Rica, and India.

For more information, contact:

Infogain
Sarmishtha Sinha
sarmishtha.sinha@infogain.com
+91 8810573274

Archetype 
Suryansh Gaur
suryansh.gaur@archetype.co
+91 9711306903

Software Testing: A Brief History And A Peek Into The Future

Many IT professionals tend to be preoccupied with the testing process.  In some ways, testing is as old as mankind itself.  We can all imagine the “hunter-gatherers” thousands of years ago foraging for new food and asking themselves, ‘is this edible?’, is this tasty? to ‘is this safe to eat?’  Perhaps testing became hardwired in us, as did a nascent scientific nature. Testing continued through the pre-industrial era, where people formed guilds to test product quality, and in the industrial era, for example, with the early testing of suction lift water pumps in steam engines.

Testing or software testing is not a new concept. The testing phase of a product is one of the most important tasks of any business today. Before going to market, every product must go through multiple and meticulous tests that guarantee quality before it’s placed in the hands of the end-user or a customer. When computing emerged, ‘Software Testing’ or measurement of the quality of design used in the software and how it corresponded to the design also gained prominence.

Software testing has followed its own evolutionary path, resulting in an end-to-end framework that is used today.

Software testing started its journey with ‘debugging,’ meaning that in order to debug, one had to look for errors and fix it. Subsequently, Alan Turing wrote the very first article on Testing in 1949 about carrying out checks on a program. Since then, testing has been through three phases, starting with the ‘demonstration period’ (1957–1978) where ‘test development’ was popular. The need to clear these tests became more important as more expensive and complex applications were being developed. In 1979 or the “destruction period,” ‘software testing’ became a process of running a program with the intention of finding errors. Finally, in the ‘evaluation period’ (1983–1987), a methodology was proposed that integrated analysis, revision, and testing activities during the software life cycle to obtain an evaluation of the product during the development process.

The current phase or the ‘prevention phase’ has redefined software testing. This phase encompasses the planning, design, construction, maintenance, and execution of tests and test environments. In addition, testing has become a core process in the Systems Development Lifecycle (SDLC), involving several technical and non-technical aspects that include specification, design and implementation, maintenance, process, and management. Businesses advanced their application deployment methods to match evolving business climates and needs, which in turn places QA organizations under tremendous pressure. The increased adoption of DevOps and Agile have forced QA to shorten testing cycles.

Software Testing: The Future

While the pace of application delivery demands accelerated, QA organizations still need to ensure proper test case coverage across functional, regression, usability, integration, performance, and security testing. However, many continue to struggle with an inefficient, expensive, and error-prone manual testing approach; an approach that no longer fits the DevOps and Agile model. Software testing in the future (now):

  1. Leverages automation: Applying automation to testing that went beyond test script execution and test case development enabled organizations to drive more value from their quality assurance program. However, to keep pace with the agile model of development, traditional test automation proved inadequate. Testing organizations needed to innovate with new and emerging technology solutions around automation.
  2. QA + AI and ML: Intelligent Automation solutions are the next and perhaps most promising step in the testing journey. Intelligent automation enhances test quality using predictive analytics supported by Artificial Intelligence (AI) and Machine Learning (ML).

Many businesses have advanced their application deployment methods to match evolving business climates and needs, putting QA organizations under tremendous pressure. The increased adoption of DevOps and Agile forced QA to shorten testing cycles. There is now room for a next-generation test automation framework designed to power Continuous Quality Engine that is an amalgamation of Automation, AI, and ML. The newer framework leads to predictive intelligence for the test planning process by highlighting potential points of failure.

PAQman is Infogain’s next-generation test automation framework designed to power Continuous Quality Engine. It is a machine learning-driven predictive intelligence for the test planning process by highlighting potential points of failure. PAQman uses in-sprint test automation compatible with CI/CD pipelines and behavior-driven development for applications on the web or mobile platforms, modern-day microservices or web services architecture, database testing, and traditional desktop applications. The module is fully integrated with DevSecOps tools.

This article is first in a blog series that will cover predictive scenarios and modules under predictive analytics for quality.

Infogain Named ‘Major Contender’ in Everest Group’s 2020 Quality Assurance Services PEAK Matrix® Assessment

Los Gatos, CA, January 14, 2020: Infogain, a leading provider of technology solutions is pleased to announce that it has been positioned as a ‘Major Contender’ in Everest Group’s Next-generation Quality Assurance (QA) Services PEAK Matrix ® Assessment 2020.

The assessment is based on Everest Group’s evaluation of close to 20 software product engineering service providers to identify only the best-in-class service providers/technology vendors as Leaders, Major Contenders or Aspirants.

Infogain was evaluated on ‘Market Impact’ mapping factors that include market adoption, portfolio mix, delivered value, and ‘Vision and Capability’ is based on strategy, scope of services, delivery footprint, innovation and investments. Everest Group also analyzed customer responses from surveys and interactions, including service provider performance, benchmarking, priorities and best practices.

Cathy Chandhok, Chief Marketing Officer at Infogain said, “We are thrilled to be recognized as a major contender for Quality Assurance Services in 2020. Gaining recognition as a Major Contender for Software Product Engineering Services earlier this year and now for Quality Assurance Services, is a great testimonial to Infogain’s product development expertise and relentless commitment to delivering value to our customers.”

Nishith Mathur, Chief Technology and Strategy Officer at Infogain, commented, “Infogain’s PAQman enables predictive analytics driven advanced automated testing by integrating intelligent automation using machine learning (ML) and artificial intelligence (AI) in the end-to-end testing value chain, helping enterprises achieve speed, efficiency and accuracy.”

Yugal Joshi Vice President at Everest Group said, The QA technology market is evolving, with enterprises at various stages in their transition between automating traditional QA for legacy technologies and implementing cutting-edge QA for emerging technologies. To serve this evolving market, Infogain has invested in IP and proof points in next-generation QA areas such as immersive technologies and cloud-native application testing, and built expertise in QA’s evolved role in engagements across multiple technology stacks”

Infogain’s Quality Assurance solutions include its PAQman testing automation module and its PAQman defect prediction module. These cover all domain functions including technical, functional, performance, data and security testing.” With Infogain’s DevSecOps approach, organizations achieve speed, efficiency and accuracy, while adopting a proactive approach to development.

Everest Group is a consulting and research firm focused on strategic IT, business services and engineering services. To view the full report, click here.

About Infogain

Infogain is a Silicon Valley headquartered company with software platform engineering and deep domain expertise in travel, retail, insurance and high technology industries. We accelerate the delivery of digital customer engagement systems using digital technologies such as cloud, microservices, robotic process automation and artificial intelligence to our clients.

Infogain delivers positive business outcomes for Fortune 500 companies and digital natives, using rapid prototyping and a solid foundation of DevSecOps-based software platform engineering that ensure high-quality and on-time delivery. A ChrysCapital portfolio company, Infogain has offices in California, Washington, Texas, London, Dubai, India and Singapore, with delivery centers in Austin, New Delhi, Bangalore, Pune, and Mumbai.

 

For more information, contact: 

Infogain

Sarmishtha Sinha
Sarmishtha.sinha@infogain.com
+91 8810573274

Archetype

Suryansh Gaur
suryansh.gaur@archetype.co
+91 9711306903