Cycle Time in Software Development: Minimize Coding Time

Introduction

Understanding cycle time in software development is essential for software engineers, engineering managers, and development teams aiming to optimize their delivery process. This article covers the definition of cycle time, its importance for team efficiency, the main causes of high coding time, and actionable strategies to prevent delays. By mastering cycle time, teams can improve productivity, deliver projects faster, and make more accurate delivery forecasts.

What is Cycle Time in Software Development?

Cycle time in software development is the time from task start to completion, encompassing all phases including coding, review, testing, and deployment. It is a critical metric that directly measures internal delivery efficiency and provides insight into how long it takes to complete work once development begins. Unlike lead time, which includes waiting periods before development starts, cycle time focuses solely on the active phases of the development process.

• Cycle time: The time from when work begins on a task to when it is completed, covering coding, review, testing, and deployment phases.
• Lead time: The total time from a feature request or order to delivery, including waiting time before development starts.

Cycle time is a key indicator of team health and delivery effectiveness, helping teams identify bottlenecks and improve their workflow. Now that we've defined cycle time, let's look at why measuring it is crucial for engineering efficiency.

Why Measuring Cycle Time Improves Software Development Engineering Efficiency?

Measuring cycle time provides valuable insights into the efficiency of a software engineering team's development process. Below are some of the ways measuring cycle time can be used to improve engineering team efficiency:

Benefits of Measuring Cycle Time

• Measuring cycle time for an individual user story as it moves through each stage helps reveal bottlenecks in the development pipeline and shows where work gets delayed.
• Cycle time is one of the key metrics for software delivery because it directly measures internal delivery efficiency and serves as a predictor of overall engineering productivity.

Forecasting and Planning

• Understanding cycle time helps with realistic forecasting and planning in project management, since it is one of the key performance indicators used to estimate timelines and manage stakeholder expectations.

Continuous Improvement

• Measuring cycle time allows you to evaluate process changes by defining it consistently, using it for measuring success, and learning whether improvement efforts are working as you track cycle time trends over time.

Automated Metrics Collection

• Effective cycle time data for individual team members provides insights into their productivity and can be used for performance evaluations.
• Automated collection of cycle time metrics across engineering teams gives leaders actionable insights for process improvements and better visibility into delivery flow.

Better monitoring also supports faster delivery, improves customer satisfaction, and increases business value. With these benefits in mind, let's explore the detailed breakdown of cycle time and how it differs from lead time.

Cycle Time vs Lead Time

Cycle time covers the coding, review, testing, and deployment phases of software development, and is measured from the internal process perspective. This metric differs from lead time, which includes waiting time before development starts and is measured from the customer's perspective. Understanding the distinction between cycle time and lead time helps teams connect engineering efficiency to business outcomes.

• Cycle time: Measures the time from when work begins on a task to when it is completed (internal process).
• Lead time: Measures the time from a feature request or order to delivery, including waiting time before development starts (customer perspective).

Understanding this breakdown helps teams identify bottlenecks, diagnose causes of high coding time, and improve review, testing, and merge flow. Shorter cycle time leads to faster feedback, better forecasting, quicker project delivery, and stronger overall engineering productivity, especially when you deconstruct cycle time across each development phase.

Now that we've clarified the difference between cycle time and lead time, let's examine the specific stages within the cycle time metric.

Stages of Cycle Time

• Coding time: The time taken to write and complete the code changes.
• Pickup time: The time spent before a pull request is assigned for review.
• Review time: The time taken for peer review and feedback on the pull request.
• Testing time: The time spent validating the change before release.
• Merge time: The duration from the approval of the pull request to its integration into the main codebase.
• Production deployment time: The final step of getting the change into a live environment.

With a clear understanding of the stages involved in cycle time, let's focus on one of the most critical phases: coding time.

What is Coding Time? 

Coding time is the time it takes from the first commit to a branch to the eventual submission of a pull request. It is a crucial part of the development process where developers write and refine their code based on the project requirements. High coding time can extend the development cycle and slow software delivery. Managing the coding time efficiently is essential to ensure the code completion is done on time with quicker feedback loops and a frictionless development process.

To achieve continuous improvement, it is essential to divide the work into smaller, more manageable portions. Our research indicates that on average, teams require 3-4 days to complete a coding task, whereas high-performing teams can complete the same task within a single day. Smaller work items help speed up cycle time, improve productivity by reducing context switching, and support better team health with less burnout, especially when combined with broader developer productivity practices around focus, tooling, and collaboration.

In the Typo platform, if your coding time is high, your main dashboard will display the coding time as red.

Benchmarking coding time helps teams identify areas where developers may be spending excessive time, allowing for targeted improvements in development processes and workflows. It also enables better resource allocation and project planning, leading to increased productivity and efficiency.

Now that we've defined coding time, let's look at how to identify when it's becoming a bottleneck.

How to Identify High-Coding Time?

To identify high coding time, follow these steps:

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1. Check the “Insights” section at the team level and sort the teams by the cycle time.
2. Click on the team to deep dive into the cycle time breakdown of each team. This breakdown helps identify bottlenecks in specific stages such as coding, the code review process, testing, or deployment processes.
3. Look for long cycle times, which may point to delays in review or deployment, where minimizing PR review time in the cycle often has outsized impact.

Once you've identified high coding time, it's important to understand the root causes.

Causes of High Coding Time

There are broadly three main causes of high coding time, each connecting to broader strategies on how to reduce software cycle time end to end:

• The task is too large on its own
• Task requirements need clarification
• Too much work in progress

The Task is Too Large

Frequently, a lengthy coding time can suggest that oversized pull requests and large tasks are increasing development time and slowing the software development process. It would be advisable to investigate repositories that exhibit extended coding times for a considerable number of code changes, then break large work into smaller pull requests to measure cycle time more accurately and speed completion. In instances where the size of a PR is substantial, collaborating with your team to split assignments into smaller, more easily accomplishable tasks would be a wise course of action.

“Commit small, commit often”

Task Requirements Need Clarification

While working on an issue or feature request, you may encounter situations where seemingly straightforward tasks unexpectedly grow in scope. This may arise due to the discovery of edge cases, unclear instructions, or new tasks added after the assignment. In such cases, it is advisable to seek clarification from the product team, even if it may take longer. Doing so will ensure that the task is appropriately scoped, thereby helping you complete it more effectively.

Getting early feedback on a requirement can prevent rework and support maintaining quality.

There are occasions when a task can prove to be more challenging than initially expected. It could be due to a lack of complete comprehension of the problem, or it could be that several "unknown unknowns" emerged, causing the project to expand beyond its original scope. The unforeseen difficulties will inevitably increase the overall time required to complete the task.

Too Much Work in Progress

When a developer has too many tasks in flight, they are forced to frequently multitask and switch contexts, which also creates more idle time between contributions and increases their coding time metric.

Use the work log to understand the dev's commits over a timeline to different issues. If a developer makes sporadic contributions to various issues, it may be indicative of frequent context switching during a sprint. To mitigate this issue, it is advisable to balance and rebalance the assignment of issues evenly and encourage the team to avoid multitasking by focusing on one task at a time. This approach can help reduce coding time.

Reducing work in progress can lead to 20-30% faster average cycle time by lowering context switching, helping the software development team stay focused, and improving the entire process, and using PR cycle time as a primary metric makes those gains visible and actionable.

Understanding the causes of high coding time sets the stage for implementing effective prevention strategies.

Ways to Prevent High Coding Time

To prevent high coding time and optimize your development process, consider the following strategies:

Set up Slack Alerts

• Set goals for the work at risk where the rule of thumb is keeping the PR with less than 100 code changes & refactor size as above 50%.
• Use real-time Slack alerts to notify the team when large pull requests are published, helping improve the code review process and reduce PR cycle time before delays spread through the development pipeline.
• Identify and address issues, story-points, or branches that are too extensive in scope and require breaking down.

Balance Workload

• Regularly review the Insights tab so too many tasks do not pile up across engineering teams.
• Identify long PRs on a weekly or even daily basis.
• Examine each team member's workload to allocate resources more effectively and manage workloads more efficiently.
• Balancing workload is one of the key factors behind process improvements and more predictable cycle time metrics.

Use a Framework

• Using a framework, such as React or Angular, can help reduce coding time by providing pre-built components and libraries that can be easily integrated into the application.

Code Reuse

• Reusing code that has already been written can help reduce coding time by eliminating the need to write code from scratch.
• It also makes code review easier because smaller, clearer changes are faster to assess, and efficient reviews can reduce PR cycle time by 30-50%, while inefficient reviews can extend overall production cycle time.
• This can be achieved by using code libraries, modules, and templates.

Rapid Prototyping

• Rapid prototyping involves creating a quick and simple version of the application to test quick prototypes early for functionality and usability.
• This can help reduce coding time by allowing developers to quickly identify and address issues, and automated testing can cut testing cycle time by 40-60% while prompt feedback supports higher quality software.

Use Agile Methodologies

• Agile methodologies, such as Scrum and Kanban, emphasize continuous delivery and feedback.
• In agile software development this supports faster delivery through small, incremental improvements while giving teams better cycle-time data for realistic project management forecasts, which in turn strengthens the engineering metrics story presented in the boardroom.

Pair Programming

• Pair programming involves two developers working together on the same code at the same time.
• It is especially useful for complex tasks because it improves code quality earlier, which can reduce delays later in code review or deployment processes and shorten cycle time.

By implementing these strategies, teams can proactively prevent high coding time and maintain a healthy, efficient development workflow.

Summary: Cycle Time in Software Development

Cycle time in software development measures the time from task start to completion, including coding, review, testing, and deployment phases. It directly measures internal delivery efficiency, making it a key indicator of team health and delivery effectiveness. Understanding and tracking cycle time is essential for making realistic delivery forecasts and identifying bottlenecks in the development process. By breaking down work into smaller tasks, clarifying requirements, minimizing multitasking, and leveraging frameworks and agile methodologies, teams can improve their cycle time and overall productivity. Measuring and optimizing cycle time empowers software engineers, managers, and teams to deliver high-quality software faster and more predictably.