Build time
What is build time?
Build time refers to the average time it takes to execute all automated workflows required to compile and deploy software from the moment code is submitted for integration until it is ready for delivery or deployment. This includes the total time required to compile source code into binary code, run tests, and package the software for release. To calculate build time, one would typically measure the start time from the initiation of the build process to the end time when the build system successfully completes all tasks and the software is ready for deployment. The average build time can be derived by aggregating the total build times over a period and dividing by the number of builds conducted during that period.
Why is build time important?
Faster feedback cycles. Build time significantly impacts the feedback loop in software development. Shorter build times mean that developers receive quicker feedback on their code changes, facilitating rapid iterations and improvements. This responsiveness is critical in modern agile environments where speed and adaptability are key to meeting evolving user needs and market demands.
Efficiency and productivity. Efficient build processes directly contribute to higher productivity levels within development teams. Lengthy build times can lead to delays, increased context switching, and reduced focus, as developers wait for builds to complete before they can proceed with their tasks. Optimizing build time ensures that developers spend more time writing and improving code, rather than waiting.
Cost-effectiveness. Build time also affects the operational costs in software development environments, especially in cloud-based infrastructures where resources are metered. Longer build times consume more computational resources, thus increasing costs. By minimizing build time, organizations can reduce expenditure on infrastructure while speeding up the development process.
What are the limitations of build time?
Does not measure quality. While build time is a useful metric for understanding the efficiency of the build process, it does not provide insights into the quality of the output. A fast build might still result in software that is buggy or fails to meet user requirements. Therefore, build time should be used in conjunction with quality-focused metrics to ensure comprehensive evaluation.
Environment dependent. Build times can vary significantly depending on the environment in which the software is built. Differences in hardware, software, network configurations, and even the state of external dependencies can affect build time. This variability can make it difficult to compare build times across different environments or to establish consistent benchmarks.
Focus on speed could compromise thoroughness. Prioritizing shorter build times might lead developers to cut corners, such as reducing the number or depth of tests run during the build. This can lead to issues in the software being overlooked, which might cause more severe problems in the later stages of development or after deployment.
Metrics related to build time
Cycle time. Cycle time measures the total time from when work begins on a particular change until it is completed. It is closely related to build time because reducing the build time can directly contribute to a shorter cycle time. Improving cycle time is crucial for enhancing overall productivity and efficiency in software development processes.
Deployment frequency. Deployment frequency tracks how often an organization successfully releases to production. Build time impacts deployment frequency because shorter build times can allow for more frequent deployments. Higher deployment frequency is generally an indicator of a more agile and responsive development process.
Test pass rate. The test pass rate measures the percentage of tests that pass successfully as part of the build process. While it is a distinct metric, it is deeply interconnected with build time. Optimizing build time without compromising the test pass rate is crucial; otherwise, the reliability of the software could be at risk. This metric helps ensure that efforts to improve build times do not undermine the quality of the build outputs.
