Abstract: A method of preparing a flavor composition containing D-allulose includes: (1) weighing D-allulose, mogroside, steviol glycoside and trichlorosucrose in parts by weight, and mixing them evenly to obtain a mixed powder; (2) degassing, compressing, and rolling the mixed powder, and extruding the raw materials into flakes; and (3) crushing and granulating the shaped flakes to obtain the flavor composition. D-allulose is used as the main raw material, and added high-intensity sweeteners as auxiliary raw materials. After the raw materials are mixed evenly, dry granulation is adopted, and the powder is degassed and pre-compressed by using the crystal water in the raw materials, and squeezed by a hydraulic roller to form a bonding force between the various sweetener molecules to form flakes, and the flakes are processed by processes such as crushing and granulating to obtain the flavor composition granules containing D-allulose with the various sweeteners integrated uniformly as a whole.

Abstract: An automated, self-adaptive framework prioritizes software testing in a consistent and effective manner. A metric evaluates past test execution information for assigning regression testing priority. The metric may be calculated with reference to one or more of the following factors taken in combination: requirement, coverage, history, and cost. The requirement factor considers customer-assigned priority of testing the code, complexity of implementing the code, and proneness of the code to faults. The coverage factor considers code coverage, feature coverage, and common usage rate. The history factor considers previous bug found rate, case stable rate, and priority to calculate. The cost factor considers test case execution time, and step length. A value of each factor for one test case is measured according to that test case and is not related to other test cases. The calculation result representing the metric for each test case determines a priority of the test case.

Abstract: An automated, self-adaptive framework prioritizes software testing in a consistent and effective manner. A metric evaluates past test execution information for assigning regression testing priority. The metric may be calculated with reference to one or more of the following factors taken in combination: requirement, coverage, history, and cost. The requirement factor considers customer-assigned priority of testing the code, complexity of implementing the code, and proneness of the code to faults. The coverage factor considers code coverage, feature coverage, and common usage rate. The history factor considers previous bug found rate, case stable rate, and priority to calculate. The cost factor considers test case execution time, and step length. A value of each factor for one test case is measured according to that test case and is not related to other test cases. The calculation result representing the metric for each test case determines a priority of the test case.