reformat to pass github check

Author: milaGGL

packages/firestore/src/remote/bloom_filter.ts

@@ -26,10 +26,17 @@ export class BloomFilter {
     padding: number,
     private readonly hashCount: number
   ) {
-    debugAssert(padding >= 0, 'Padding is negative.');
     this.bitSize = this.bitmap.length * 8 - padding;
-    debugAssert(this.bitSize >= 0, 'Bitmap size is negative.');
-    debugAssert(this.hashCount >= 0, 'Hash count is negative.');
+    if (this.bitSize === 0) {
+      debugAssert(
+        this.hashCount === 0,
+        'An empty bitmap should correspond to 0 hashCount.'
+      );
+    } else {
+      debugAssert(padding >= 0, 'Padding is negative.');
+      debugAssert(this.bitSize >= 0, 'Bitmap size is negative.');
+      debugAssert(this.hashCount >= 0, 'Hash count is negative.');
+    }
   }
 
   getBitSize(): number {
@@ -41,10 +48,6 @@ export class BloomFilter {
     if (this.bitSize === 0) {
       return false;
     }
-    // If document name is an empty string, return false
-    if (!document) {
-      return false;
-    }
 
     // Hash the string using md5
     const md5 = new Md5();

packages/firestore/test/unit/remote/bloom_filter.test.ts

@@ -48,26 +48,45 @@ import {
 
 describe('BloomFilter', () => {
   it('can initiate an empty BloomFilter', () => {
-    const bloomFilter = new BloomFilter(
-      /* bitmap */ new Uint8Array(0),
-      /* padding */ 0,
-      /* hashCount */ 0
-    );
+    const bloomFilter = new BloomFilter(new Uint8Array(0), 0, 0);
     expect(bloomFilter.getBitSize()).to.equal(0);
   });
 
   it('can initiate a non empty BloomFilter', () => {
     const bloomFilter = new BloomFilter(
-      /* bitmap */ new Uint8Array([151, 153, 236, 116, 7]),
-      /* padding */ 3,
-      /* hashCount */ 13
+      new Uint8Array([151, 153, 236, 116, 7]),
+      3,
+      13
     );
     expect(bloomFilter.getBitSize()).to.equal(37);
   });
 
+  it('should throw error if empty BloomFilter has hash count', () => {
+    try {
+      new BloomFilter(new Uint8Array(0), 0, 1);
+      expect.fail();
+    } catch (error) {
+      expect(
+        (error as Error)?.message.includes(
+          'INTERNAL ASSERTION FAILED: An empty bitmap should correspond to 0 hashCount.'
+        )
+      ).to.be.true;
+    }
+    try {
+      new BloomFilter(new Uint8Array(1), 8, 1);
+      expect.fail();
+    } catch (error) {
+      expect(
+        (error as Error)?.message.includes(
+          'INTERNAL ASSERTION FAILED: An empty bitmap should correspond to 0 hashCount.'
+        )
+      ).to.be.true;
+    }
+  });
+
   it('should throw error if padding is negative', () => {
     try {
-      new BloomFilter(new Uint8Array(0), -1, 0);
+      new BloomFilter(new Uint8Array(1), -1, 1);
       expect.fail();
     } catch (error) {
       expect(
@@ -80,7 +99,7 @@ describe('BloomFilter', () => {
 
   it('should throw error if bitmap size is negative', () => {
     try {
-      new BloomFilter(new Uint8Array(0), 1, 0);
+      new BloomFilter(new Uint8Array(0), 1, 1);
       expect.fail();
     } catch (error) {
       expect(
@@ -93,7 +112,7 @@ describe('BloomFilter', () => {
 
   it('should throw error if hash count is negative', () => {
     try {
-      new BloomFilter(new Uint8Array(0), 0, -1);
+      new BloomFilter(new Uint8Array(1), 1, -1);
       expect.fail();
     } catch (error) {
       expect(
@@ -123,17 +142,18 @@ describe('BloomFilter', () => {
 
   /**
    * Golden tests are generated by backend based on inserting n number of
-   * documents path into Bloom filter.
+   * documents path into a bloom filter.
    *
-   * Full documents path is generated by concating documentPrefix and n, ie,
-   * projects/project-1/databases/database-1/documents/coll/doc11
+   * Full document path is generated by concating documentPrefix and number n,
+   * ie, projects/project-1/databases/database-1/documents/coll/doc12
    *
    * The test result is generated by checking the membership of documents from
    * documentPrefix+0 to documentPrefix+2n. The membership results from 0 to n
-   * is expected to be 1, and from n to 2n to be 0 with some false positive results.
+   * is expected to be true (1), and the membership results from n to 2n is
+   * expected to be false (0) with some false positive results (1).
    *
-   * The test result of BloomFilter.mightContain() should match the backend result
-   * exactly.
+   * The test result of BloomFilter.mightContain() should match the backend
+   * result exactly.
    */
   describe('BloomFilter membership test', () => {
     const documentPrefix =
@@ -155,7 +175,7 @@ describe('BloomFilter', () => {
       return ByteString.fromBase64String(encoded).toUint8Array();
     }
 
-    it('mightContain result for 1 document with 1 false positive rate should match backend result', () => {
+    it('mightContain result for 1 document with 1 false positive rate', () => {
       const { bits, hashCount } = testDataCount1Rate1 as TestDataType;
       const { membershipTestResults } = testResultCount1Rate1 as TestResultType;
 
@@ -171,7 +191,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 1 document with 0.01 false positive rate should match backend result', () => {
+    it('mightContain result for 1 document with 0.01 false positive rate', () => {
       const { bits, hashCount } = testDataCount1Rate01 as TestDataType;
       const { membershipTestResults } =
         testResultCount1Rate01 as TestResultType;
@@ -188,7 +208,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 1 document with 0.0001 false positive rate should match backend result', () => {
+    it('mightContain result for 1 document with 0.0001 false positive rate', () => {
       const { bits, hashCount } = testDataCount1Rate0001 as TestDataType;
       const { membershipTestResults } =
         testResultCount1Rate0001 as TestResultType;
@@ -205,7 +225,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 500 documents with 1 false positive rate should match backend result', () => {
+    it('mightContain result for 500 documents with 1 false positive rate', () => {
       const { bits, hashCount } = testDataCount500Rate1 as TestDataType;
       const { membershipTestResults } =
         testResultCount500Rate1 as TestResultType;
@@ -222,7 +242,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 500 documents with 0.01 false positive rate should match backend result', () => {
+    it('mightContain result for 500 documents with 0.01 false positive rate', () => {
       const { bits, hashCount } = testDataCount500Rate01 as TestDataType;
       const { membershipTestResults } =
         testResultCount500Rate01 as TestResultType;
@@ -239,7 +259,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 500 document with 0.0001 false positive rate should match backend result', () => {
+    it('mightContain result for 500 document with 0.0001 false positive rate', () => {
       const { bits, hashCount } = testDataCount500Rate0001 as TestDataType;
       const { membershipTestResults } =
         testResultCount500Rate0001 as TestResultType;
@@ -256,7 +276,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 5000 documents with 1 false positive rate should match backend result', () => {
+    it('mightContain result for 5000 documents with 1 false positive rate', () => {
       const { bits, hashCount } = testDataCount5000Rate1 as TestDataType;
       const { membershipTestResults } =
         testResultCount5000Rate1 as TestResultType;
@@ -273,7 +293,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 5000 documenta with 0.01 false positive rate should match backend result', () => {
+    it('mightContain result for 5000 documenta with 0.01 false positive rate', () => {
       const { bits, hashCount } = testDataCount5000Rate01 as TestDataType;
       const { membershipTestResults } =
         testResultCount5000Rate01 as TestResultType;
@@ -290,7 +310,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 5000 documenta with 0.0001 false positive rate should match backend result', () => {
+    it('mightContain result for 5000 documenta with 0.0001 false positive rate', () => {
       const { bits, hashCount } = testDataCount5000Rate0001 as TestDataType;
       const { membershipTestResults } =
         testResultCount5000Rate0001 as TestResultType;
@@ -307,7 +327,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 50000 documents with 1 false positive rate should match backend result', () => {
+    it('mightContain result for 50000 documents with 1 false positive rate', () => {
       const { bits, hashCount } = testDataCount50000Rate1 as TestDataType;
       const { membershipTestResults } =
         testResultCount50000Rate1 as TestResultType;
@@ -324,7 +344,7 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
     });
-    it('mightContain result for 50000 documents with 0.01 false positive rate should match backend result', () => {
+    it('mightContain result for 50000 documents with 0.01 false positive rate', () => {
       const { bits, hashCount } = testDataCount50000Rate01 as TestDataType;
       const { membershipTestResults } =
         testResultCount50000Rate01 as TestResultType;
@@ -341,9 +361,9 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
       //Extend default timeout(2000)
-    }).timeout(5000);
+    }).timeout(10_000);
 
-    it('mightContain result for 50000 documents with 0.0001 false positive rate should match backend result', () => {
+    it('mightContain result for 50000 documents with 0.0001 false positive rate', () => {
       const { bits, hashCount } = testDataCount50000Rate0001 as TestDataType;
       const { membershipTestResults } =
         testResultCount50000Rate0001 as TestResultType;
@@ -360,6 +380,6 @@ describe('BloomFilter', () => {
         expect(mightContain).to.equal(backendMembershipResult);
       }
       //Extend default timeout(2000)
-    }).timeout(5000);
+    }).timeout(10_000);
   });
 });

packages/firestore/test/unit/remote/bloom_filter_golden_test_data/index.ts

@@ -1,3 +1,20 @@
+/**
+ * @license
+ * Copyright 2022 Google LLC
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
 export { default as testDataCount1Rate1 } from './Validation_BloomFilterTest_MD5_1_1_bloom_filter_proto.json';
 export { default as testResultCount1Rate1 } from './Validation_BloomFilterTest_MD5_1_1_membership_test_result.json';
 export { default as testDataCount1Rate01 } from './Validation_BloomFilterTest_MD5_1_01_bloom_filter_proto.json';