fix quadratic random tests

contracts/RandomTest.sol

@@ -55,14 +55,17 @@ contract RandomTest {
    * @param n how many grade values to generate
    * @return an array of grade values of length n
    */
-  function randomGradeValues(uint32 n) public constant returns(uint24[]) {
+  function randomGradeValues(uint32 n, uint32 iterations) public constant returns(uint24[]) {
     // declare a container to store all the generated grades
     uint24[] memory result = new uint24[](n);
 
     // generate amount of random grade values requested
     for(uint32 i = 0; i < n; i++) {
-      // generate random using exactly the same logic as in Workshop.randomGradeValue
-      result[i] = uint24(Random.__quadraticRandom(i, 0, GRADE_VALUES));
+      // perform `iterations` number of iterations
+      for(uint32 j = 0; j < iterations; j++) {
+        // generate random using exactly the same logic as in Workshop.randomGradeValue,
+        result[i] = uint24(Random.__quadraticRandom(i, result[i], GRADE_VALUES - result[i]));
+      }
     }
 
     // return the result

test/gold_silver.js

@@ -172,7 +172,7 @@ contract('GoldERC20', (accounts) => {
 		assert.equal(amt, await tk.balanceOf(player2), "wrong player 2 balance after several transfers");
 	});
 
-	it("minting and burning: minting, burning, zer-value checks", async() => {
+	it("minting and burning: minting, burning, zero-value checks", async() => {
 		const tk = await Gold.new();
 
 		// token creator

test/workshop_rnd.js

@@ -37,7 +37,7 @@ contract('Workshop (RND)', (accounts) => {
 		// verify GRADE_VALUES constant is the same in both smart contracts
 		assert((await rndTest.GRADE_VALUES()).eq(await workshop.GRADE_VALUES()), "GRADE_VALUES mismatch");
 	});
-	it("random: verify properties required", async() => {
+	it("random: generate a set of iterations for grade values", async() => {
 		// construct random test helper smart contract
 		const rndTest = await RandomTest.new();
 
@@ -47,40 +47,51 @@ contract('Workshop (RND)', (accounts) => {
 		// maximum possible grade value
 		const maxGrade = (await rndTest.GRADE_VALUES()).toNumber();
 
-		// generate some amount of random grade values
-		const gradeValues = await rndTest.randomGradeValues(n);
+		// call a function to generate n iterations n = [1, 6]
+		for(let i = 0; i < 6; i++) {
+			await generateN(rndTest, n, i + 1, maxGrade);
+		}
+	});
+});
+
+async function generateN(rndTest, n, i, maxGrade) {
+	assert(i > 0, "incorrect n!");
+
+	// generate some amount of random grade values
+	const gradeValues = await rndTest.randomGradeValues(n, i);
 
-		// sort the array
-		gradeValues.sort((a, b) => a.minus(b).toNumber());
+	// sort the array
+	gradeValues.sort((a, b) => a.minus(b).toNumber());
 
-		// write statistical raw data into the file
-		fs.writeFileSync("./quadratic_random_" + TEST_DEPTH + ".csv", gradeValues.map((a) => a.toNumber()).join("\n"));
+	// write statistical raw data into the file
+	fs.writeFileSync("./quadratic_random_" + TEST_DEPTH + "_" + i + ".csv", gradeValues.map((a) => a.toNumber()).join("\n"));
 
-		// calculate the minimum
-		const min = gradeValues[0].toNumber();
+	// calculate the minimum
+	const min = gradeValues[0].toNumber();
 
-		// calculate the maximum
-		const max = gradeValues[gradeValues.length - 1].toNumber();
+	// calculate the maximum
+	const max = gradeValues[gradeValues.length - 1].toNumber();
 
-		// calculate an average
-		const avg = gradeValues.reduce((a, b) => a.plus(b), web3.toBigNumber(0)).dividedToIntegerBy(gradeValues.length).toNumber();
+	// calculate an average
+	const avg = gradeValues.reduce((a, b) => a.plus(b), web3.toBigNumber(0)).dividedToIntegerBy(gradeValues.length).toNumber();
 
-		// calculate the median
-		const median = gradeValues[Math.floor(gradeValues.length / 2)].toNumber();
+	// calculate the median
+	const median = gradeValues[Math.floor(gradeValues.length / 2)].toNumber();
 
-		// print the values into the console
-		console.log("\tmin: %o\n\tmax: %o\n\tavg: %o\n\tmed: %o", min, max, avg, median);
+	// print the values into the console
+	console.log("\t%o iteration(s)\n\t\tmin: %o\n\t\tmax: %o\n\t\tavg: %o\n\t\tmed: %o", i, min, max, avg, median);
 
+	if(i === 1) {
 		// verify the distribution properties are correct
 		assertEqualWith(0, min, 1000, "wrong minimum");
 		assertEqualWith(maxGrade, max, 100000, "wrong maximum");
 		assertEqualWith(maxGrade / 4, avg, 25000, "wrong average");
+	}
 
-		// verify random didn't exceed the bounds
-		assert(min >= 0, "minimum less than zero!");
-		assert(max < 1000000, "maximum exceeded 1000000!");
-	});
-});
+	// verify random didn't exceed the bounds
+	assert(min >= 0, "minimum less than zero!");
+	assert(max < maxGrade, "maximum exceeded GRADE_VALUES!");
+}
 
 
 // asserts equal with the precisions defined in leeway (absolute value)