Benchmark: adejkas - MeasureThat.net

Tests:

test111
function traverse(tree,root){ if (!root) return "" let val = "(" + root if (!tree[root]) { val += ")" } else { let pair = tree[root] let left = pair[0] let right = pair[1] val += traverse(tree,left) val += traverse(tree,right) val += ")" } return val } function parseTree(edges){ const tree = {} for (let pair of edges){ if (!tree[pair[1]]) tree[pair[1]] = [] tree[pair[1]].push(pair[3]) } return tree } function isValidTree(tree, numOfEdges) { if (!tree || !Object.keys(tree)) return "E5" const root = Object.keys(tree).sort()[0] const queue = [root] const visited = new Set(root) while (queue.length) { const nodes = tree[queue.pop()] if (!nodes) continue if (visited.has(nodes[0]) || visited.has(nodes[1])) return "E3" if (nodes.length > 2) return "E1" if (nodes[0] == nodes[1]) return "E2" queue.push(...nodes) visited.add(nodes[0]) nodes[1] && visited.add(nodes[1]) } if (numOfEdges != visited.size - 1) return "E4" return "E0" } function binarySym(treeString="(B,D) (D,E) (A,B) (C,F) (E,G) (A,C)") { console.log("================") const edges = treeString.split(" ") let tree = parseTree(edges) const isValid = isValidTree(tree, edges.length) if (isValid != "E0") return isValid const rootNode = Object.keys(tree).sort()[0] let rv = traverse(tree,rootNode) return rv } binarySym()
test222
function traverse(tree,root){ if (!root) return "" let val = "(" + root if (!tree[root]) { val += ")" } else { let pair = tree[root] let left = pair[0] let right = pair[1] val += traverse(tree,left) val += traverse(tree,right) val += ")" } return val } function parseTree(edges){ const tree = {} for (let pair of edges){ if (!tree[pair[1]]) tree[pair[1]] = [] tree[pair[1]].push(pair[3]) } return tree } function isValidTree(tree, numOfEdges) { if (!tree || !Object.keys(tree)) return "E5" const root = Object.keys(tree).sort()[0] const queue = [root] const visited = new Set(root) while (queue.length) { const nodes = tree[queue.pop()] if (!nodes) continue if (visited.has(nodes[0]) || visited.has(nodes[1])) return "E3" if (nodes.length > 2) return "E1" if (nodes[0] == nodes[1]) return "E2" queue.push(...nodes) visited.add(nodes[0]) nodes[1] && visited.add(nodes[1]) } if (numOfEdges != visited.size - 1) return "E4" return "E0" } function binarySym(treeString="(B,D) (D,E) (A,B) (C,F) (E,G) (A,C)") { console.log("================") const edges = treeString.split(" ") let tree = parseTree(edges) const isValid = isValidTree(tree, edges.length) if (isValid != "E0") return isValid const rootNode = Object.keys(tree).sort()[0] let rv = traverse(tree,rootNode) return rv } binarySym()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test111
test222

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

I'll break down the benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

**Benchmark Definition**

The benchmark definition is provided in JSON format, which defines two test cases: `test111` and `test222`. Each test case has a unique `Name`, `Description`, `Script Preparation Code`, and `Html Preparation Code`.

However, there is no actual JavaScript code provided in the benchmark definition. The script preparation code and html preparation code fields are empty.

**Individual Test Cases**

Each test case has the following properties:

1. **Benchmark Definition**: A JavaScript function that contains two main functions: `traverse` and `parseTree`.
2. **Test Name**: Unique identifier for each test case (`test111` and `test222`).

The benchmark definition of each test case is the same, with only the variable names changed (e.g., `tree` becomes `tree1` and `tree2`).

**What is being tested?**

Based on the benchmark definition, it appears that the test cases are designed to measure the performance of a binary symmetry algorithm for a tree data structure.

Here's a high-level overview of what's happening:

* The `traverse` function traverses the tree in a depth-first manner and returns a string representation of the tree.
* The `parseTree` function constructs the tree from an array of edges.
* The `binarySym` function takes a string representation of the tree, parses it into a tree data structure, checks if the tree is valid (i.e., has the correct number of edges), and then traverses the tree to generate a binary symmetry string.

**Options compared**

It appears that there are two options being compared:

1. **`test111`**: This test case uses a specific implementation of the `binarySym` function, which may have some optimizations or differences in logic.
2. **`test222`**: This test case also uses a specific implementation of the `binarySym` function, but with some changes (e.g., different variable names).

The comparison between these two tests is likely to measure the performance difference between the two implementations.

**Pros and Cons**

Without seeing the actual code, it's difficult to provide detailed pros and cons for each implementation. However, here are some general observations:

* The `traverse` function may have some optimizations or differences in logic that affect its performance.
* The `parseTree` function may be more computationally expensive than the `traverse` function.
* The `binarySym` function is likely to be a bottleneck in the benchmark, as it involves traversing the tree and generating a binary symmetry string.

**Other Considerations**

Here are some other considerations that may impact the benchmark results:

* **Hardware and Software**: The benchmark results may vary depending on the hardware and software configuration (e.g., CPU, RAM, operating system).
* **Browser Differences**: The benchmark uses Chrome 90 as the browser. Other browsers may have different performance characteristics or optimizations.
* **Tree Size**: The size of the tree being traversed and parsed may affect the performance results.

In summary, the benchmark is testing the performance of a binary symmetry algorithm for a tree data structure, comparing two implementations (`test111` and `test222`). Without seeing the actual code, it's difficult to provide detailed pros and cons or other considerations.

Related benchmarks:

adejkas (version: 0)

Comparing performance of: test111 vs test222

Created: 5 years ago by: Guest

Jump to the latest result

test111

test222

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):