1Model the domain

Users provide the meta-models that capture the domain concepts—for example, data centres and workloads in the cloud computing domain—together with a description of the domain execution environment. This environment includes the processor that runs the test cases, such as a simulator or an external API. Gotten uses this information to generate an MT environment tailored to the domain.

2Define metamorphic relations with mrDSL

The generated environment provides a DSL called mrDSL for defining and executing MRs. An mrDSL program declares the domain meta-models, model instance names, input features expressed through OCL, output features, processor attributes, and the metamorphic relations to be evaluated.

metamodel datacentre "/sample.gotten/model/datac.ecore" with m1, m2
models "/sample.gotten/model/dcmodels"
metamodel workload "/sample.gotten/model/workload.ecore" with w1, w2
models "/sample.gotten/model/workloads"

datacentre input Features {
    context DataCentre def: NNodes: Int = racks->collect(numBoards*board.nodesPerBoard)->sum()
    context DataCentre def: CPU: Int = racks->collect(
            numBoards*board.nodesPerBoard*board.nodeType.CPUCores*board.nodeType.CPUSpeed)->sum()
}
output Features {
    Time : Long
    Energy : Long
}
Processor {
    Name: String
    Version: String
}
MetamorphicRelations {
    MR1 = [(( NNodes(m1) > NNodes(m2) ) and ((w1) == (w2)) ) implies ((Time(m1) <= Time(m2)))]
    MR2 = [(( CPU(m1) > CPU(m2) ) and ((w1) == (w2)) ) implies ((Energy(m1) <= Energy(m2)))]
}

An mrDSL program for the cloud computing domain. MR1 states that, given the same workload, a data centre with more nodes should not take longer to process it; MR2 relates computing power and energy consumption.

3Execute the metamorphic testing process

A dedicated wizard guides users through the MT process. The environment executes the test cases on the domain processor, evaluates the defined MRs over the collected results, and produces a detailed report identifying any violated relations and the test cases involved.

4Generate follow-up test cases with fowDSL

Gotten provides a second DSL, fowDSL, for the automated generation of follow-up test cases. The generation method is based on MOMoT. For each MR, a fowDSL program specifies the permitted operations, such as increasing or decreasing numerical attributes or creating and deleting objects. It also defines operation limits, the optimisation objective, and the search algorithms to be applied.

followups for datacentre using MR1
with source folder = "/sample.gotten/model/dcmodels"
and output folder = "/sample.gotten/model/dcmodels"

NNodes ->  decrease [1..4] Rack.numBoards keeping {Rack.numBoards > 0};
           decrease [1..4] Board.nodesPerBoard keeping {Board.nodesPerBoard > 0}

maximize ( NNodes(m2) - NNodes(m1) )

maxSolutions 10
iterations 2
algorithms [Random, NSGAII, NSGAIII, eMOEA]

A fowDSL program deriving follow-up data centre models from the source test cases by reducing the number of boards and nodes, maximising the difference in nodes between the two models.

5Analyse the results

The environment collects and reports the test results. Users can inspect which MRs hold or fail for each pair of test cases and then refine the relations, models, or generation strategies.