White Paper on Test Case Design -- Orthogonal Experiment Design Method

White Paper on Test Case Design -- Orthogonal Experiment Design Method

Author: Vince Source: http://blog.csdn.net/vincetest

I. Method Introduction The causal relationship between the reason used as the input condition and the output result when a test case is designed using the causal indicator is sometimes difficult to obtain from the Software Requirement Specification Description. The causal relationship is often very large, so that the number of test cases obtained by this reason is astonishing, bringing a heavy burden to software testing, in order to effectively and reasonably reduce the testing work hours and costs, orthogonal experiment design can be used to design test cases. Orthogonal experimental design method: According to Galois theory, a proper number of representative points (examples) are selected from a large number of (experimental) data (test cases ), so as to reasonably arrange the experiment (TEST) a scientific experiment design method. similar methods include Clustering Analysis and factor method. Steps for designing test cases using orthogonal experiments : 1. Extraction Function Description , Construction factor -- Status table The conditions that affect the experiment indicators are called factors. . The condition that affects the experimental factor is the factor status. . When orthogonal experiment design is used to design test cases , First, find out the operation objects and external factors that affect the function implementation according to the specification of the tested software. , Treat them as factors , The value of each factor is regarded as the State. . Define functional requirements in the Software Requirement Specification Description , Break down and expand the overall summary function requirements , Break down to specific basic functional requirements with relative independence . In this way, all the factors in the tested software can be determined. , It also provides reference for determining the weight of a factor. . Determining Factors and States is the key to designing test cases . Therefore, it is required that the values be determined as comprehensively and correctly as possible. , To ensure the test case design is complete and effective . 2. Weighted Filtering , Generate factor analysis table The selection of factors and States can be weighted by their importance . Depending on the factors and status , Frequency and test requirements , Determine the weight . 3. Test dataset construction using orthogonal table Basis for derivation of orthogonal tables Galois Theory (omitted here , Materials for mathematical statistics can be viewed as needed) . Design test cases using orthogonal experimental design method , Division by equivalence classes , Boundary Value Analysis , Factors and other methods have the following advantages: : Reduces test work hours; controls the number of generated test cases; test cases have a certain coverage rate . II. Practical drills None

 

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