
<p>Testing software is like ensuring a puzzle&#8217;s pieces fit perfectly together. However, sometimes, the pieces don’t align as expected, leading to testing failures. Let&#8217;s dive deeper into these challenges, understand why they happen, and explore effective solutions to create a seamless testing process.</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#1_Inadequate_Requirements"><span class="toc_number toc_depth_1">1</span> 1. Inadequate Requirements:</a></li><li><a href="#2_Miscommunication"><span class="toc_number toc_depth_1">2</span> 2. Miscommunication:</a></li><li><a href="#3_Wrong_Tool_Selection"><span class="toc_number toc_depth_1">3</span> 3. Wrong Tool Selection:</a></li><li><a href="#4_Lack_of_User_Interaction"><span class="toc_number toc_depth_1">4</span> 4. Lack of User Interaction:</a></li><li><a href="#5_Not_Asking_Enough_Questions"><span class="toc_number toc_depth_1">5</span> 5. Not Asking Enough Questions:</a></li><li><a href="#6_Not_Having_a_Motivated_Workforce"><span class="toc_number toc_depth_1">6</span> 6. Not Having a Motivated Workforce:</a></li><li><a href="#7_Unrealistic_Expectations"><span class="toc_number toc_depth_1">7</span> 7. Unrealistic Expectations:</a></li><li><a href="#8_Not_having_a_good_test_strategy"><span class="toc_number toc_depth_1">8</span> 8. Not having a good test strategy :</a></li></ul></div>
<h2 id="h-1-inadequate-requirements"><span id="1_Inadequate_Requirements"><strong>1. Inadequate Requirements:</strong></span></h2>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh3.googleusercontent.com/rC8L7mWrTshhlz86CgCVVnIVW6crDYTsSWDM-5UhQMh1soFXxl1vJIBlIA479jytfaoQ5xTcJrm2pRA8GIpaN2z6O8wTQih8Y_fguQSHcqGblQv3on04Ifax3-8_V1DqrL2FyOj3nJq8CtlRFGqd7DI" alt="Inadequate Requirements"/></figure></div>



<p>Understanding what the customer needs is like having a clear map to your destination. Incomplete or vague instructions can lead to confusion. Gathering detailed requirements ensures everyone is on the same page, preventing misunderstandings later on. The more details we have, the smoother the testing process becomes.</p>



<p><strong>Solution:</strong>&nbsp;</p>



<ul><li><strong>Regular meetings: </strong>Facilitate regular meetings with clients and stakeholders.<br></li><li><strong>Detailed documentation</strong>: Maintain comprehensive documentation outlining client requirements. Detailed records serve as a reference, ensuring that every aspect of the project is clearly defined,<br></li></ul>



<h2 id="2-miscommunication"><span id="2_Miscommunication"><strong>2. Miscommunication:</strong></span></h2>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh3.googleusercontent.com/wOaHemswjjIN57K0v_rw58dNhWk5r8H7fskpwf4NnGJ8bjMaYCk4pgBCxqJnIn_ZEcPJP4QQHZFFmRlg_oOE9ey3YOLpSSJ9-MoVVrM6PebzdlYXKd-hMS77zotCLVZ7qqokPNIyLq7jUukRYkU1Vxo" alt="Miscommunication"/></figure></div>



<p>Effective communication is like the glue that holds a team together. If there are gaps in communication, team members might not understand each other&#8217;s perspectives. Clear and open channels of communication prevent assumptions and misunderstandings, ensuring everyone is working towards the same goals.</p>



<p><strong>Solution:</strong></p>



<ul><li><strong>Open-Door Policy: </strong>Encourage team members to approach leadership and colleagues freely. An open-door policy creates an atmosphere where questions, concerns, and ideas can be openly discussed<br></li><li><strong>Regular Team Meetings: </strong>Organize frequent team meetings where everyone can discuss progress, challenges, Regular communication strengthens teamwork and ensures alignment towards common objectives.<br></li></ul>



<h2 id="3-wrong-tool-selection"><span id="3_Wrong_Tool_Selection"><strong>3. Wrong Tool Selection:</strong></span></h2>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh5.googleusercontent.com/0qXeJ_vAsN9EDgEX1iTbrhy4rL-MmHX6_Jb0AAEZu2NByE8P88mMg5aGFHjbcTmSYRyMB9aT6BQT1wpnC55ctIrdDoCt341iohDseWVkA8NLTgLVFPsEdWbL9RUPEvak8dYROFsceaI25LXkvL5W1DA" alt="Wrong tool selection"/></figure></div>



<p>Choosing the right tools is akin to selecting the right tools for a job. Each tool has its purpose, and the wrong choice can lead to inefficiency. Thorough research on available tools and understanding the team&#8217;s proficiency in using them is crucial. An effective tool enhances productivity and streamlines the testing process.</p>



<p><strong>Solution:&nbsp;</strong></p>



<ul><li><strong>Tool Demonstrations:</strong> Organize tool demonstrations to provide hands-on experience to the team. Seeing the tools in action helps team members understand their functionalities and capabilities, aiding in informed decision-making.</li><li><strong>Training Sessions:</strong> Conduct training sessions tailored to the team’s needs. These sessions enhance the team&#8217;s proficiency, enabling them to effectively navigate and utilize the selected tool.</li><li><strong>Skill-Based Evaluation:</strong> Evaluate available tools based on the team&#8217;s skill set and expertise. Consider the team’s familiarity with similar tools and their capacity to adapt<br></li></ul>



<h2 id="4-lack-of-user-interaction"><span id="4_Lack_of_User_Interaction"><strong>4. Lack of User Interaction:</strong></span></h2>



<p>Users are the ultimate judges of software. Without their input, the software might not meet their needs. Regular interactions with users provide invaluable feedback. Understanding their perspectives, preferences, and pain points ensures the software aligns perfectly with user expectations.</p>



<p><strong>Solution:</strong></p>



<ul><li><strong>User Feedback Loops: </strong>Create structured channels for gathering user feedback regularly. Establish surveys, feedback forms, or direct communication methods to capture user opinions and preferences. Structured feedback loops ensure continuous user input.</li><li><strong><a href="https://testsigma.com/guides/usability-testing/" target="_blank" rel="noreferrer noopener">Usability Testing</a> Sessions: </strong>Organize dedicated usability testing sessions where real users interact with the software. Observe their behaviors, challenges, and preferences firsthand. Usability tests provide valuable insights into how users interact with the product</li><li><strong>Early User Involvement: </strong>Involve users right from the project&#8217;s early stages. Include them in design discussions, prototype reviews, and initial testing phases</li></ul>



<h2 id="5-not-asking-enough-questions"><span id="5_Not_Asking_Enough_Questions"><strong>5. Not Asking Enough Questions:</strong></span></h2>



<p>Questions are like keys that unlock understanding. If team members hesitate to ask questions, doubts persist. Encouraging a culture of inquiry not only reduces uncertainties but also nurtures a proactive approach. It promotes a sense of ownership and accountability among team members.</p>



<p><strong>Solution:&nbsp;</strong></p>



<ul><li><strong>Cultivating an Inclusive Environment</strong>: Create a safe space where team members feel comfortable asking questions without fear of judgment. Encourage open discussions and foster an atmosphere where curiosity is valued.</li><li><strong>Facilitating Brainstorming Sessions: </strong>Organize regular brainstorming sessions where team members can freely express their ideas and concerns.</li><li><strong>Emphasizing Clear Communication: </strong>Highlight the importance of clear and concise communication within the team. Clear communication channels eliminate misunderstandings and enable team members to express their thoughts openly,</li></ul>



<h2 id="6-not-having-a-motivated-workforce"><span id="6_Not_Having_a_Motivated_Workforce"><strong>6. Not Having a Motivated Workforce:</strong></span></h2>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh4.googleusercontent.com/9e9qf4twbLBlKElfU5Lzz0Nbjwrgo1nOxMstKClQHZAza5sAbVKcBGiv0LHlIpCDlMLj6QwYGpIjfsYnPMN9EK-CiaBsHo1Lch62zM4meDZYBQ_2AMycDtya2OxldRhYbwhCS4VwmsSzHT2w01L2gNA" alt="No motivated workforce"/></figure></div>



<p>Motivation is the engine that drives progress. A motivated team is more likely to tackle challenges and find innovative solutions. Recognition, encouragement, and a positive work environment contribute to team members&#8217; enthusiasm, ensuring they are invested in the project&#8217;s success.</p>



<p><strong>Solution:</strong></p>



<ul><li><strong>Recognition of Achievements: </strong>Acknowledging and appreciating team members&#8217; accomplishments boosts morale and fosters a positive work environment.</li><li><strong>Skill Development Opportunities: </strong>Providing avenues for skill enhancement through training programs and workshops equips team members with new knowledge and expertise. Continuous learning not only enhances individual capabilities but also contributes to the overall growth of the team,&nbsp;</li><li><strong>Supportive Work Atmosphere: </strong>Creating a workplace that values collaboration, respect, and encouragement establishes a supportive atmosphere. Team members thrive in such environments, feeling secure in expressing their ideas and concerns.</li></ul>



<h2 id="7-unrealistic-expectations"><span id="7_Unrealistic_Expectations"><strong>7. Unrealistic Expectations:</strong></span></h2>



<p>Realism is the foundation of achievable goals. Setting realistic expectations based on the project&#8217;s scope and resources is essential. Unrealistic expectations can lead to disappointment and frustration at a later point of time. Breaking down larger tasks into manageable steps ensures steady progress.</p>



<p><strong>Solution:</strong></p>



<ul><li><strong>Feasibility Studies</strong>: Conduct thorough feasibility studies to assess the project’s viability. Understand the technical, financial, and resource-related aspects</li><li><strong>Setting Milestones</strong>: Break down the project into smaller, manageable milestones. Setting specific, measurable goals provides a clear path forward.&nbsp;</li><li><strong>Stakeholder Involvement: </strong>Involve relevant stakeholders in the goal-setting process. Understand their perspectives, expectations, and concerns. Collaboration ensures that goals align with the project&#8217;s purpose, fostering collective commitment and realistic outcomes.<br><br></li></ul>



<h2 id="8-not-having-a-good-test-strategy"><span id="8_Not_having_a_good_test_strategy"><strong>8. Not having a good test strategy :</strong></span></h2>



<div class="wp-block-image"><figure class="aligncenter is-resized"><img loading="lazy" src="https://lh5.googleusercontent.com/eN2U3BHecaaF8TPEW7BVc1lPTwVJMsd5UOxDsuozENuwm7a99DcAn7C5joMAt3nkisr5ukoRG2Q6WdIx40ymIXsmqzhifgMlmynRxt_hkIp8Icwii7xaKohRmcLTd1eSTLDhOuTDuVLQx9_V9osv-sw" alt="Test Strategy" width="284" height="177"/></figure></div>



<p>The <a href="https://testsigma.com/blog/software-testing-strategy/" target="_blank" rel="noreferrer noopener">testing strategy</a> is like a roadmap for ensuring the software&#8217;s quality. It outlines how testing will be conducted, what areas will be covered, and the overall approach. When various challenges impact the testing strategy, it can throw the entire process off balance, affecting the project’s outcomes<br><br><strong>Solution:&nbsp;</strong></p>



<ul><li><strong>Agility in Testing Strategy: </strong>A flexible test strategy allows adjustments as the project progresses. Being adaptable ensures the approach aligns with evolving project needs, accommodating changes and improvements seamlessly.</li><li><strong>Precision in Goal Definition:</strong> A clear and concise test strategy defines precise objectives. Establishing specific goals guides the <a href="https://www.leewayhertz.com/software-testing-process/" target="_blank" rel="noreferrer noopener">testing process</a> effectively, ensuring that every effort is directed toward achieving these objectives.</li><li><strong>Proactive Risk Management:</strong> Addressing potential risks before testing begins is crucial. A robust test strategy identifies and plans for risks in advance, allowing the team to implement preventive measures and contingencies, ensuring a smoother testing process.</li></ul>



<p></p>



<blockquote class="wp-block-quote"><p><strong>&#8220;It’s fine to celebrate success, but it is more important to heed the lessons of failure.&#8221; &#8211; Bill Gates</strong></p></blockquote>



<p><br><p><button class="btn bg-primary cta-btn" style="margin: auto"><a href="https://testsigma.com/signup" target="_blank" rel="noopener noreferrer" style="color:#fff">Automate your tests for web, mobile, desktop and APIs, 10x faster, and for a better ROI with Testsigma</a></button>
</p><br></p>



<p>Testing might seem like a maze, but it&#8217;s also a chance to learn and innovate. By involving users early on, we ensure our software meets their expectations. Clear communication within the team and asking lots of questions help us uncover potential issues. Additionally, staying positive and encouraging each other creates a motivated environment. So, in the journey of testing, every challenge teaches us something new. Embracing these lessons, we move forward, turning obstacles into opportunities, and creating better software with each step.</p>



<p>Happy testing!</p>


Failed Testing Navigating Challenges and Achieving Success

Failed Testing: Navigating Challenges and Achieving Success

Context Driven Testing | What it is, How to Do, and Examples


<p>We are surrounded by software!&nbsp;</p>



<p>However, we rarely focus on the consequences that can happen if software fails. Today, we will dive deeper into the fascinating world of defects to understand how even the tiniest of glitches can have critical consequences. Most software anomalies might appear inconsequential at first, but we&#8217;ll understand that ripple effects can span across finances, reputation, employee morale, and beyond.&nbsp;</p>



<p>Get ready to explore the intricate layers of defect costs that lurk beneath the surface of the software world.</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#The_Social_Costs"><span class="toc_number toc_depth_1">1</span> The Social Costs</a></li><li><a href="#The_Financial_Costs"><span class="toc_number toc_depth_1">2</span> The Financial Costs</a></li><li><a href="#The_Technical_Costs"><span class="toc_number toc_depth_1">3</span> The Technical Costs</a></li><li><a href="#The_Testing_Costs"><span class="toc_number toc_depth_1">4</span> The Testing Costs</a></li><li><a href="#Operational_Costs"><span class="toc_number toc_depth_1">5</span> Operational Costs</a></li><li><a href="#Lost_Opportunities"><span class="toc_number toc_depth_1">6</span> Lost Opportunities</a></li><li><a href="#Customer_Acquisition_Costs"><span class="toc_number toc_depth_1">7</span> Customer Acquisition Costs</a></li><li><a href="#The_Complexity_of_Defect_Costs"><span class="toc_number toc_depth_1">8</span> The Complexity of Defect Costs</a></li></ul></div>
<h2 id="h-the-social-costs"><span id="The_Social_Costs"><strong>The Social Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh6.googleusercontent.com/zd9-O5kL_G__tWT41g5P7LwmsyzV78YqMnwBZyvkSx1FSBYKkWRF526rXRpmpYtgz4O8Oy9AihfmxNxFmQ_BdAJ5VX29ZCazQPO0IahTWhfEFWh1T5OU7rsaeBKmhdwqgVOnS_94fw4z5d7_1RuobA" alt="social costs"/></figure></div>



<p class="has-text-align-center"><em>Reputation Loss: A Cautionary Tale of Boeing 737 MAX Aircraft</em></p>



<p><p style="padding-top:30px">In 2018, Boeing, a towering giant in the aerospace industry, unveiled the Boeing 737 MAX aircraft. It was an exciting moment for aviation, but little did they know that a series of software-related defects would put their reputation at risk.</p></p>



<p>Two devastating crashes occurred:</p>



<ul><li>Lion Air Flight 610 in October 2018</li><li>Ethiopian Airlines Flight 302 in March 2019</li></ul>



<p>causing the deaths of 346 people. The heart-breaking incidents were traced back to a software glitch. A bitter revelation that shattered Boeing&#8217;s reputation in an industry where trust is paramount.</p>



<p><strong>Lesson</strong>: <em>The loss of lives was irreplaceable, and the damage to Boeing&#8217;s reputation was enormous. There are </em><strong><em>social consequences </em></strong><em>of software defects.</em></p>



<h2 id="the-financial-costs"><span id="The_Financial_Costs"><strong>The Financial Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh4.googleusercontent.com/HwPzy5XzYZubL3YyHV30UhyitO-3uTgRps3ZF8Vg7TwMJAIZlw2Os-x8kSO7NXYBEcKFwLU2Eao0IeyyYgmrfakqpPIxQlIgQE76kWWopdd2RK6kmyZR8G1VfXjotD4o1_AlcXPITZCjU2aeBaCqdw" alt="Financial costs"/></figure></div>



<p class="has-text-align-center"><em>Facebook NASDAQ Disaster</em></p>



<p><p style="padding-top:30px">Back in 2012, during the highly anticipated initial public offering (IPO) of Facebook. The event captured the world&#8217;s attention, but it swiftly devolved into a financial nightmare due to a software glitch.</p></p>



<p>Nasdaq&#8217;s trading platform encountered unforeseen hiccups, causing significant disruptions. Unable to confirm orders, traders were left in the dark, confusing the entire market. Investors and brokerages bore the brunt of this software hiccup, resulting in financial losses and severe damage to Nasdaq&#8217;s reputation.</p>



<p><strong>Lesson</strong>: <em>The Nasdaq Facebook IPO disaster serves as a reminder that software defects can manifest in the most unexpected places, triggering financial repercussions that extend far beyond the realm of technology.</em> <em>&nbsp;</em></p>



<h2 id="the-technical-costs"><span id="The_Technical_Costs"><strong>The Technical Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh5.googleusercontent.com/yqHIcK2Ok6FYUbDc9k0Z77t9uXSWRW0dy7y13OHBDZeGrpgtCsgJkeC1GRh2UVpAM_4sXoOSmFA3t8SJ2cZv4yFzjjZh-cvYmP6NWBxuuXM-UpttwMvyt-kvCWf58MRIgWR3tyk1T8V5Y0LS93k5Tg" alt="The technical costs"/></figure></div>



<p class="has-text-align-center"><em>A tale of technical burden: Microsoft&#8217;s October 2018 Update</em></p>



<p><p style="padding-top:30px">Microsoft&#8217;s Windows 10 October Update (Version 1809) was highly anticipated. As soon as it was released, reports flooded about users losing their documents, photos, and precious files during the update.&nbsp;</p></p>



<p>Due to the panic, Microsoft had to halt the rollout and investigate immediately.</p>



<p>Root Cause: An annoying software defect.</p>



<p><strong>Lesson</strong>: The incident highlights technical costs associated with a software defect. Microsoft&#8217;s response involved halting the rollout, investigating the issue, and releasing a fix. The technical and operational costs escalated due to hidden technical complexities.</p>



<h2 id="the-testing-costs"><span id="The_Testing_Costs"><strong>The Testing Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh4.googleusercontent.com/Cdo4TtVNeqVXBcPljpqKlguEzUvzSVDJXJ0hvAw-VPFvQUjWlyiNb17haWj7arfPYMgst40x47LE-SLpAgAl5ih1-qPaJ6frRwIlHaULBIJ--4UxPe2Jo835rgG286zJWrnL5HNOzPukLgfQTHGCBQ" alt="the testing costs"/></figure></div>



<p class="has-text-align-center"><em>Unexpected Costs of Testing, Documenting, &amp; Reproducing Issues: HealthCare.gov&#8217;s Ordeal</em></p>



<p><p style="padding-top:30px">One of the highly anticipated HealthCare.gov was launched in 2013. The website was designed to streamline the process of enrolling in health insurance plans under Obamacare. However, technical issues cast a long shadow and disappointment over this grand vision.</p></p>



<p>Slow-loading pages, frequent crashes, difficulty in creating an account, and verifying user information marred the initial rollout. To address these defects and ensure the website&#8217;s functionality, the U.S. government had to allocate additional budgets for extensive testing and debugging efforts.</p>



<p><strong>Lesson:</strong> <em>The HealthCare.gov debacle exemplifies the significant testing costs that can arise from software defects. The government had to invest substantial time and resources to rectify the situation, underscoring the importance of rigorous testing before launching any software product.</em></p>



<h2 id="operational-costs"><span id="Operational_Costs"><strong>Operational Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh3.googleusercontent.com/E026RVo9sR8CxueKirTqmSOgTTJIkYWio7nvOXDd9fqwacVjPi4hJMV9H-mkMsxVTP1XA4AgSdMppJYW6f9JcYYZpk5mXMGH0azdFhPoxI3-QaV_o6nP_0Yh5Zo_IXQoYM1lT6cBQ5v9I-1ywBS3-g" alt="operational cost"/></figure></div>



<p class="has-text-align-center"><em>The Toll of Additional Support: British Airways&#8217; Software Saga</em></p>



<p><p style="padding-top:30px">Remember your latest flight boarding experience?&nbsp;</p></p>



<p>When you were eagerly anticipating your upcoming journey. But British Airways (BA), in 2017, had a different narrative. Their check-in system malfunctioned due to a software defect, triggering a global IT outage and domino effect failures.</p>



<p>Due to this issue, multiple flights were canceled, baggage handling went haywire, and passengers encountered endless delays and frustration. To mitigate the operational fallout, British Airways had to deploy additional staff, compensate affected passengers, and invest heavily in rectifying the underlying software problem.</p>



<p><strong>Lesson:</strong> <em>This scenario highlights the operational costs caused due to a software defect. Beyond the technical and financial burdens, the need for additional support staff to handle customer complaints and implement workarounds can be a substantial drain on your existing operational system.</em></p>



<h2 id="lost-opportunities"><span id="Lost_Opportunities"><strong>Lost Opportunities</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh5.googleusercontent.com/p4pTPx9C_A4P13YvGCha751U-tqEgGePDZdCwrCCi0eXFX8sx4GN2xqVwgmyKdJk0DadarO0Dk3mVKk2Q_HS0MAndUM2LLZarf0365jp2-_BlJiKetXVTZwAsAwkzH4upxuH-FJSmQ_quWxM8aBy2w" alt="Apple iOS6 Maps Issue"/></figure></div>



<p class="has-text-align-center"><em>Apple iOS6 Maps Issue</em></p>



<p><p style="padding-top:30px">In 2012, Apple introduced its own mapping application as a replacement for Google Maps in iOS 6.&nbsp;</p></p>



<p>The bold move was blocked by a host of production defects. Users encountered inaccuracies, missing landmarks, and unreliable directions that led to a series of missed opportunities.</p>



<p>Apple had the potential to cross-sell other products and services, such as Siri and location-based app recommendations, to users who switched to alternative mapping apps like Google Maps. However, the poor user experience damaged Apple&#8217;s reputation and led to lost revenue from location-based services, app recommendations, and advertisements.</p>



<p>The Apple Maps fiasco demonstrates that software defects can incur immediate costs hindering the realization of potential revenue streams.&nbsp;</p>



<p><strong>Lesson: </strong><em>It serves as a reminder that user experience, quality, and trust are invaluable commodities that cannot be achieved without proper testing.</em></p>



<h2 id="customer-acquisition-costs"><span id="Customer_Acquisition_Costs"><strong>Customer Acquisition Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh4.googleusercontent.com/nCVm-HRvVtWO1wHOA1IFLOIMsaZTcfhD7JV2yWkCcec4JoGaEkW5pmjGYf9xOlnbwsQV7WlvfGYmWIpUgh_QzQzMUk2jSG7nlJv21jByrwIH5JtZ6Gp2DFoWxfXUm0qclJrtBpLImAPfNBz7n2pa1Q" alt="customer acquisition cost"/></figure></div>



<p class="has-text-align-center"><em>Equifax data breach, 2017</em></p>



<p><p style="padding-top:30px">Defects can increase customer acquisition costs.&nbsp;</p></p>



<p>As organizations scramble to build trust and attract new customers, replacing lost customers is proven to be more expensive than retaining existing ones.</p>



<p>One striking example is the Equifax Data Breach of 2017. The security breach exposed the personal information of 147 million US consumers, triggering a crisis. Equifax found itself in the unenviable position of having to work diligently to rebuild customer trust and reputation. It leads to the following:</p>



<ul><li><strong>Increased Customer Acquisition Efforts:</strong> Equifax had to invest significantly in rebuilding trust. This involved extensive marketing and communication efforts to address customer concerns and promote improved security measures.</li><li><strong>Impact on Attracting New Customers:</strong> The incident cast a long shadow over Equifax&#8217;s ability to attract new customers. Heightened regulatory scrutiny, which indirectly impacted customer acquisition costs, added to the financial burden.</li></ul>



<h2 id="the-complexity-of-defect-costs"><span id="The_Complexity_of_Defect_Costs"><strong>The Complexity of Defect Costs</strong></span></h2><br>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh5.googleusercontent.com/fD6xwABe--497XR2k-w6MeEvRhoSz_07UZnpRm6rIR7FQi4gCLyv9VOwKEtYSkashi9OQPhucPjlBqdlBN95zCnndAflEbJSiLC5xMpG7WibvvFnNZXXxJHFCo_n8g_C6SK_--iMRA-j-9xpMydE9A" alt="the complexity of defect costs"/></figure></div>



<p><p style="padding-bottom:30px">Throughout all these diverse examples, one thing is absolutely clear i.e., the cost of a software defect is a multifaceted and interconnected web of consequences. From the immediate financial hits to the long-term damage to reputation, from the toll on an organization’s morale to the need for extensive legal and public relations efforts, defects can wreak havoc in unpredictable ways.</p></p>



<p>The complexities of these costs serve as an important reminder of the critical importance of rigorous testing and quality processes in the software development process. Identifying and addressing defects early can save organizations from the maze of trouble and consequences.</p>



<p>Here are a few lessons to take from the case studies &amp; exploration of various costs associated with the defects:</p>



<ol><li><strong>Invest in Testing:</strong> Rigorous testing and quality practices are not optional—they are essential. The cost of fixing defects after they&#8217;ve reached production can be exponentially higher. Checkout our open source tool to accelerate your testing effort.</li></ol>



<br><button class="btn bg-primary cta-btn" style="margin: auto"><a href="https://testsigma.com/signup" target="_blank" rel="noopener noreferrer" style="color:#fff">Try Testsigma Opensource</a></button><br>



<ol start="2"><li><strong>Consider the Human Element:</strong> Software defects don&#8217;t just impact systems; they impact people. Customer’s morale, trust, and satisfaction are intangible yet invaluable assets. Do join our free discord community to stay up to date with fellow professionals and be on top of your quality and testing game.</li></ol>



<br><button class="btn bg-primary cta-btn" style="margin: auto"><a href="https://discord.com/invite/5caWS7R6QX" target="_blank" rel="noopener noreferrer" style="color:#fff">Join Testsigma Community</a></button><br>



<ol start="3"><li><strong>Trust is Priceless:</strong> Once trust is shattered, the cost of rebuilding it can be exorbitant. Trust is a currency that can&#8217;t be quantified but holds immeasurable value.</li><li>Prepare for the Unpredictable: Defects can manifest in unexpected ways and places. A proactive stance towards testing and quality is the best defense.</li></ol>



<blockquote class="wp-block-quote has-text-align-center"><p><em>“Quality is never an accident; <br>it is always the result of high intention, sincere effort, intelligent direction and skillful execution.”</em></p></blockquote>



<p class="has-text-align-center"><strong>John Ruskin</strong></p>



<p>Like a hidden iceberg lurking beneath the surface of the sea, with the potential to sink even the mightiest of ships, defects exist in the software world.</p>



<p>Understanding and mitigating these costs should be at the forefront of every organization&#8217;s software strategy. As we navigate the ever-evolving digital landscape, let&#8217;s do so with a keen awareness of the hidden consequences that lie beneath the surface.</p>


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Cost of a Defect: Unboxing the Hidden Consequences

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<p>When you are building a software application, there are several steps to successfully develop and deploy the application to be available to the users. In this process, there can be several errors we could encounter. To understand the different errors that can occur, we use fault-based testing.</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#What_is_Fault-Based_Testing"><span class="toc_number toc_depth_1">1</span> What is Fault-Based Testing?</a></li><li><a href="#A_Theory_of_Fault-Based_Testing"><span class="toc_number toc_depth_1">2</span> A Theory of Fault-Based Testing</a></li><li><a href="#Fault-Based_Testing_Techniques"><span class="toc_number toc_depth_1">3</span> Fault-Based Testing Techniques</a><ul><li><a href="#Mutation_Testing"><span class="toc_number toc_depth_2">3.1</span> Mutation Testing</a></li><li><a href="#Fuzz_Testing"><span class="toc_number toc_depth_2">3.2</span> Fuzz Testing</a></li><li><a href="#Boundary_Value_Analysis"><span class="toc_number toc_depth_2">3.3</span> Boundary Value Analysis</a></li><li><a href="#Error_Guessing"><span class="toc_number toc_depth_2">3.4</span> Error Guessing</a></li></ul></li><li><a href="#Fault-Based_Test_Suite_Prioritization_for_Specification-Based_Testing"><span class="toc_number toc_depth_1">4</span> Fault-Based Test Suite Prioritization for Specification-Based Testing</a></li><li><a href="#Assumptions_in_Fault-Based_Testing"><span class="toc_number toc_depth_1">5</span> Assumptions in Fault-Based Testing</a></li><li><a href="#What_are_the_Benefits_of_Fault-Based_Testing"><span class="toc_number toc_depth_1">6</span> What are the Benefits of Fault-Based Testing?</a></li><li><a href="#Conclusion"><span class="toc_number toc_depth_1">7</span> Conclusion</a></li><li><a href="#Frequently_Asked_Questions"><span class="toc_number toc_depth_1">8</span> Frequently Asked Questions</a><ul><li><a href="#Is_there_any_difference_between_fault-based_and_stress-based_testing"><span class="toc_number toc_depth_2">8.1</span> Is there any difference between fault-based and stress-based testing?</a></li><li><a href="#What_is_fault-based_testing_also_known_as"><span class="toc_number toc_depth_2">8.2</span> What is fault-based testing also known as?</a></li></ul></li></ul></div>
<h2 id="h-what-is-fault-based-testing"><span id="What_is_Fault-Based_Testing"><strong>What is Fault-Based Testing?</strong></span></h2>



<p>Fault-based testing is a software testing method that identifies faults, errors, and defects within a software system. It introduces various types of faults like syntax and semantic errors to assess the system&#8217;s ability to handle unexpected inputs effectively. By employing techniques like mutation testing and fuzz testing, it aims to uncover vulnerabilities and weaknesses that might lead to software failures.</p>



<p>Fault-based testing is crucial for enhancing software quality, improving robustness, and proactively addressing potential issues before they impact end-users. It is often integrated with other testing approaches to provide a comprehensive assessment of a software application&#8217;s reliability and resilience.</p>



<h2 id="h-a-theory-of-fault-based-testing"><span id="A_Theory_of_Fault-Based_Testing"><strong>A Theory of Fault-Based Testing</strong></span></h2>



<p>This theory is built on the principle that software is prone to faults and errors, and the systematic identification and evaluation of these faults can lead to the discovery of potential vulnerabilities and weaknesses. The theory posits that by intentionally introducing various types of faults, such as coding errors, logical mistakes, or boundary condition violations, testers can assess how a software system responds to these issues and determine the effectiveness of error-handling mechanisms. This approach helps improve software quality and reliability by proactively addressing defects before they can manifest in real-world scenarios.</p>



<p>These techniques are applied in a controlled manner to explore various fault scenarios, ensuring that the software is robust and resilient in the face of unexpected inputs and errors. Overall, a theory of fault-based testing provides a systematic framework for enhancing software quality and uncovering hidden issues, contributing to more reliable and resilient software systems.</p>



<h2 id="h-fault-based-testing-techniques"><span id="Fault-Based_Testing_Techniques"><strong>Fault-Based Testing Techniques</strong></span></h2>



<p>Fault-based testing techniques are critical methods used to introduce and evaluate faults, errors, and defects in software to ensure its robustness and reliability. Several key fault-based testing techniques are commonly employed:</p>



<h3 id="h-mutation-testing"><span id="Mutation_Testing">Mutation Testing</span></h3>



<p>Mutation testing involves the deliberate introduction of artificial faults (mutations) into the source code. These mutations represent common programming mistakes, such as changing an operator or variable. Test cases are then executed against the mutated code to assess whether they can detect and reveal the introduced faults. The effectiveness of the test suite is measured by its mutation score, indicating how many mutations were successfully detected.</p>



<h3 id="h-fuzz-testing"><span id="Fuzz_Testing"><a href="https://testsigma.com/blog/fuzz-testing/" target="_blank" rel="noreferrer noopener">Fuzz Testing</a></span></h3>



<p>Fuzz testing, or fuzzing, focuses on feeding the software with a variety of malformed, random, or unexpected inputs. This technique is particularly useful for uncovering vulnerabilities and security flaws in a system. Fuzzers automatically generate and send inputs to the software, monitoring its behavior for crashes or unexpected responses. By doing so, fuzz testing helps identify issues in input validation, boundary checking, and exception handling.</p>



<h3 id="h-boundary-value-analysis"><span id="Boundary_Value_Analysis">Boundary Value Analysis</span></h3>



<p>Boundary value analysis concentrates on testing at the extreme boundaries of input domains. Test cases are designed to assess how the software handles values near the edges of the valid input range. For example, if a software system accepts integers from 1 to 100, boundary value analysis would test values like 0, 1, 100, and 101 to uncover potential errors or misbehavior caused by boundary conditions. This technique is effective at exposing off-by-one errors and similar issues.</p>



<h3 id="h-error-guessing"><span id="Error_Guessing"><a href="https://testsigma.com/blog/error-guessing/" target="_blank" rel="noreferrer noopener">Error Guessing</a></span></h3>



<p>Error guessing is an informal testing technique that relies on testers&#8217; experience and intuition to identify potential fault scenarios. Testers use their knowledge of common programming mistakes, system vulnerabilities, or areas where errors are likely to occur. They then create test cases based on these insights, attempting to provoke errors based on their educated guesses. While less systematic than other fault-based testing techniques, error guessing can be a valuable addition to the testing process, leveraging the tester&#8217;s domain expertise.</p>



<p>These fault-based testing techniques play a crucial role in the software testing process, collectively contributing to the identification and resolution of defects and vulnerabilities that may compromise the reliability and performance of a software system. By intentionally introducing and assessing faults, software testers can enhance software quality and reduce the risk of unexpected failures in real-world scenarios.</p>



<h2 id="h-fault-based-test-suite-prioritization-for-specification-based-testing"><span id="Fault-Based_Test_Suite_Prioritization_for_Specification-Based_Testing"><strong>Fault-Based Test Suite Prioritization for <a href="https://testsigma.com/blog/specification-based-testing/" target="_blank" rel="noreferrer noopener">Specification-Based Testing</a></strong></span></h2>



<p>Fault-based test suite prioritization for specification-based testing is a strategy to determine the order in which test cases are executed based on their likelihood of uncovering defects in the software. The basic idea of this strategy is to identify and fix critical issues early in the testing process.&nbsp;</p>



<p>For example, imagine a software application for online shopping. A prioritization method could start by running test cases that involve fundamental functionalities like user login and product search. These are considered high-priority because issues in these areas could affect the entire application. As testing proceeds, lower-priority <a href="https://testsigma.com/guides/what-is-test-case/" target="_blank" rel="noreferrer noopener">test cases</a> for less critical features, such as user preferences or advanced filtering options, can be executed. By following this prioritization, if a major fault is detected early during testing, it can be addressed promptly, reducing the risk of high-impact issues in the final product. This approach optimizes testing efforts by focusing on areas that have the potential to cause significant problems.</p>



<h2 id="h-assumptions-in-fault-based-testing"><span id="Assumptions_in_Fault-Based_Testing"><strong>Assumptions in Fault-Based Testing</strong></span></h2>



<p>Fault-based testing relies on several key assumptions to effectively identify and address faults and defects in software. One such assumption is that the intentional introduction of faults will expose weaknesses in the software. Here are some assumptions of fault-based testing along with an example:</p>



<p><strong>Introducing Known Faults:</strong> One of the core assumptions in fault-based testing is that by deliberately injecting known faults into the software, you can assess how well it handles these issues. This assumes that the presence of these faults will lead to observable defects.</p>



<p>For instance, consider a web application, you intentionally introduce a fault by modifying the login process code to reject valid usernames and passwords. When you test the system with this fault, you expect it to fail to authenticate users and generate an error message.</p>



<p><strong>Defects Correspond to Faults:</strong> Fault-based testing assumes that the defects observed in the software are directly related to the introduced faults. This means that when you identify a problem, it can be traced back to a specific fault that was introduced during testing.</p>



<p>While performing mutation testing, you change a multiplication operator (*) to a division operator (/) in a critical calculation function. If the test cases that rely on this function produce incorrect results, you can trace the defect back to the introduced fault, which is the operator change.</p>



<p><strong>Test Cases Detect Introduced Faults:</strong> Fault-based testing assumes that the test cases are capable of detecting the introduced faults. Test cases are designed to expose the errors that are introduced into the software, ensuring they can effectively reveal these issues.</p>



<p>Let&#8217;s say you introduce a fault in a sorting algorithm that causes it to produce incorrect results when presented with a sorted input. Test cases are then executed to determine if the algorithm can identify and correct this error, showing that the test cases are capable of detecting the introduced fault.</p>



<p><strong>Detected Faults Represent All Faults</strong>: This assumption implies that the faults discovered during testing are representative of the entire spectrum of potential faults in the software. It assumes that if the introduced faults are detected, other similar faults in the code will also be uncovered.</p>



<p>During mutation testing, you introduce a set of specific faults into the code. If these introduced faults are detected and resolved, it&#8217;s assumed that similar types of faults within the codebase will also be addressed.</p>



<p>These assumptions underpin the effectiveness of fault-based testing in identifying and addressing issues in software. However, it&#8217;s important to recognize that fault-based testing may not uncover all types of faults or defects, as not all issues are related to the specific introduced faults. Nevertheless, this methodology remains a valuable tool in improving software quality and robustness.</p>



<h2 id="h-what-are-the-benefits-of-fault-based-testing"><span id="What_are_the_Benefits_of_Fault-Based_Testing"><strong>What are the Benefits of Fault-Based Testing?</strong></span></h2>



<p>Fault-based testing offers several benefits for software development and quality assurance processes. Here are some of the key advantages:</p>



<p><strong>Defect Detection</strong>: is effective in identifying defects and weaknesses within a software system. We do this by intentionally introducing faults and errors and this methodology can reveal issues that might remain hidden during regular testing.</p>



<p><strong>Improved Software Quality:</strong> Identifying and addressing defects early in the development process leads to improved software quality. By fixing issues proactively, the software becomes more reliable, robust, and resilient.</p>



<p><strong>Security Vulnerability Identification</strong>: Fault-based testing, particularly techniques like fuzz testing, can uncover security vulnerabilities, such as buffer overflows and injection attacks. By exposing these vulnerabilities, the software can be hardened against potential cyber threats.</p>



<p><strong>Cost Savings:</strong> Detecting and fixing defects early in the software development process is more cost-effective than addressing issues after the software is deployed. Fault-based testing can save organizations substantial time and resources in the long run.</p>



<p><strong><a href="https://testsigma.com/guides/quality-assurance/" target="_blank" rel="noreferrer noopener">Quality Assurance</a>: </strong>Integrating fault-based testing with other testing methodologies ensures comprehensive quality assurance. It complements techniques like unit testing, <a href="https://en.wikipedia.org/wiki/Integration_testing" target="_blank" rel="noreferrer noopener">integration testing</a>, and system testing to provide a well-rounded assessment of software reliability.</p>



<p><strong>Compliance and Regulation:</strong> In industries with stringent compliance and regulatory requirements, such as healthcare and finance, fault-based testing helps ensure that software meets these standards by identifying and addressing potential issues.</p>



<h2 id="h-conclusion"><span id="Conclusion"><strong>Conclusion</strong></span></h2>



<p>In conclusion, fault-based testing stands as an indispensable pillar of <a href="https://testsigma.com/guides/quality-assurance/" target="_blank" rel="noreferrer noopener">software quality assurance</a>, enabling developers and testers to unearth hidden defects, vulnerabilities, and weaknesses in software systems. By introducing known faults, this systematic methodology offers a unique perspective, shedding light on how a software application responds to errors and erroneous inputs. Through techniques like mutation testing, fuzz testing, boundary value analysis, and error guessing, fault-based testing provides a structured approach to enhance software quality and robustness. With its ability to mitigate risks, improve reliability, and reduce the likelihood of costly software failures, this testing approach not only safeguards an organization&#8217;s reputation but also leads to greater user satisfaction. As software development continues to advance, fault-based testing remains a cornerstone in the pursuit of more secure, reliable, and resilient software solutions.</p>



<p><br><p><button class="btn bg-primary cta-btn" style="margin: auto"><a href="https://testsigma.com/signup" target="_blank" rel="noopener noreferrer" style="color:#fff">Automate your tests for web, mobile, desktop and APIs, 10x faster, with Testsigma</a></button></p><br></p>



<h2 id="h-frequently-asked-questions"><span id="Frequently_Asked_Questions"><strong>Frequently Asked Questions</strong></span></h2>



<h3 id="h-is-there-any-difference-between-fault-based-and-stress-based-testing"><span id="Is_there_any_difference_between_fault-based_and_stress-based_testing">Is there any difference between fault-based and stress-based testing?</span></h3>



<p>While fault-based testing looks for errors and how the software handles them, stress-based testing checks how well the software can handle a big load. Both are important to make sure software works well, but they have different focuses.</p>



<h3 id="h-what-is-fault-based-testing-also-known-as"><span id="What_is_fault-based_testing_also_known_as">What is fault-based testing also known as?</span></h3>



<p>Fault-based testing is also known as error-based testing or failure-based testing. These terms are often used interchangeably to describe the testing methodology that focuses on identifying and evaluating faults, errors, and defects in a software system.</p>


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<p>In the Software Development Life Cycle, software testing is a crucial step. Software testing helps to have a stable production by detection of bugs in early stages, decreases security breaches, checks that the software is compliant and reduces customer complaints.&nbsp;</p>



<p>In this blog, let us understand about a type of software testing – Workflow Testing.</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#What_is_Workflow_Testing"><span class="toc_number toc_depth_1">1</span> What is Workflow Testing?</a></li><li><a href="#What_is_the_purpose_of_Workflow_Testing"><span class="toc_number toc_depth_1">2</span> What is the purpose of Workflow Testing?</a></li><li><a href="#What_is_the_importance_of_Workflow_Testing"><span class="toc_number toc_depth_1">3</span> What is the importance of Workflow Testing?</a></li><li><a href="#Who_performs_Workflow_Testing"><span class="toc_number toc_depth_1">4</span> Who performs Workflow Testing?</a></li><li><a href="#How_to_perform_Workflow_Testing"><span class="toc_number toc_depth_1">5</span> How to perform Workflow Testing?</a></li><li><a href="#What_are_the_features_of_Workflow_Testing"><span class="toc_number toc_depth_1">6</span> What are the features of Workflow Testing?</a></li><li><a href="#What_are_the_different_phases_of_Workflow_Testing"><span class="toc_number toc_depth_1">7</span> What are the different phases of Workflow Testing?</a></li><li><a href="#What_is_the_process_of_Workflow_Testing"><span class="toc_number toc_depth_1">8</span> What is the process of Workflow Testing?</a></li><li><a href="#What_is_the_strategy_for_Workflow_Testing"><span class="toc_number toc_depth_1">9</span> What is the strategy for Workflow Testing?</a></li><li><a href="#How_do_you_write_a_Workflow_Test_Case"><span class="toc_number toc_depth_1">10</span> How do you write a Workflow Test Case?</a></li><li><a href="#Conclusion"><span class="toc_number toc_depth_1">11</span> Conclusion</a></li><li><a href="#Frequently_Asked_Questions"><span class="toc_number toc_depth_1">12</span> Frequently Asked Questions</a><ul><li><a href="#What_is_QA_workflow"><span class="toc_number toc_depth_2">12.1</span> What is QA workflow?</a></li></ul></li></ul></div>
<h2 id="h-what-is-workflow-testing"><span id="What_is_Workflow_Testing"><strong>What is Workflow Testing?</strong></span></h2>



<p>Workflow testing is a process of testing the complete workflow of a functionality or an application against the given business requirement. Consider the functionality of buying a product in an ecommerce application. Workflow testing in this case involves adding a product to cart, selecting a payment method and making payment.</p>



<h2 id="what-is-the-purpose-of-workflow-testing"><span id="What_is_the_purpose_of_Workflow_Testing"><strong>What is the purpose of Workflow Testing?</strong></span></h2>



<p>The purpose of Workflow testing is to ensure that each functionality in a software or an application is working as per requirement. It is performed to make sure that the sequence of working for a software is correct. It also helps to analyse the interaction between functionalities. Workflow Testing also tests the behaviour of a software under different scenarios and use cases. Using this method of testing helps in identifying any deviations from defined business workflow.</p>



<h2 id="what-is-the-importance-of-workflow-testing"><span id="What_is_the_importance_of_Workflow_Testing"><strong>What is the importance of Workflow Testing?</strong></span></h2>



<p>It is evident that Workflow Testing is a major form of testing. In this section, let us understand the importance of Workflow Testing.</p>



<ol><li>Workflow Testing helps to verify working of each functionality and the interaction between these functionalities.</li><li>It provides user satisfaction. A well tested application or a software increases user confidence.</li><li>It performs end to end workflow testing from the initial step to the final outcome which makes the software more stable.</li><li>It can be performed with different use cases and scenarios and check the behaviour of software for each case.</li><li>With changing requirements, the software should also be changed. Workflow testing makes sure that these changes do not affect the functionalities and their interaction.</li></ol>



<h2 id="who-performs-workflow-testing"><span id="Who_performs_Workflow_Testing"><strong>Who performs Workflow Testing?</strong></span></h2>



<ol><li>Test Engineers – They are responsible to carry out the designing and execution of test cases. Test engineers write test cases for different scenarios and test the workflow.</li></ol>



<ol start="2"><li>Developers- They help the test engineers to understand the required outcome for a product, setting up the test environment and addressing the deviations or bugs raised when testing a product.</li></ol>



<ol start="3"><li>Integration engineers – They test the interaction between functionalities when integrating the complete software.</li></ol>



<h2 id="how-to-perform-workflow-testing"><span id="How_to_perform_Workflow_Testing"><strong>How to perform Workflow Testing?</strong></span></h2>



<p>Manual Workflow Testing &#8211; The test cases are designed, the test environment is set up, and test cases are written. The test cases are then executed and verified against the required workflow. If there are any defects, they are rectified. Once the <a href="https://en.wikipedia.org/wiki/Defect" target="_blank" rel="noreferrer noopener">defects </a>are fixed, the software is retested and deployed.</p>



<p>Automated Workflow Testing – The process of testing remains the same in automated workflow testing as well. But choosing automated testing helps in increasing the efficiency, repeatability and the consistency of test cases. It also allows parallel testing across various test environments which in turn saves time. <a href="https://testsigma.com/">Testsigma</a> is an automated tool that can be used.&nbsp;</p>



<p><br><p><button class="btn bg-primary cta-btn" style="margin: auto"><a href="https://testsigma.com/signup" target="_blank" rel="noopener noreferrer" style="color:#fff">Automate your workflow tests for web, mobile and desktop applications, 10x faster, with Testsigma</a></button></p><br></p>



<h2 id="what-are-the-features-of-workflow-testing"><span id="What_are_the_features_of_Workflow_Testing"><strong>What are the features of Workflow Testing?</strong></span></h2>



<p>Workflow Testing involves testing the sequence, interaction and the logic of functionalities or a software. In this section, let us see some of the features of Workflow Testing.</p>



<ol><li>This testing needs complete understanding of the business requirements and the software workflow.</li><li>Workflow testing is used to test each component or functionality of a software and hence makes sure that all these components are working as per requirement.</li><li>It performs integration testing and other types of testing as well.</li><li>It is a suitable testing process for workflow-based software or products.</li></ol>



<h2 id="what-are-the-different-phases-of-workflow-testing"><span id="What_are_the_different_phases_of_Workflow_Testing"><strong>What are the different phases of Workflow Testing?</strong></span></h2>



<p>There are a number of phases in workflow testing that help the test engineers to test a software. The result from these different phases of testing is a stable and reliable software. Let us discuss these phases here :&#8211;</p>



<ol><li>Inception phase &#8211; This is the initial phase where the test engineers plan the test designs, decide on the test scenarios, prepare the testing steps and the environment.</li></ol>



<ol start="2"><li>Elaboration Phase – This is the phase where test architecture baseline is designed.</li></ol>



<ol start="3"><li>Construction Phase – This is the phase where the actual testing is done. Each functionality is tested and also the integration between these functionalities is tested. This phase helps to find any bugs or any deviations from the business requirement.</li></ol>



<ol start="4"><li>Transition Phase – This is the final stage of Workflow testing. Regression testing is performed to confirm the functionalities even after making changes to some functionalities. Re-tests are carried out to make the end result stable.</li></ol>



<h2 id="what-is-the-process-of-workflow-testing"><span id="What_is_the_process_of_Workflow_Testing"><strong>What is the process of Workflow Testing?</strong></span></h2>



<p>If a software is tested in its earlier stages, bugs can be resolved sooner and the productivity can be increased. This can be achieved by following a sequence of steps. Let us discuss these steps in this section.</p>



<ol><li>Requirement analysis – This step is to gather all the required information. The business requirements and workflow are understood based on which the test strategies will be curated.</li></ol>



<ol start="2"><li>Write Test Cases – The testing team starts developing the test cases once the business workflow is understood. The test cases consist of different test case scenarios and decision tables.</li></ol>



<ol start="3"><li>Test Verification – This step is to verify the designed workflow with different users such as test managers, clients and the end users.</li></ol>



<ol start="4"><li>Test Execution – This is the most important step in the process. This is the phase where the workflow of a product or a software is tested. Different use cases and data inputs are given to analyse the end results.</li></ol>



<ol start="5"><li>Result Comparison – The obtained results from the previous step are compared with expected results. If there are deviations or bugs found, they are logged to be worked on.</li></ol>



<ol start="6"><li>Resolve the Issues and Deploy – Once the logged issues are all resolved, the working software is deployed in a live environment.</li></ol>



<h2 id="what-is-the-strategy-for-workflow-testing"><span id="What_is_the_strategy_for_Workflow_Testing"><strong>What is the strategy for Workflow Testing?</strong></span></h2>



<p>So far in this blog, we have understood the importance, features and the different phases. Let us now understand the strategies of Workflow testing.</p>



<ol><li>Workflow Analysis – This is where the business workflows are analysed and understood. Here, the test data and also the production data are analysed and evaluated. All the necessary planning is completed in this stage to avoid any discrepancies in later stages.</li></ol>



<ol start="2"><li>Workflow Designing – Once the workflow is understood, the team comes together to write test cases for different scenarios. The test cases are designed such that all the necessary outputs can be achieved. These test cases are compared and reviewed against the business workflow to make sure it meets with the requirement.</li></ol>



<ol start="3"><li>Workflow Execution and Monitoring – Here, the team executes all the test cases and verifies the output. If there are any defects, they are raised to be rectified. Once the defects are fixed, the test cases are executed again and then the software is deployed.</li></ol>



<h2 id="how-do-you-write-a-workflow-test-case"><span id="How_do_you_write_a_Workflow_Test_Case"><strong>How do you write a Workflow Test Case?</strong></span></h2>



<ol><li>Provide a title for the test case and define the purpose of the test case.</li><li>List out the prerequisites that need to be met before the execution of test cases.</li><li>Define the test data such as the input values and conditions.</li><li>Write the test case for different scenarios with both positive and negative input values.</li><li>Define the expected results for the test cases.</li><li>Mention if the test case has passed or failed with relevant justifications for both cases.</li><li>Maintain the version history that will be helpful with new changes and referencing.</li><li>Mention the test case author and the date on which the test case was written.</li></ol>



<h2 id="conclusion"><span id="Conclusion"><strong>Conclusion</strong></span></h2>



<p>Workflow testing makes sure that a software built is working as per the business requirement given. A well-defined and constructed workflow testing produces stable and usable software. A small section in this blog explains about <a href="https://testsigma.com/automated-testing" target="_blank" rel="noreferrer noopener">Automated testing</a>. </p>



<h2 id="h-frequently-asked-questions"><span id="Frequently_Asked_Questions"><strong>Frequently Asked Questions</strong></span></h2>



<h3 id="h-what-is-qa-workflow"><span id="What_is_QA_workflow">What is QA workflow?</span></h3>



<p>QA workflow is the process followed by the QA team for testing. It will include the phases of documentation, test case development, test automation as well as reporting, and any other steps that QA team deems necessary.</p>


Workflow Testing What It is, Process & How to Perform

Workflow Testing | What It is, Process & How to Perform?

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<p>Static analysis or static code analysis is used by developers and software testers to detect coding defects. Static analysis in software testing is not new, at least not for software testers with coding knowledge or experience. Static analysis involves reviewing the code similarly to performing a code or peer review.&nbsp;</p>



<p>Static analysis helps software testers fully understand how the code functions and its structure. Software testers can execute code in isolation and review for errors. Static analysis reviews by software testers also help ensure code meets organizational and industry standards.&nbsp;</p>



<p>This guide describes the types of static code analysis in software testing, how it’s performed, and its benefits for software testing coverage.&nbsp;</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#How_is_static_code_analysis_done"><span class="toc_number toc_depth_1">1</span> How is static code analysis done?</a></li><li><a href="#Types_of_static_analysis"><span class="toc_number toc_depth_1">2</span> Types of static analysis</a></li><li><a href="#Benefits_and_drawbacks_of_static_analysis"><span class="toc_number toc_depth_1">3</span> Benefits and drawbacks of static analysis</a></li><li><a href="#Static_verification_vs_dynamic_verification"><span class="toc_number toc_depth_1">4</span> Static verification vs. dynamic verification</a></li><li><a href="#Static_analysis_tools_and_vendors"><span class="toc_number toc_depth_1">5</span> Static analysis tools and vendors</a></li><li><a href="#Summary"><span class="toc_number toc_depth_1">6</span> Summary</a></li><li><a href="#Frequently_Asked_Questions"><span class="toc_number toc_depth_1">7</span> Frequently Asked Questions</a><ul><li><a href="#What_is_an_example_of_static_analysis"><span class="toc_number toc_depth_2">7.1</span> What is an example of static analysis?</a></li><li><a href="#Why_is_it_called_static_code_analysis"><span class="toc_number toc_depth_2">7.2</span> Why is it called static code analysis?</a></li></ul></li></ul></div>
<h2 id="h-how-is-static-code-analysis-done"><span id="How_is_static_code_analysis_done">How is static code analysis done?</span></h2>



<p>Static analysis like other <a href="https://testsigma.com/guides/software-testing/" target="_blank" rel="noreferrer noopener">software testing</a> can be done either manually or by using automation. Static analysis in software testing typically occurs early in the development process. Static code analysis can fulfill testing responsibilities when it’s not possible to test a feature fully in the application.&nbsp;</p>



<p>If static analysis is performed manually it is done either by using pair testing with a developer or by stepping through the code line by line in a formal setting similar to a code review. In either case, the software tester must follow along and ask any questions necessary to understand the functionality. It’s important to consider the individual code under review as well as its impact on the application functionality as a whole. The code is executed manually to verify no errors exist.&nbsp;</p>



<p>When static analysis is performed using automated tools, testers typically use a static code analyzer tool. Static code analyzer tools check the code against defined rules and any related standards. Most tools allow users to determine what standards are checked and to set custom guidelines as well. The code is executed by the tool, and any issues are flagged for review. </p>



<p>Check here &#8211; <a href="https://testsigma.com/blog/static-testing/" target="_blank" rel="noreferrer noopener">Static Testing</a></p>



<h2 id="h-types-of-static-analysis"><span id="Types_of_static_analysis">Types of static analysis</span></h2>



<p>Static analysis in software testing is not all the same. There are several different types of static analysis to fit various testing needs.&nbsp;</p>



<p>Typical static analysis methods include:</p>



<ul><li>Control&nbsp;<ul><li>Tests the <a href="https://en.wikipedia.org/wiki/Control_flow" target="_blank" rel="noreferrer noopener">control flow </a>in a calling structure.&nbsp;</li></ul></li><li>Data&nbsp;<ul><li>Verifies data properties and types.&nbsp;</li></ul></li><li>Error or Fault<ul><li>Verifies error processing and identifies failures in components.</li></ul></li><li>Interface&nbsp;<ul><li>Confirms interface compatibility often using mocked or faked dependencies.</li></ul></li></ul>



<h2 id="benefits-and-drawbacks-of-static-analysis"><span id="Benefits_and_drawbacks_of_static_analysis"><strong>Benefits and drawbacks of static analysis</strong></span></h2>



<p>Static code analysis in software testing provides benefits including:</p>



<ul><li>Improved code quality throughout the development cycle</li><li>Provides expanded test code coverage</li><li>Helps to find defects before the code is in production</li><li>Prevention of costly common issues</li><li>Reduces costs by finding issues before code is in test or production</li><li>Improves developer and QA collaboration</li></ul>



<h2 id="h-static-verification-vs-dynamic-verification"><span id="Static_verification_vs_dynamic_verification">Static verification vs. dynamic verification</span></h2>



<p>Static analysis verification testing differs from the more common dynamic verification testing. The differences are around the test objective and include:</p>



<figure class="wp-block-table"><table><tbody><tr><td><strong>Test Objective</strong></td><td><strong>Static Analysis Testing</strong></td><td><strong>Dynamic Testing</strong></td></tr><tr><td>Identifying defects early in the software development process</td><td>x</td><td></td></tr><tr><td>Code review, unit testing</td><td>x</td><td></td></tr><tr><td>Regression Testing</td><td></td><td>x</td></tr><tr><td>Integration Testing</td><td>x</td><td>x</td></tr><tr><td>End-to-End Testing</td><td></td><td>x</td></tr><tr><td>Full application test coverage</td><td></td><td>x</td></tr><tr><td>User Acceptance</td><td></td><td>x</td></tr></tbody></table></figure>



<h2 id="h-static-analysis-tools-and-vendors"><span id="Static_analysis_tools_and_vendors">Static analysis tools and vendors</span></h2>



<p>Numerous effective static analysis tools exist. Using an automated tool for static analysis saves significant time and can increase the number of early issues detected especially in coding standards.&nbsp;</p>



<p>The following is a partial list of tools, there are <a href="https://testsigma.com/blog/static-testing-and-dynamic-testing/">more</a> options:<gwmw style="display:none;"></p>



<ul><li>Embold<ul><li>Intelligent software analytics platform that can detect and prioritize code issues.</li><li>Includes visual indicators of issues.&nbsp;</li><li>Detects design patterns used within the code.&nbsp;</li></ul></li><li>Kiuwan<ul><li>Focuses on security testing supporting approximately 25 security standards.&nbsp;</li><li>Engineered for use by DevOps teams and is integrated with Jenkins.&nbsp;</li></ul></li><li>PyCharm<ul><li>Useful for code bases built in Python.&nbsp;</li><li>Includes enhanced code navigation for easier analysis.</li><li>Provides an automatic refactoring tool.</li></ul></li></ul>



<h2 id="h-summary"><span id="Summary">Summary</span></h2>



<p>Static code analysis in software testing provides testing coverage at the early stages of development as well as throughout the development cycle. Software testers benefit from learning the internal code structure and function which can help create functional and <a href="https://testsigma.com/regression-testing" target="_blank" rel="noreferrer noopener">regression tests</a> that execute defined code components in full.&nbsp;</p>



<p>For fuller and deeper test cover, consider including testing using static code analysis manually or by using an automated tool.&nbsp;</p>



<h2 id="h-frequently-asked-questions"><span id="Frequently_Asked_Questions">Frequently Asked Questions</span></h2>



<h3 id="h-what-is-an-example-of-static-analysis"><span id="What_is_an_example_of_static_analysis">What is an example of static analysis?</span></h3>



<p>In the example below, the OWASP Lapse+ tool provides a typical interface for viewing and analyzing code components:</p>



<div class="wp-block-image"><figure class="aligncenter"><img src="https://lh5.googleusercontent.com/VicZP7Cnl49PmTVe2GlJRn0shlA38Fnv5qTYhoBoIEW-WFG8oMWfmMrCKS2LNx9_XAH3_5ejPCt2J_JolxEgwOC6g04I8mb2UcAjXDNNaC7uU9YaU1F-yQQuzdVHRGhdaiZAIeSFCpgXaitDPHVoz2s" alt="What is an example of static analysis"/></figure></div>



<h3 id="why-is-it-called-static-code-analysis"><span id="Why_is_it_called_static_code_analysis"><strong>Why is it called static code analysis?</strong></span></h3>



<p>Because the testing is performed outside the application UI. Since the code is not being executed dynamically as required, it is static. Testers are reviewing and stepping through code components that are not active.</p>


Static Analysis in Software Testing


<p>When I talk about machine learning, what pops out of your brain? We are frequently asked about the distinction between training and testing data. So, we decided to explain it in detail through this blog. Understanding the disparity between these two data types and utilizing them appropriately is essential.</p>



<p>Knowing the difference between these two data types ensures that the machine-learning model is reliable, accurate, and effective.</p>



<p>Read more about AI and ML in software testing here: <a href="https://testsigma.com/blog/ai-and-ml-in-software-testing/" target="_blank" rel="noreferrer noopener">https://testsigma.com/blog/ai-and-ml-in-software-testing/</a></p>



<div class="wp-block-image"><figure class="aligncenter size-full is-resized"><img loading="lazy" src="https://testsigma.com/blog/wp-content/uploads/image-153.png" alt="difference between training data and testing data" class="wp-image-34918" width="641" height="368"/></figure></div>



<p>This blog post explores the primary purposes of training and testing data, the techniques used to prepare them, and the potential pitfalls that can arise when misusing them and about automation of the data.</p>



<div id="toc_container" class="no_bullets"><p class="toc_title">Table Of Contents</p><ul class="toc_list"><li><a href="#What_is_Training_Data"><span class="toc_number toc_depth_1">1</span> What is Training Data?</a></li><li><a href="#What_is_Testing_Data"><span class="toc_number toc_depth_1">2</span> What is Testing Data?</a></li><li><a href="#Why_do_we_need_training_and_testing_data"><span class="toc_number toc_depth_1">3</span> Why do we need training and testing data?</a></li><li><a href="#Why_Knowing_the_Difference_is_Important"><span class="toc_number toc_depth_1">4</span> Why Knowing the Difference is Important?</a></li><li><a href="#How_Training_and_Testing_Data_Work_with_Example"><span class="toc_number toc_depth_1">5</span> How Training and Testing Data Work with Example?</a></li><li><a href="#Training_Data_vs_Testing_Data"><span class="toc_number toc_depth_1">6</span> Training Data vs. Testing Data</a></li><li><a href="#How_are_Training_and_Testing_Data_used_in_Test_Automation_Tools"><span class="toc_number toc_depth_1">7</span> How are Training and Testing Data used in Test Automation Tools?</a></li><li><a href="#Conclusion"><span class="toc_number toc_depth_1">8</span> Conclusion</a></li><li><a href="#Frequently_Asked_Questions"><span class="toc_number toc_depth_1">9</span> Frequently Asked Questions</a><ul><li><a href="#How_can_you_improve_the_training_and_testing_data"><span class="toc_number toc_depth_2">9.1</span> How can you improve the training and testing data?</a></li><li><a href="#How_do_you_separate_training_and_test_data_sets"><span class="toc_number toc_depth_2">9.2</span> How do you separate training and test data sets?</a></li></ul></li></ul></div>
<h2 id="h-what-is-training-data"><span id="What_is_Training_Data">What is Training Data?</span></h2>



<p><strong><em>Do you know: The training data is always correct!</em></strong></p>



<p>Machine learning algorithms learn from data in datasets. They find patterns in the data, develop an understanding of the data, make decisions based on the data, and evaluate the accuracy of their choices.</p>



<p>In machine learning, datasets are typically split into two subsets: training and testing data. The training data is used to train the machine learning algorithm. The testing data is used to evaluate the accuracy of the trained algorithm. The training data should represent the data the algorithm will encounter in the real world.&nbsp;</p>



<h2 id="h-what-is-testing-data"><span id="What_is_Testing_Data">What is Testing Data?</span></h2>



<p><strong><em>Testing data is like a box of chocolates. You never know what you&#8217;re going to get.</em></strong></p>



<p>Once you have trained your machine learning model on a dataset, you must test it on unseen data to evaluate its performance. This unseen data is called the testing data. This is similar to the test data used in software testing, just the context is different here. In software testing, we use test data to ensure the software works well for given data. In machine learning, we use testing data to ensure the model works for the given testing data. The testing data should meet two criteria:</p>



<ol><li>It should represent the actual dataset that the model will be used on. This means that the testing data should have the same distribution of features as the actual dataset.</li><li>It should be large enough to generate meaningful predictions. This means the testing data should be large enough to provide a statistically significant test of the model&#8217;s performance.</li></ol>



<p>The testing data should be new, &#8220;unseen&#8221; data the model has not seen before. This is because the model will already have learned the patterns in the training data, so testing its ability to generalize to new data is essential.</p>



<p>The testing data can be used to evaluate the model&#8217;s accuracy, robustness, and fairness. It can also be used to identify areas where the model needs to be improved.</p>



<p>Splitting the data into 80% training data and 20% testing data is common in data science. This means that 80% of the data will be used to train the model, and 20% will be used to test the model.</p>



<h2 id="h-why-do-we-need-training-and-testing-data"><span id="Why_do_we_need_training_and_testing_data">Why do we need training and testing data?</span></h2>



<p>Here are some reasons why we need training and testing data in machine learning:</p>



<p><strong><em>&#8220;Training data teaches a machine learning model how to behave while testing data evaluates how well the model has learned.&#8221;</em></strong></p>



<p>1. <strong>Training data</strong> is used to teach the machine learning model how to make predictions or perform a desired task. It is typically labeled, which means that the model&#8217;s output is known for each data point. The model learns to identify the patterns in the data and make predictions based on those patterns. </p>



<p>Examples could be call recordings from <a href="https://www.nextiva.com/blog/call-center-software.html" target="_blank" rel="noreferrer noopener">call center software</a> to train virtual agents on identifying customer needs and sentiment, or chat scripts paired with customer data to train chatbots on addressing common questions and resolving basic issues.</p>



<p>Training data is like the textbook that a student uses to learn a new subject. The book contains the information the student needs to know, and the student learns by reading the text and doing the exercises.</p>



<p>2. <strong>Testing data</strong> is used to evaluate the machine learning model&#8217;s performance. It is typically different from the training data and not labeled. This means the model&#8217;s output is unknown for each data point. The model&#8217;s ability to make accurate predictions on the testing data is evaluated.</p>



<p>Testing data is like the test that a student takes to assess their knowledge of the subject. The test contains questions that the student needs to answer, and the student&#8217;s performance on the test is used to evaluate their understanding.</p>



<p>By using training and testing data, we can ensure that the model can make accurate predictions on new data it has not seen before.</p>



<h2 id="h-why-knowing-the-difference-is-important"><span id="Why_Knowing_the_Difference_is_Important">Why Knowing the Difference is Important?</span></h2>



<p><strong><em>The difference between training data and testing data is that training data tells you how to build a model, and testing data tells you how to break it.</em></strong></p>



<p>The difference between training data and testing data is important because it helps to prevent the model from overfitting. Overfitting occurs when the model learns the training data too well and is unable to generalize to new data. This can happen if the training data is too small or if it is not representative of the real world.</p>



<p>By using a separate testing data set, the model can be evaluated on data that it has not seen before. This helps to ensure that the model is able to generalize to new data and make accurate predictions.</p>



<h2 id="h-how-training-and-testing-data-work-with-example"><span id="How_Training_and_Testing_Data_Work_with_Example">How Training and Testing Data Work with Example?</span></h2>



<p>Here is an example of Training Data:</p>



<p>If you train a model to classify images of flowers and fruits, the training data would consists of image labeled as &#8220;flowers&#8221; or &#8220;fruits.&#8221; The  model would learn to identify the features distinguishing flowers from fruits by looking at the labeled data.</p>



<p>Good quality of the training data is essential for the machine learning model&#8217;s performance. If the data is not representative of the real world, the model cannot make accurate predictions. The data should also be large enough to allow the model to learn the patterns in the data. </p>



<p>Properly selecting and preparing training data is necessary for machine learning. This can enhance the performance of your models and ensure their readiness for real-world applications.</p>



<p><strong><em>Let us see an example for Testing Data:</em></strong></p>



<p>If you train a model to classify images of flowers and fruits, the testing data would consist of images the model has yet to see. The model would be evaluated on its ability to classify these images correctly.</p>



<p>The testing data quality is essential for the machine learning model&#8217;s performance, The data should represent the real world and be large enough to evaluate the model thoroughly.</p>



<p><strong><em>Lеt mе еxplain to you with another simplе еxamplе:&nbsp;</em></strong></p>



<p>Take testing data for a machine learning model that is used to predict the price of houses. The training data might consist of historical data on <a href="https://goldlineremovals.com.au/house-prices-and-moving-into-inner-west-suburbs/" target="_blank" rel="noreferrer noopener">house prices</a>, such as the house size, the number of bedrooms, and the house&#8217;s location.</p>



<p>The testing data would consist of new data on house prices that the model has not seen before. The model would be evaluated on its ability to predict the prices of these houses.</p>



<h2 id="h-training-data-vs-testing-data"><span id="Training_Data_vs_Testing_Data">Training Data vs. Testing Data</span></h2>



<figure class="wp-block-table"><table><tbody><tr><td>Feature&nbsp;</td><td>Training Data&nbsp;</td><td>Testing Data</td></tr><tr><td>Purpose</td><td>Training data is used to train the machine-learning model. The more training data the model has, the better it can make predictions.</td><td>Testing Data is used to evaluate the performance of the model.&nbsp;</td></tr><tr><td>Exposure&nbsp;</td><td>The model can learn from the training data and improve its predictions.</td><td>The testing data is not exposed to the model before evaluation. This ensures the model cannot memorize the testing data and make perfect predictions.</td></tr><tr><td>Distribution</td><td>The distribution of the training data should be similar to the distribution of the real-world data that the model will be used.&nbsp;</td><td>The distribution of the testing data is entirely different from the real-world data.</td></tr><tr><td>Use</td><td>Training data is used to prevent overfitting.&nbsp;</td><td>The testing data is used to evaluate the model&#8217;s performance by making predictions on it and comparing the predictions to the actual labels.</td></tr><tr><td>Size</td><td>The training data is typically larger. This is because the model needs to see many examples of input data to learn how to make accurate predictions.</td><td>The size of the testing data is typically smaller than the training data because the testing data is used to evaluate the performance of the model that has been trained on the training data.</td></tr></tbody></table></figure>



<h2 id="h-how-are-training-and-testing-data-used-in-test-automation-tools"><span id="How_are_Training_and_Testing_Data_used_in_Test_Automation_Tools">How are Training and Testing Data used in Test Automation Tools?</span></h2>



<p>No wonder Training and Testing data are used in <a href="https://testsigma.com/blog/automation-testing-tools/">Test automation tools</a>. This is to improve the accuracy and reliability of the tests.</p>



<p><strong><em>Training data</em></strong> is used to train the test automation tool on the specific application or system that is being tested. This helps the tool to learn the expected behavior of the application and to identity any potential defects.</p>



<p><strong><em>Testing data</em></strong> is used to evaluate the performance of the test automation tool. This helps to ensure that the tool is able to find defects and that it is not overfitting to the training data.</p>



<p>Here are some simple explanations of how training and testing data are used in test automation tools:</p>



<ul><li><strong>Training data</strong> teaches the test automation tool how to interact with the application or system under test. It should represent the real world and large enough to allow the tool to learn the patterns in the application&#8217;s behavior.</li><li><strong>Testing data</strong> is used to evaluate the performance of the test automation tool. It should be different from the training data and not labeled. This ensures that the tool is balanced with the training data and can find defects in new data.</li></ul>



<p>By using training and testing data, you can build test automation tools that are more accurate and reliable.</p>



<h2 id="h-conclusion"><span id="Conclusion">Conclusion</span></h2>



<p><strong><em>As Andrew Ng said, &#8220;The training data is the food for the model, and the testing data is the dessert.&#8221;</em></strong></p>



<p>Training data and Testing data are the most essential to understand to build accurate and reliable machine-learning models. By carefully selecting and preparing the data, you can improve your models&#8217; performance and ensure they are ready for real-world use.</p>



<h2 id="h-frequently-asked-questions"><span id="Frequently_Asked_Questions">Frequently Asked Questions</span></h2>



<h3 id="h-how-can-you-improve-the-training-and-testing-data"><span id="How_can_you_improve_the_training_and_testing_data">How can you improve the training and testing data?</span></h3>



<p id="h-improving-the-training-and-testing-data-can-be-done-by-increasing-the-diversity-of-the-data-sources-and-by-carefully-selecting-and-preprocessing-the-data-to-remove-any-biases-or-noise-also-incorporating-data-augmentation-techniques-can-help-generate-more-varied-and-representative-examples-for-training-and-testing">Improving the training and testing data can be done by increasing the diversity of the data sources and by carefully selecting and preprocessing the data to remove any biases or noise. Also, incorporating data augmentation techniques can help generate more varied and representative examples for training and testing.</p>



<h3 id="h-how-do-you-separate-training-and-test-data-sets"><span id="How_do_you_separate_training_and_test_data_sets">How do you separate training and test data sets?</span></h3>



<p>To separate training and <a href="https://en.wikipedia.org/wiki/Training,_validation,_and_test_data_sets" target="_blank" rel="noreferrer noopener">test data sets</a>, you can randomly split the data into two sets using a specific ratio, such as 70% for training and 30% for testing.</p>



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