Code Impact

Understanding Impact

Impact is a way to measure the magnitude of code changes that are happening, in a way that goes beyond simplistic measurements like lines of code.

Impact attempts to answer the question: “Roughly how much cognitive load did the contributor/team carry when implementing these changes?”

Impact is a measure of work size that takes the following into account:

The amount of code in the change
What percentage of the work is edits to old code
The surface area of the change (think ‘number of edit locations’)
The number of files affected
The severity of changes when old code is modified
How this change compares to others from the project history

One contributor makes an addition of 100 new lines of code to a single file. Compare that to another contributor effort which touches three files at multiple insertion points where they add a total of 16 lines while removing 24 lines.

The significance of each contribution can’t be boiled down to just the amount of code being checked in. Even without knowing specifics, it’s likely that the second set of changes were more difficult to implement, given that they involved several spot-edits to old code.

On one hand, we have someone adding 100 lines of new code to a single file, while on the other hand, only 16 lines of new code are written, but there’s a bit more going on here:

this change required modifying previous work
the edits happened in 4 different locations
3 different files were affected

Even without knowing the severity of changes or comparing to historical changes, it’s probably safe to assume that the second contribution was more ‘expensive,’ and therefore carries a higher impact score.

Although the first set of changes is technically more code, the added complexity of the work from the second change could arguably make that change set at least as much work, and possibly more — even in the simplistic representation above, it’s clear that there’s more than just lines of code at play.

How to Use It?

Prioritize Code Changes: Uses the severity and scope of changes to determine priority in the development cycle, ensuring critical modifications are addressed promptly.
Enhance Code Quality Management: By analyzing the impact data, such as the number of files affected and locations edited, this metric helps refine quality assurance and testing strategies to maintain high standards.
Optimize Resource Allocation: Understanding the extent of changes to old code allows for more effective distribution of contributor efforts, focusing resources on areas requiring significant updates.
Guide Review Processes: Directs code review efforts by highlighting the areas with the most extensive or critical changes, ensuring thorough evaluations are conducted where needed most.

Strategic Implementation of Code Impact

Development Prioritization: Use impact metrics to sequence development tasks, focusing first on changes with the highest severity or largest scope.
Quality Assurance Protocols: Tailor testing protocols based on the breadth and depth of code changes identified, ensuring comprehensive coverage.
Resource Management: Adjust resource allocation dynamically based on ongoing assessments of Code Impact, maximizing development efficiency.

Considerations for Implementation

Balanced Metrics Approach: Combine Code Impact with other performance metrics to provide a holistic view of development efforts and outcomes.
Cultural Fit: Ensure the implementation of the Code Impact metric supports a culture of transparency and continuous improvement, avoiding any perceptions of micromanagement.
Feedback and Adaptation: Regularly refine the application of the Code Impact metric based on contributor feedback and evolving project demands to enhance its effectiveness and relevance.