fix: use numeric types in scoring data object

Signed-off-by: Dustin Popp <[email protected]>

packages/validator/src/schemas/results-object.yaml

@@ -160,14 +160,12 @@ $defs:
       percentage:
         type: integer
         description: The percentage of total violations for a given severity that this rule comprises
-
-  # TODO: refactor the logic to use numbers for these.
   MaxScore:
-    type: string
+    type: integer
     description: A number describing the maximum quality score for an API after accounting for rule violations
-    # minimum: 0
-    # maximum: 100
+    minimum: 0
+    maximum: 100
   Demerit:
-    type: string
+    type: number
     description: A number describing the demerit impact a rule has on an API
-    # minimum: 0.01
+    minimum: 0.01

packages/validator/src/scoring-tool/score.js

@@ -43,13 +43,14 @@ function scoreResults(result, metrics, logger) {
 
     // Count up category totals as we go.
     for (const [category, demerit] of Object.entries(data.demerits)) {
-      demeritSumsByCategory[category] += parseFloat(demerit);
+      demeritSumsByCategory[category] += demerit;
     }
 
     // After adding category totals, we can calculate the total impact for the given rule.
-    data.demerits.total = Object.values(data.demerits)
-      .reduce((sum, num) => sum + parseFloat(num), 0.0)
-      .toFixed(2);
+    data.demerits.total = includeDecimals(
+      Object.values(data.demerits).reduce((sum, num) => sum + num, 0.0),
+      2
+    );
 
     scoringData.push(data);
   });
@@ -62,11 +63,12 @@ function scoreResults(result, metrics, logger) {
 
   // Average the categorized scores to produce the overall score.
   // They are already weighted through their coefficients.
-  impactSummary.overall = (
+  impactSummary.overall = includeDecimals(
     getCategories()
-      .map(c => parseFloat(impactSummary[c]))
-      .reduce((total, score) => total + score) / getCategories().length
-  ).toFixed(0);
+      .map(c => impactSummary[c])
+      .reduce((total, score) => total + score) / getCategories().length,
+    0
+  );
 
   return {
     impactSummary,
@@ -97,7 +99,7 @@ function computeCategorizedScores(rule, count, metrics) {
 
   // Base the categories on those defined for the given rule in the rubric.
   rule.categories.forEach(c => {
-    result[c] = (baseScore * getCategoryCoefficient(c)).toFixed(2);
+    result[c] = includeDecimals(baseScore * getCategoryCoefficient(c), 2);
   });
 
   return result;
@@ -150,7 +152,16 @@ function tally(result, logger) {
 // is the "/40", which is just scaling the input subjectively — it's
 // a number we will keep tuning alongside tuning the demerit coefficients.
 function computeOverallScore(demeritSum) {
-  return (100 - (100 * Math.atan(demeritSum / 40)) / Math.asin(1)).toFixed(0);
+  return includeDecimals(
+    100 - (100 * Math.atan(demeritSum / 40)) / Math.asin(1),
+    0
+  );
+}
+
+// In order to display numbers with meaningful precision,
+// only use the first "number" of decimal places.
+function includeDecimals(value, number) {
+  return parseFloat(value.toFixed(number));
 }
 
 module.exports = {

packages/validator/test/scoring-tool/score.test.js

@@ -30,49 +30,49 @@ describe('scoring-tool score tests', function () {
 
     expect(results).toEqual({
       impactSummary: {
-        usability: '83',
-        security: '100',
-        robustness: '82',
-        evolution: '88',
-        overall: '88',
+        usability: 83,
+        security: 100,
+        robustness: 82,
+        evolution: 88,
+        overall: 88,
       },
       scoringData: [
         {
           rule: 'ibm-avoid-property-name-collision',
           count: 2,
           func: '2×10÷operations',
           demerits: {
-            usability: '5.00',
-            total: '5.00',
+            usability: 5.00,
+            total: 5.00,
           },
         },
         {
           rule: 'ibm-etag-header',
           count: 3,
           func: '3×1÷operations',
           demerits: {
-            usability: '0.75',
-            robustness: '1.50',
-            total: '2.25',
+            usability: 0.75,
+            robustness: 1.50,
+            total: 2.25,
           },
         },
         {
           rule: 'ibm-no-array-responses',
           count: 1,
           func: '1×10÷operations',
           demerits: {
-            evolution: '7.50',
-            total: '7.50',
+            evolution: 7.50,
+            total: 7.50,
           },
         },
         {
           rule: 'ibm-operation-summary',
           count: 2,
           func: '2×10÷operations',
           demerits: {
-            usability: '5.00',
-            robustness: '10.00',
-            total: '15.00',
+            usability: 5.00,
+            robustness: 10.00,
+            total: 15.00,
           },
         },
       ],
@@ -119,8 +119,8 @@ describe('scoring-tool score tests', function () {
 
     const scores = computeCategorizedScores(rubricEntry, 4, metrics);
     expect(scores).toEqual({
-      usability: '2.00',
-      evolution: '6.00',
+      usability: 2.00,
+      evolution: 6.00,
     });
   });
 
@@ -183,12 +183,12 @@ describe('scoring-tool score tests', function () {
   });
 
   it('should computeOverallScore', function () {
-    expect(computeOverallScore(0)).toBe('100');
-    expect(computeOverallScore(3.4)).toBe('95');
-    expect(computeOverallScore(12.7)).toBe('80');
-    expect(computeOverallScore(58)).toBe('38');
-    expect(computeOverallScore(123.45)).toBe('20');
-    expect(computeOverallScore(700.08)).toBe('4');
+    expect(computeOverallScore(0)).toBe(100);
+    expect(computeOverallScore(3.4)).toBe(95);
+    expect(computeOverallScore(12.7)).toBe(80);
+    expect(computeOverallScore(58)).toBe(38);
+    expect(computeOverallScore(123.45)).toBe(20);
+    expect(computeOverallScore(700.08)).toBe(4);
   });
 });