https://github.com/walkframe/covertable
makes combinations for testing.
https://github.com/walkframe/covertable
allpairs covering-array javascript javascript-library pairwise pairwise-testing python testing typescript
Last synced: about 1 year ago
JSON representation
makes combinations for testing.
- Host: GitHub
- URL: https://github.com/walkframe/covertable
- Owner: walkframe
- License: apache-2.0
- Created: 2019-06-16T10:13:51.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-08-31T20:20:35.000Z (over 1 year ago)
- Last Synced: 2025-02-26T18:13:24.706Z (about 1 year ago)
- Topics: allpairs, covering-array, javascript, javascript-library, pairwise, pairwise-testing, python, testing, typescript
- Language: TypeScript
- Homepage:
- Size: 2.29 MB
- Stars: 46
- Watchers: 2
- Forks: 5
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# CoverTable
Time is limited.
Creating a test case that satisfies all possible factors is often unrealistic and, more importantly, tedious.
Save time with CoverTable, a flexible pairwise tool that generates combinations covering two (or more) factors.
## Implementations
CoverTable is available in two implementations, with TypeScript as the primary focus and Python offered as a secondary option.
### TypeScript
[](https://badge.fury.io/js/covertable) [](https://github.com/walkframe/covertable/actions/workflows/typescript.yaml)
- [README](https://github.com/walkframe/covertable/blob/master/typescript/README.md)
- [History](https://github.com/walkframe/covertable/blob/master/typescript/history.md)
### Python (Legacy Support)
[](https://badge.fury.io/py/covertable) [](https://github.com/walkframe/covertable/actions/workflows/python.yaml)
- [README](https://github.com/walkframe/covertable/blob/master/python/README.rst)
- [History](https://github.com/walkframe/covertable/blob/master/python/history.md)
For more details, please refer to the links above.
## Performance
> **Note:**
> The following data was measured in Python 3.7.7 on a `3.1 GHz 6-Core Intel Core i5`.
> The coverage number is `2`.
| Combination | Default | Minimum case | Fastest case |
|-------------------|-------------------------------------|---------------------------------------|------------------------------------|
| **3^4** | num: `9`
time: `0.0006s` | num: `9`
time: `0.0006s` | num: `14`
time: `0.0005s` |
| **3^13** | num: `19`
time: `0.03s` | num: `17`
time: `0.03s` | num: `21`
time: `0.003s` |
| **4^15 + 3^17 + 2^29** | num: `36`
time: `7.41s` | num: `34`
time: `7.47s` | num: `42`
time: `0.40s` |
| **4^1 + 3^39 + 2^35** | num: `27`
time: `15.19s` | num: `26`
time: `14.70s` | num: `30`
time: `0.51s` |
| **2^100** | num: `14`
time: `23.97s` | num: `12`
time: `0.63s` | num: `13`
time: `0.48s` |
| **10^20** | num: `198`
time: `14.28s` | num: `195`
time: `14.48s` | num: `284`
time: `0.53s` |
In general, as the number of elements or coverage increases, the number of combinations tends to increase significantly.
## Tolerance
If you use the `greedy` criterion and specify a positive integer for the `tolerance` option, you can increase speed at the expense of the number of combinations.
The greater the `tolerance`, the faster the speed and the larger the number of combinations.
### Example: 10^20 Test Cases
| Tolerance | num | time |
|-----------|------|--------|
| 0 (default) | `195` | `14.48s` |
| 1 | `199` | `12.45s` |
| 2 | `201` | `9.48s` |
| 3 | `201` | `7.17s` |
| 4 | `207` | `5.70s` |
| 5 | `212` | `4.58s` |
| 6 | `212` | `3.65s` |
| 7 | `216` | `3.07s` |
| 8 | `223` | `2.57s` |
| 9 | `226` | `2.14s` |
| 10 | `233` | `1.84s` |
| 11 | `237` | `1.61s` |
| 12 | `243` | `1.43s` |
| 13 | `249` | `1.28s` |
| 14 | `254` | `1.19s` |