Week 7 - Answers to the Weekly Exercises

Question 1 Answers:

Here's a breakdown of what might be most important in each scenario:

  1. End-of-day Processing in a Bank: In this case, the most important performance factor is likely throughput or processing speed. Ensuring that all transactions are processed by the end of the day and that cash reconciliation is completed promptly is crucial for financial accuracy and regulatory compliance. The system needs to handle a large volume of transactions efficiently to meet the end-of-day deadline.
  2. User Transactions in a Bank: For user transactions in a bank, the most important performance factor is likely response time or latency. Customers expect quick service, and completing transactions within 5 minutes is a reasonable expectation for most routine banking tasks. Therefore, minimizing the time it takes to process each transaction and provide feedback to the user is critical for customer satisfaction and operational efficiency.
  3. Remote File System Access: In this scenario, the most important performance factor is likely network latency. Since the processing is done at the remote file server, the time it takes for each character to be sent to the server and returned back depends heavily on the speed and reliability of the network connection. Minimizing latency ensures a smooth and responsive user experience, especially when interacting with remote systems where each keystroke incurs communication overhead.

Question 2 Answers:

For each of the given components (operating system, database, and network card), there are specific tuning parameters that can significantly affect performance. Let's explore them along with potential sources/documents where you can find information about these parameters: 

1.Operating System (e.g., Windows XP):
    Tuning Parameters:
        Virtual memory settings
        CPU scheduling algorithms
        Disk I/O settings
        Network settings (TCP/IP parameters)
        Power management settings
    Documents/Sources:
        Official documentation provided by the operating system vendor (e.g., Microsoft's TechNet library for Windows operating systems)
        Online forums and communities dedicated to system administration and optimization
        Books on operating system internals and performance tuning
        Whitepapers and technical articles published by the vendor or third-party experts
    
2.Database (e.g., Oracle):
    Tuning Parameters:
        Memory allocation (buffer cache, shared pool, etc.)
        Disk I/O settings (I/O distribution, block size, etc.)
        Query optimization parameters
        Parallel processing settings
        Locking and concurrency parameters
    Documents/Sources:
        Oracle documentation (official Oracle documentation portal)
        Oracle performance tuning guides and whitepapers
        Online forums and communities specializing in Oracle database administration and performance tuning
        Training materials and courses provided by Oracle and other educational platforms
    
3.Network Card (e.g., a Wireless LAN card):
    Tuning Parameters:
        Maximum transmission unit (MTU)
        Transmission power settings
        Signal strength thresholds
        Quality of Service (QoS) settings
        Power management settings
    Documents/Sources:
        Manufacturer's documentation and datasheets for the specific network card model
        Driver documentation provided by the operating system or the manufacturer
        Networking standards and protocols documentation (e.g., IEEE standards for wireless LAN)
        Online forums and communities focused on networking and wireless technologies

Question 3 Answers:

Collecting requirements for performance testing and functional testing (such as black box testing) involves similar principles of gathering information about the system under test, but there are distinct differences in the sources, methods, tools, and skill sets required for each type of testing: 

1.Sources Used:
    
    Performance Testing:
        Performance requirements might come from stakeholders, project managers, architects, or system designers.
        Historical performance data and benchmarks from similar systems or previous versions may inform performance testing requirements.
        Input from end users and business analysts regarding expected usage patterns and load scenarios can be valuable.
    
    Functional Testing:
        Functional requirements are typically specified in documentation such as business requirement documents (BRD), functional specification documents (FSD), use cases, user stories, and acceptance criteria.
        Stakeholder interviews and workshops may be conducted to clarify requirements and gather additional information.
        User feedback, bug reports, and customer support inquiries can also provide insights into functional requirements.
    
2.Methods Used:
    
    Performance Testing:
        Performance testing often involves analyzing non-functional requirements such as response time, throughput, scalability, and resource utilization.
        Performance test scenarios may be derived from use cases, user stories, or anticipated system usage patterns.
        Load modeling techniques are used to simulate realistic user behavior and system load.
    
    Functional Testing:
        Functional testing focuses on verifying that the system behaves according to specified functional requirements.
        Test cases are designed based on functional specifications and user requirements.
        Techniques such as equivalence partitioning, boundary value analysis, and state transition testing are used to create comprehensive test coverage.
    
3.Tools Used:
    
    Performance Testing:
        Performance testing tools such as JMeter, LoadRunner, Gatling, and Apache Bench are commonly used to simulate user load, measure response times, and analyze system performance under different conditions.
        Monitoring tools like New Relic, AppDynamics, and Prometheus may be used to gather real-time performance metrics from production environments.
    
    Functional Testing:
        Functional testing tools like Selenium, Appium, TestComplete, and Cucumber are used to automate test cases and perform regression testing.
        Test management tools such as HP ALM, Jira, and TestRail help organize test cases, track test execution, and manage defects.
    
4.Skill Sets Required:
    
    Performance Testing:
        Performance testers require expertise in performance testing methodologies, load modeling, test scripting, and performance monitoring.
        Knowledge of performance testing tools and technologies, as well as understanding of system architecture and performance bottlenecks, is essential.
    
    Functional Testing:
        Functional testers need strong analytical and problem-solving skills to understand requirements, design effective test cases, and identify defects.
        Proficiency in test automation frameworks, scripting languages, and testing methodologies is valuable for creating maintainable and scalable test suites.

Question 4 Answers:

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Question 5 Answers:

Here's a checklist of features and capabilities you might expect from a performance test automation tool: 

Protocol Support:
    Ability to test various protocols such as HTTP, HTTPS, SOAP, REST, JDBC, JMS, etc.
    
Load Generation:
    Capability to simulate thousands or more virtual users to generate realistic load on the system under test.
    
Scripting and Recording:
    Support for scripting performance test scenarios using a scripting language (e.g., JavaScript, Python) or recording user interactions.
    
Parameterization:
    Ability to parameterize test data to simulate different user inputs and scenarios.
    
Correlation:
    Capability to correlate dynamic values in responses to ensure accurate test execution.
    
Assertions:
    Support for adding assertions to validate response content, status codes, and performance thresholds.
    
Monitoring and Diagnostics:
    Built-in monitoring capabilities to track system resources, response times, throughput, and error rates during test execution.
    
Reporting and Analysis:
    Comprehensive reporting features to analyze test results, identify performance bottlenecks, and generate performance metrics.
    
Integration:
    Integration with CI/CD pipelines for automated test execution and result reporting.
    Integration with version control systems for managing test scripts and configurations.
    
Scalability:
    Ability to scale tests across distributed environments and cloud platforms to simulate real-world scenarios.
    
Customization:
    Flexibility to customize test scenarios, load profiles, and reporting formats according to project requirements.
    
Ease of Use:
    User-friendly interface and intuitive workflows for creating, executing, and analyzing performance tests.
Now, let's compare a few popular performance test automation tools based on the checklist: 
    
Apache JMeter:
    Protocol Support: HTTP, HTTPS, FTP, JDBC, LDAP, SOAP, JMS, etc.
    Load Generation: Supports simulating thousands of virtual users.
    Scripting and Recording: Provides scripting and recording capabilities.
    Parameterization: Supports parameterization through variables.
    Correlation: Offers built-in correlation options.
    Assertions: Includes various assertions for response validation.
    Monitoring and Diagnostics: Basic monitoring and reporting features available.
    Reporting and Analysis: Provides basic reporting capabilities.
    Integration: Integrates with CI/CD pipelines and version control systems.
    Scalability: Limited scalability compared to enterprise solutions.
    Customization: Offers extensive customization options.
    
Micro Focus LoadRunner:
    Provides support for various protocols and extensive load generation capabilities.
    Offers scripting, recording, and parameterization features.
    Includes advanced correlation and assertion capabilities.
    Offers comprehensive monitoring, diagnostics, and analysis features.
    Integrates with CI/CD pipelines and version control systems.
    Scalable for large-scale performance testing.
    Provides customizable reporting options.
    
Gatling:
    Protocol Support: Mainly focused on HTTP and HTTPS protocols.
    Load Generation: Efficient load generation capabilities.
    Scripting and Recording: Supports scripting using Scala DSL.
    Parameterization: Supports parameterization of test data.
    Correlation: Provides mechanisms for correlation.
    Assertions: Offers assertions for response validation.
    Monitoring and Diagnostics: Limited built-in monitoring features.
    Reporting and Analysis: Provides detailed HTML reports.
    Integration: Integrates with CI/CD pipelines.
    Scalability: Limited scalability compared to enterprise solutions.
    Customization: Offers customization through Scala scripting.

Question 6 Answers:

The statement "Staffing people for software performance testing is arguably the most difficult" holds merit due to several factors related to skill sets, attitude, and other parameters unique to performance testing: 

Specialized Skill Sets:
    Performance testing requires a unique set of skills beyond traditional software testing. Testers must understand performance testing methodologies, tools, and techniques for load generation, monitoring, and analysis.
    They need to be proficient in scripting or programming languages to develop complex test scenarios, automate test execution, and analyze performance metrics effectively.
    
Technical Proficiency:
    Performance testers need a deep understanding of systems architecture, networking principles, database technologies, and web protocols to effectively simulate real-world scenarios and identify performance bottlenecks.
    They should be familiar with various performance testing tools and have the ability to interpret performance metrics to pinpoint areas for optimization.
    
Analytical and Problem-Solving Skills:
    Performance testing often involves diagnosing complex performance issues under high load conditions. Testers must possess strong analytical skills to dissect system behavior, isolate performance bottlenecks, and propose effective solutions.
    They need to be adept at troubleshooting and problem-solving to address issues related to scalability, concurrency, resource contention, and system configurations.
    
Attention to Detail:
    Performance testing requires meticulous attention to detail to design realistic test scenarios, configure test environments accurately, and interpret performance metrics precisely.
    Testers must be vigilant in detecting anomalies, outliers, and unexpected behaviors that may impact system performance.
    
Collaborative Attitude:
    Effective performance testing often involves collaboration with various stakeholders including developers, system administrators, architects, and business analysts.
    Testers need strong communication and interpersonal skills to articulate performance concerns, facilitate discussions, and advocate for performance best practices throughout the software development lifecycle.
    
Continuous Learning and Adaptability:
    The field of performance testing is constantly evolving with advancements in technology, methodologies, and tools. Testers need to stay abreast of industry trends, emerging technologies, and best practices to remain effective in their roles.
    They should be open to learning new techniques, experimenting with different tools, and adapting to changing requirements and environments.
    
Resource Constraints and Complex Environments:
    Performance testing often involves testing complex distributed systems, cloud-based architectures, and hybrid environments with diverse configurations and dependencies.
    Testers may face challenges related to resource constraints, such as limited access to production-like environments, insufficient hardware resources, or restricted access to third-party systems and services.