Best Spectrum code snippet using specs.ParameterizedExampleSpecs.compute
Source:ParameterizedExampleSpecs.java
...46 Variable<Number> result = new Variable<>();47 given("a calculator", () -> {48 calculator.set(new Calculator());49 });50 when("it computes the expression " + expression, () -> {51 result.set(calculator.get().compute(expression));52 });53 then("the result is " + expectedResult, () -> {54 assertThat(result.get(), is(expectedResult));55 });56 },57 withExamples(58 example("1 + 1", 2),59 example("5 * 9", 45),60 example("7 / 2", 3.5)));61 scenarioOutline("different types of parameters",62 (foo, bar, baz) -> {63 given("foo is " + foo, () -> {64 });65 and("bar is " + bar, () -> {66 });67 and("baz is " + baz, () -> {68 });69 when("something happens", () -> {70 });71 then("it works", () -> {72 });73 },74 withExamples(75 example(1, "boo", 3.14),76 example(1, "yay", 4.2))77 );78 scenarioOutline("with two parameters, just to see",79 (foo, bar) -> {80 given("blah " + foo, () -> {81 });82 when(bar + " - blerg", () -> {83 });84 then("something", () -> {85 });86 },87 withExamples(88 example("hey", 3.14),89 example("hi", 6.2),90 example("bye", -1.5))91 );92 }93 // dummy class under test94 static class CukeEater {95 private int amount;96 public CukeEater(int amount) {97 this.amount = amount;98 }99 public int remainingCucumbers() {100 return this.amount;101 }102 public void eatCucumbers(int number) {103 this.amount -= number;104 }105 }106 // another dummy class under test107 static class Calculator {108 private final ScriptEngine engine;109 public Calculator() {110 this.engine = new ScriptEngineManager().getEngineByName("nashorn");111 }112 public Number compute(String expression) throws Exception {113 return (Number) this.engine.eval(expression);114 }115 }116}...
compute
Using AI Code Generation
1import org.specs2.specification.dsl.mutable._2class ParameterizedExampleSpecs extends mutable.Specification {3 "This is a specification to check the 'compute' method" >> {4 "The 'compute' method should" >> {5 "return 0 if the argument is 0" >> {6 (n: Int) => compute(n) must_== 07 }8 "return 1 if the argument is 1" >> {9 (n: Int) => compute(n) must_== 110 }11 "return 2 if the argument is 2" >> {12 (n: Int) => compute(n) must_== 213 }14 }15 }16 def compute(n: Int) = n17}18import org.specs2.specification.dsl.mutable._19class ParameterizedExampleSpecs extends mutable.Specification {20 "This is a specification to check the 'compute' method" >> {21 "The 'compute' method should" >> {22 "return 0 if the argument is 0" >> {23 (n: Int) => compute(n) must_== 024 }25 "return 1 if the argument is 1" >> {26 (n: Int) => compute(n) must_== 127 }28 "return 2 if the argument is 2" >> {29 (n: Int) => compute(n) must_== 230 }31 }32 }33 def compute(n: Int) = n34}35import org.specs2.specification.dsl.mutable._36class ParameterizedExampleSpecs extends mutable.Specification {37 "This is a specification to check the 'compute' method" >> {38 "The 'compute' method should" >> {39 "return 0 if the argument is 0" >> {40 (n: Int) => compute(n) must_== 041 }42 "return 1 if the argument is 1" >> {43 (n: Int) => compute(n) must_== 144 }45 "return 2 if the argument is 2" >> {46 (n: Int) => compute(n) must_== 247 }48 }49 }
compute
Using AI Code Generation
1val examples = ParameterizedExampleSpecs.compute(2examples.foreach { case (method, op, tpe) =>3 s"$method with $op and $tpe" should {4 "work" in {5 }6 }7}
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