Performance Testing

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Performance Testing in SDLC

In this article, I am going to discuss Performance Testing in SDLC. Please read our previous article where we discussed System Testing. At the end of this article, you will understand the following important pointers which are related to Performance Testing in SDLC.

1. What is Performance Testing?
2. When is Performance Testing Employed?
3. What Metrics are Measured in Performance Testing?
4. What are Performance Testing Attributes?
5. What are the Objectives of Performance Testing?
6. Different Types of Performance Testing in SDLC
7. Process of Performance Testing in SDLC
8. Example of Performance Testing in SDLC
9. Performance Testing Tools
10. What are the Advantages of Performance Testing?
11. What are the Disadvantages of Performance Testing?

What is Performance Testing?

Software testing in the form of performance testing verifies that software programs function as intended under the anticipated demand. It’s a method for putting systems to the test to see how sensitive, responsive, and stable they are under a certain workload.

Performance testing is a subset of software testing that focuses on assessing a system’s or application’s scalability and performance. Performance testing seeks to locate bottlenecks, gauge system responsiveness under various loads and situations, and confirm that the system is capable of supporting the anticipated volume of users or transactions.

When is Performance Testing Employed?

Once the software is stable and placed into production, we will do performance testing. Since the software may be accessed by several users concurrently, some performance difficulties may arise. The tester runs one round of performance testing to prevent these performance problems. Performance testing is something we only conduct after the application is functionally stable, despite the fact that it is non-functional testing.

What Metrics are Measured in Performance Testing?

To comprehend the caliber and efficacy of performance testing, metrics are required. There can be no improvement without measurements. There are two definitions that require explanation:

1. Measurements: The information is gathered, such as the time it takes to answer a request in seconds.
2. Metrics: A computation used to define the quality of results using measures, such as the average response time (total response time/requests).

There are numerous ways to gauge speed, scalability, and stability, but it is unrealistic to anticipate that every method will be used in every performance test. The following metrics are frequently employed in performance testing:

• Reaction Time: Duration between sending a request and receiving a response.
• Hold Time: This tells programmers how long it takes for the first byte to arrive once a request has been sent. Additionally called average delay.
• Typical Load Time: From a user’s perspective, the average time it takes to deliver each request is a key sign of quality.
• Maximum Response Time: This is the lengthiest period of time needed to complete a request. A peak reaction time that is much longer than usual could be a hint of an anomaly that will cause issues.
• Mistake Rate: This computation compares the proportion of requests that encounter errors to all requests. When the load surpasses the capacity, these errors frequently happen.
• Multiple Users: The most popular way to gauge load is the number of concurrently active users. often referred to as load size.
• Query Rates Per Second: The volume of requests handled.
• Transactions Successful/Failure: A count of all requests that were either approved or denied.
• Throughput: Throughput Indicates how much bandwidth was consumed during the test and is measured in kilobytes per second.
• Use of the CPU: How long it takes the CPU to complete a request.
• Utilization of Memory: The amount of memory required to handle the request.

What are Performance Testing Attributes?

Some of the attributes are:

1. Speed: This factor impacts how quickly a software product reacts.
2. Scalability: It establishes how much load the software solution can support at once.
3. Stability: It assesses the software product’s stability under various workloads.
4. Reliability: It establishes whether or not a piece of software is secure.

What are the Objectives of Performance Testing?

The main objectives of performance testing include:

• Eliminating performance congestion is the goal of performance testing.
• Before the product is introduced to the market, it reveals what has to be improved.
• The goal of performance testing is to accelerate software.
• Performance testing aims to make software dependable and stable.
• Performance testing is to assess a system or application’s performance and scalability under varied loads and circumstances. Measuring system performance aids in the identification of bottlenecks and ensures that the system can support the anticipated volume of users or transactions. Additionally, it contributes to the system’s reliability, stability, and ability to manage the anticipated load in a production environment.

Explain Different Types of Performance Testing in SDLC

1. Load Testing: It evaluates a product’s performance under realistic user loads. Prior to the release of the software product on the market, the goal is to identify performance congestion.
2. Stress Testing: Stress testing entails putting a product under heavy workloads to determine whether it can withstand heavy traffic. Finding the software product’s breaking point is the goal.
3. Endurance Testing: Testing for endurance is done to make sure the software can withstand the anticipated load over an extended period of time.
4. Spike Testing: Testing for spikes examines how a product responds to unexpectedly high spikes in user-generated load.
5. Volume Testing: In volume testing, a lot of data is saved in a database, and the behavior of the entire software system is monitored. The goal is to evaluate the performance of the product with various database volumes.
6. Scalability Testing: In testing for scalability, the effectiveness of a software program is assessed when scaling up to accommodate an increase in user load. Planning for software system capacity increase is aided by it.

Explain the Process of Performance Testing in SDLC

The goal of the performance testing procedure is the same regardless of which organization uses the approach. The general seven-step procedure for conducting performance testing is given below:

• Identify the Testing Environment: All the magic takes place in the testing environment, or test best. Determine the testing environment and be aware of the testing tools at your disposal. Prior to use, become familiar with all the gear, software, and various network setups.
• Identifying The Performance Metrics: It’s necessary to determine the performance success criteria in addition to the generic performance measures like response time, throughput, and restrictions. There might not always be a sufficient range of performance benchmarks to choose from. To set performance targets, you can identify successful applications that are similar to these ones.
• Plan And Design Performance Tests: Consider a number of important eventualities while accounting for user variability, test data, and plan effectiveness. This is necessary to replicate different use cases and lay up the metrics that will be acquired.
• Configure the Test Environment: Set up all of the testing equipment and monitoring resources required to get the testing environment ready.
• Test Design Implementation: Test Design Implementation Design all of your performance tests in accordance with your performance metrics and criteria.
• Run the Tests: Execute and run the performance tests as step six. Additionally, record and keep track of all test data that is generated.
• Analyze, Tune, and Retest: Analyze the results of each performance test, thereafter, then fine-tune the test once again to determine whether performance has improved or declined. Rerun the tests using the same or alternative settings.

Example of Performance Testing in SDLC

Let’s use one instance where the target load is either fewer than 1000 users or equal to 1000 users to test the behavior of an application. It is evident in the figure below that the 100-up users are regularly added to test the maximum demand, a process known as upward scalability testing.

Scenario 1: When doing a load test, we will focus on the number of users, and the requirement calls for 1000 users, thus when we have 1000 users as the desired load and 2.7/sec as the goal time, these scenarios will pass.

Scenario 2: The goal time will increase to 3.5 seconds and the intended load will be increased by 100 users. If we stress test this scenario, it will pass because the real load is higher (1100) than the planned load (1000).

Scenario 3: In this case, increasing the desired load three times to

1200-> 3.5 sec will result in failure since it is not less than or equal to the required load.

1300-> 4 seconds [It is not less than or equal to the target load i.e. Fail].

1400 -> Crashed.

Explain Performance Testing Tools

Performance testing instruments are widely accessible on the market. Choosing a tool based on your needs is essential if you want performance testing to get the best results. The following is a list of the most popular testing tools:

1. LoadNinja: You can quickly and expertly create scriptless load tests with LoadNinja without compromising on quality. It is scriptless, and thus there is no need for translation or cleaning.
2. JMeter: JMeter is a cloud-based, open-source testing tool that enables you to assess and gauge the performance of web applications.
3. HP LoadRunner: HP LoadRunner, one of the most effective performance testing tools, can be used to examine how apps function in real time under extremely high loads.
4. WebLoad: WebLoad is a tool for measuring the load on mobile and desktop websites. To verify web and mobile applications, it incorporates all performance testing elements into a single process.

What are the Advantages of Performance Testing?

Performance testing has a number of benefits that might raise the caliber and dependability of software programs. Here are some main advantages:

1. Determines Bottlenecks: Performance testing identifies bottlenecks and performance constraints prior to deployment, allowing for timely optimizations.
2. Enhances Scalability: Performance testing guarantees the application can handle greater workloads by simulating diverse user loads and stress conditions. This encourages scalability and expansion.
3. Enhances User Experience: Performance testing, which measures response times and latency, ensures faster and more dependable software performance, enhancing user happiness.
4. Reduce Downtime Risks: Reduces the likelihood of unplanned failures and downtime in production environments: Testing under high loads and stress conditions reveals probable failure sites.
5. Optimizes how Resources are Used: Performance testing enables effective resource allocation, guaranteeing the best use of infrastructure and hardware and saving money.

What are the Disadvantages of Performance Testing?

Here are some main disadvantages:

1. Cost: Setting up and running performance tests requires specialized technology, pricey software, and qualified personnel.
2. Time-Consuming: Conducting numerous iterations and scenarios for performance testing to imitate real-world situations can take a lot of time and cause project timetable delays.
3. Complexity: Designing and putting into practice performance assessments can be challenging, particularly for big and intricate systems. It necessitates an understanding of workload patterns, performance indicators, and system design.
4. Limited Coverage: It is impossible to test every conceivable event and condition using performance testing. It might not catch every potential performance fault, allowing the possibility for the product of ion unanticipated complications.
5. Dependence on the Environment: The test environment, which may include network conditions, server settings, and user loads, might affect the findings of performance testing. The identical production environment may not always be possible to replicate.

In the next article, I am going to discuss Usability Testing in SDLC. Here, in this article, I try to explain Performance Testing in SDLC. I hope you enjoy this Performance Testing in SDLC article.