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  1. DZone
  2. Coding
  3. Java
  4. Your Codebase Is a Cluttered Garage

Your Codebase Is a Cluttered Garage

By consolidating this first-call information, teams can identify unused code and finally tidy up that ever-growing codebase.

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Erik Costlow user avatar
Erik Costlow
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Oct. 11, 23 · Analysis
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Unused code adds time and burden to maintaining the codebase, and removing it is the only cure for this side of “more cowbell.” Unfortunately, it’s not always obvious whether developers can remove certain code without breaking the application. As the codebase becomes cluttered and unwieldy, development teams can become mired in mystery code that slows development and lowers morale.

Do you remember the first time you walked into your garage, empty and sparkling, yawning with the promise of protecting your vehicles and power tools? How did it look the last time you walked in? If you’re like many of us, the clutter of long-closed boxes taunts you every time you walk around them, losing precious minutes before you can get to the objects you need while your car sits in the driveway. Sadly, development teams have a similar problem with their source code, which has grown into a cluttered mess.

Over the last few months, I’ve been working on a way to help development teams maintain less code. Everything we normally read is about working with new frameworks, new tools, and new techniques — but one thing many of us ignore is improving velocity by simply getting rid of things we no longer need. Essentially, as it runs, the JVM streams off its first-call method invocation log to a central location to track "have we used this method recently." When the method appears in the code inventory, the answer is yes — if the method does not appear, then it becomes a candidate for removal of that unused code.

Dead Code Removal

If you’re a senior developer helping new teammates, consider the work it takes to onboard new members and for them to learn your codebase. Each time they change something, they scroll past methods. Although our IDEs and analyzers can identify fully dead code, the frustration point is code that looks alive but just isn’t used. Often, these are public methods or classes that just aren’t called or have commented/modified annotations. As I’ve talked to teams about the idea that we hoard unused code, I’ve heard comments like these:

  • “I don’t know what this code does, so I don’t want to get rid of it, but I would love to.”
  • "I could clean that up, but I have other priority issues and don’t have time for that."
  • “We never prioritize clean up. We just do new features.”

What if Java developers had an easier way to identify dead code for removal — a way where we could prioritize code cleanup during our sprints to reduce technical debt without taking time away from business needs to add features?

Code removal is complex and generally takes a back seat to new features. Over time, code becomes unused as teams refactor without removal: commenting on an annotation, changing a path, or moving functionality. Most senior engineers would have to allocate time in their sprints to find what to remove: evaluating missing log statements or reviewing code with static analyzers. Both are problematic from a time perspective, so many teams just leave it in the code repository, active but dead: a problem for a future team lead or delayed until the next big rewrite. The JVM, however, has an overlooked capability to identify dead code and simplify the prioritization problem. By re-purposing the bytecode interpreter, the JVM can identify when a method is first called per execution. When tracked in a central location, these logs produce a treasure map you can follow to remove dead code. reducing the overall cognitive burden and improving team velocity. If a method hasn’t run in a year, you can probably remove it. Team leads can then take classes and methods that haven’t been executed and remove that code either at one time or throughout several sprints.

Why remove unused code at all? For many groups, updating libraries and major Java versions requires touching a lot of code. Between Java 8 and Java 17, the XML libraries were deprecated and removed — as you port your application, do you still use all that XML processing? Instead of touching the code and all associated unit tests, what if you could get rid of that code and remove the test? If the code doesn’t run, team members shouldn’t spend hours changing the code and updating tests to pass: removing the dead code is faster and reduces the mental complexity of figuring that code out. Similar situations arise from updates to major frameworks like Spring, iText, and so on.

Imagine you paid your neighbor’s kids to mow your lawn with your mower, and it was hidden behind a wall of boxes, expired batteries, old clothes, and old electronics. How hard do you think they would try to navigate around your junk before they gave up and went home? Senior engineers are doing the same thing. What should be an hour’s work of mowing becomes two hours.

The problem of cluttered and unused code also affects teams working on decomposing a monolith or re-architecting for the cloud. Without a full measurement of what code is still used, teams end up breaking out huge microservices that are difficult to manage because they include many unnecessary pieces brought out of the monolith. Instead of producing the desired streamlined suite of microservices, these re-architecture projects take longer, cost more, and feel like they need to be rewritten right away because the clutter the team was trying to avoid was never removed. Difficulties stick with the project until teams can decrease the maintenance burden: removing unnecessary code is a rapid way to decrease that burden. Instead of clamoring for a rewrite, reduce the maintenance burden to tidy up what you have.

The Benefits of Tracking Used/Unused Code

The distinguishing benefit of tracking life vs. unused code from the JVM is that teams can gather data from production applications without impacting performance. The JVM knows when a method is first called, and logging it doesn’t add any measurable overhead. This way, teams that aren’t sure about the robustness of their test environments can rely on the result. A similar experience exists for projects that have had different levels of test-driven development over their lifetime. Changing a tiny amount of code could result in several hours of test refactoring to make tests pass and get that green bar. I’ve seen many projects where the unit tests were the only thing that used the code. Removing the code and the unnecessary tests was more satisfying than updating all the code to the newer library just to get a green bar. 

The best way of identifying unused code for removal is to passively track what code runs. Instead of figuring it out manually or taking time from sprints, tune your JVM to record the first invocation of each method. It’s like a map of your unused boxes next to your automatic garage door opener. Later on, during sprints or standard work, run a script to compare your code against the list to see what classes and methods never ran. While the team works to build new features and handle normal development, start removing code that never ran. Perform your standard tests – if tests fail, look into removing or changing the test as well because it was just testing unused code.

By removing this unused code over time, teams will have less baggage, less clutter, and less mental complexity to sift through as they work on code. If you’ve been working on a project for a long time or just joined a team and your business is pressuring you to go faster, consider finally letting go of unnecessary code.

Track Code Within the JVM

The JVM provides plenty of capabilities that help development teams create fast-running applications. It already knows when a method will be first called, so unlike profilers, there’s no performance impact on tracking when this occurs. By consolidating this first-call information, teams can identify unused code and finally tidy up that ever-growing codebase.

Java virtual machine Dead code elimination Debug code Duplicate code

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