Examples
Examples
Try the starting example
- Tests: ID, whole duration minutes, prerequisite IDs joined by | or none
- A,10,none B,6,A C,8,none D,4,B|C
- Parallel identical workers
- 2
- Feasible test schedule: worker and start-end minutes
- A: W1 0-10; C: W2 0-8; B: W1 10-16; D: W1 16-20
- Busy minutes by worker
- W1: 20; W2: 8
- Schedule makespan (minutes)
- 20
- Worker-time utilization (%)
- 70
- Total test execution minutes
- 28
Try another scenario
- Tests: ID, whole duration minutes, prerequisite IDs joined by | or none
- A,10,none B,6,A C,8,none D,4,B|C
- Parallel identical workers
- 1
- Feasible test schedule: worker and start-end minutes
- A: W1 0-10; C: W1 10-18; B: W1 18-24; D: W1 24-28
- Busy minutes by worker
- W1: 28
- Schedule makespan (minutes)
- 28
- Worker-time utilization (%)
- 100
- Total test execution minutes
- 28
Calculation method
Calculation method
Feasible test schedule: worker and start-end minutes
At each completion time assign longest ready tests first, input-order ties, to lowest-numbered free workers. Prerequisites must finish before launch.
Busy minutes by worker
Sum test durations assigned to each worker.
Schedule makespan (minutes)
Latest scheduled completion.
Worker-time utilization (%)
Total test duration/(workers×makespan)×100.
Total test execution minutes
Sum supplied test durations, independent of parallelism.
Symbols and units
- a
- Tests: ID, whole duration minutes, prerequisite IDs joined by | or none
- b
- Parallel identical workers
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- A deterministic feasible nonpreemptive DAG schedule, not a minimum-makespan optimizer or actual test runner. Durations and prerequisite links are supplied; setup costs and heterogeneous workers are excluded.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
NIST: combinatorial testing and coverage measurement; audit rules are explicitly supplied ↗
Background reading; this does not imply endorsement or independent review of SumFizz.