Distinguishing Between Best Fit, Worst Fit, First Fit, and Last Fit
Published on: May 10, 2023
Last updated: December 16, 2025 Read in fullscreen view
Last updated: December 16, 2025 Read in fullscreen view
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The following article provides a concise, easy-to-understand explanation—along with a few everyday examples—to distinguish between Best Fit, Worst Fit, First Fit, and Last Fit, based on memory allocation strategies in operating systems and programming.
In both life and work, solution-oriented thinking is not just about finding an answer, but about choosing the most optimal approach (streamline or optimize). Much like parking in a large parking lot, you might choose a space that fits your car snugly to save space (Best Fit), or pick the largest spot simply for comfort (Worst Fit). Each choice reflects how you weigh efficiency against waste—and that is the essence of solution-oriented thinking: not just “solving a problem,” but “solving it intelligently.”
When “assigning space” also requires a smart strategy (solution-oriented thinking)
Imagine you are managing a parking lot or a warehouse, and every time a “customer” (a program) arrives, you must find a suitable space to accommodate it. There are multiple ways to choose a spot, and we call these allocation strategies.
First Fit – Park wherever it fits / Immediate match
- Definition: Select the first available free block that is large enough to hold the process.
- Pros: Fast, minimal searching required.
- Cons: May leave behind many small fragmented spaces (fragmentation).
- Everyday example: You enter a parking lot, see the first empty spot that fits your car, and park immediately without searching further.
Best Fit – Choose the tightest match / The most “perfect” fit
- Definition: Find the smallest free block that is still sufficient to hold the process.
- Pros: Maximizes space utilization and minimizes waste.
- Cons: Time-consuming to search; can create many tiny unusable fragments.
- Everyday example: When buying a storage box, you choose the one that fits the item most snugly to save warehouse space.
Worst Fit – Deliberately choose the largest space / Prioritizing time and speed
- Definition: Select the largest available free block to hold the process.
- Pros: Reduces the likelihood of creating tiny leftover fragments.
- Cons: Can waste a significant amount of memory space.
- Everyday example: You have the biggest suitcase, so you throw everything into it—even if the items are small.
Last Fit – Park at the end of the lot / Go where competition is lowest
- Definition: Select the last free block in the list that is large enough to hold the process.
- Pros: Simple and easy to implement.
- Cons: Not optimal in terms of speed or space utilization.
- Everyday example: At a supermarket, you deliberately park in the last available spot at the far end of the parking lot.
Conclusion
| Strategy | Principle | Advantages | Disadvantages |
|---|---|---|---|
| First Fit | Use the first suitable block | Fast | Small-scale fragmentation |
| Best Fit | Tightest fit | Space-efficient | Longer search time |
| Worst Fit | Largest available block | Reduces tiny fragments | Wastes space |
| Last Fit | Last block large enough | Easy to implement | Not optimal |
Tran Quang Huy
Automation Lead, TIGO CONSULTING
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