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How can you assess software performance in real-time systems?

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Software performance is a critical aspect of real-time systems, which are systems that have strict deadlines and constraints for delivering outputs and responding to inputs. Real-time systems can be found in domains such as aerospace, robotics, automotive, and industrial control. To ensure that the software in these systems meets the performance requirements and avoids errors, failures, or delays, you need to assess it using appropriate methods and tools. In this article, you will learn how to do that by following these steps:

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1 Define performance metrics

When measuring the performance of real-time systems, it is important to first define what metrics you want to measure and how. Performance metrics are quantitative indicators that reflect the quality, efficiency, and effectiveness of the software. Common performance metrics include throughput (the amount of work or data processed per unit of time), response time (the time elapsed between a request and a response), utilization (the percentage of system resources used by the software), reliability (the probability of the software functioning correctly without failures), and availability (the percentage of time that the software is operational and accessible). It is important to consider which metrics are relevant to your system's goals, specifications, and constraints, and also define acceptable ranges and thresholds for each metric.

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2 Design performance tests

The next step is to design performance tests that can simulate real-world scenarios and conditions the software will face. Performance tests are experiments that apply load, stress, or other inputs to the software and measure its outputs and behavior. For example, you could use a load test to apply a normal or expected level of load to the software and measure its throughput, response time, and utilization. A stress test applies an extreme or abnormal level of load to the software to measure its reliability, availability, and error handling. An endurance test applies a sustained or continuous level of load to the software and measures its performance over a long period of time. Additionally, a spike test applies a sudden or unexpected surge of load to the software and measures its performance under peak demand. You should design performance tests that cover the most critical and frequent use cases, scenarios, and events that the software will encounter, using realistic and representative data and parameters.

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Victor Melias Alberto Gois

Project Leader at Mercado Livre | Engineering Manager | Software Architect | CPA-20
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It's important to consider these tests when planning the development. You must evaluate your usecase and wonder what kinds of tests will be necessary. Sometimes (actually, almost always) you won't need them. But when you do, it must be planned ahead so you don't waste resources later on rebuilding your software.

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3 Implement performance tests

The third step is to implement performance tests using suitable tools and frameworks. Performance testing tools are software applications that generate, execute, and monitor performance tests, and provide reports and analysis of the results. For real-time systems, JMeter is an open-source tool that can create and run load, stress, endurance, and spike tests for various types of software such as web applications, databases, and messaging systems. LoadRunner is a commercial tool that can create and run load, stress, endurance, and spike tests for various types of software such as web applications, databases, and mobile applications. Additionally, RT-Tester is a commercial tool that can create and run performance tests for real-time systems such as embedded systems, control systems, and safety-critical systems. To ensure the best results from your performance tests, you should use tools that are compatible with your software's technology, platform, and architecture; as well as those that provide the features and functions you need.

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4 Run performance tests

The fourth step is to run performance tests in a controlled and isolated environment. This means mimicking the hardware, software, network, and other factors that affect the software's performance in the real world, as well as eliminating or minimizing interference and noise from other sources. To ensure real-time systems are tested accurately, some best practices include using dedicated and stable machines and devices, consistent and calibrated clocks and timers for measuring, wired and secure connections for communicating, separate and isolated networks for testing, and clean and fresh data and caches for testing. It's also important to run performance tests in a repeatable and reproducible manner while following the prepared test plan and schedule.

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5 Analyze performance test results

The final step is to analyze performance test results and compare them with the performance metrics and expectations. This requires examining the data and statistics collected by the performance testing tools, looking for patterns, trends, anomalies, and insights. You should also evaluate the software's performance against the performance requirements and criteria that you have defined, and identify any gaps, issues, or risks. To analyze and compare performance test results in a systematic and objective way, you can use graphs and charts to visualize the data, tables and matrices to summarize the metrics, dashboards and reports to present findings, benchmarks and baselines to compare with previous or expected performance, and root cause analysis to diagnose and resolve any problems. The evidence and data should be used to support your conclusions and actions.

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Scott R.

Chief Architect | Technology Strategist
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Assessing software performance in real time systems poses unique challenges, particularly in environments like high-performance systems using preemptive kernels. Such systems are generally engineered to maximize performance, making the assessment process intricate. Even standard tools designed for performance evaluation can introduce issues and potentially skew the results due to their own resource conception, priority, or lack of. Allocating ample system resources for testing without compromising real time responsiveness is crucial (give yourself a reserve). Understanding expected usage under different circumstances aids in establishing baseline performance and accurate deviation assessments. Also, consider developing integrated tools.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you assess software performance in real-time systems?

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6

1 Define performance metrics

2 Design performance tests

3 Implement performance tests

4 Run performance tests

5 Analyze performance test results

6 Here’s what else to consider

Systems Engineering

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How can you assess software performance in real-time systems?

1

2

3

4

5

6

1 Define performance metrics

2 Design performance tests

3 Implement performance tests

4 Run performance tests

5 Analyze performance test results

6 Here’s what else to consider

Systems Engineering

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