CN110825621A - Regression test case priority calculation method based on dynamic risk - Google Patents
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Abstract
The invention provides a regression test case priority calculation method based on dynamic risks, which is characterized in that module error occurrence probability is calculated according to factors such as demand change, a failure dynamic impact value of a calculation module is calculated according to test case calling conditions, a dynamic risk value of a test case is finally obtained, and the dynamic risk value is sequenced to obtain the priority of the test case. According to the method, the execution condition of the code in the actual test operation process is accurately reflected by calculating the static module error occurrence probability and the dynamic module failure impact value, and is more consistent with the actual operation condition; has the characteristics of simplicity, high efficiency and the like.
Description
Technical Field
The invention belongs to the field of software testing in software engineering, and particularly relates to a regression test case priority calculation method based on dynamic risks in regression testing in an integrated test stage.
Background
Regression testing is a very important step in software testing, namely testing software after software codes are modified; in the regression test in the integrated test stage, the most reliable method is to perform regression on all test cases, but under the conditions of time tightness, budget limitation and the like, the method is not practical, so that how to selectively perform regression test is an important content in the regression test in the integrated test stage.
The test case priority calculation method based on module risk measures the risk value of a test case by calculating the probability of error occurrence and the impact caused by the error occurrence, thereby determining the priority of a regression test case; however, most module risk calculation methods are based on static code relationships, and neglect the dynamics of logic and data in the actual test case operation, which can cause serious problems in the regression test in the integrated test stage, such as modules with simple dependency relationships but complex logic, and low calculated priority, which is not considered, which is obviously contrary to the conventional principles.
Aiming at solving the problems, the invention provides a regression test case priority calculation method based on dynamic risks aiming at the regression test in the integrated test stage, the error occurrence probability is calculated according to factors such as demand change, defect repair and code quantity, the dynamic influence caused by the error occurrence is calculated according to the dynamic module calling relation when the test case actually runs, and the dynamic risk value of the test case is further obtained, so that the calculation of the regression test case priority is more accurately realized.
Disclosure of Invention
The regression test case priority calculation method based on the dynamic risk comprises the following steps.
Step 1, collecting and counting code change conditions caused by repairing defects by taking a module as a unit; collecting and counting code change conditions caused by change based on requirements;
the module may be a function or a method for implementing a specific function, or may be a class or a set including a plurality of functions or methods.
Step 2, calculating risk factors of the module caused by requirement change and requirement complexity;
the change of the requirement is an important factor causing code modification, and the modification times and the modification degree of the code in the module are important factors influencing the risk of the module; therefore, the more changes in the requirements a module covers, the higher the risk level;
another complex module usually contains more requirements, which also means that the module is more demanding and complex, and the risk is greater;
the risk factor of a module due to requirement change and requirement complexity can be represented by the ratio of the requirement change quantity contained in the module to the total requirement change quantity, and multiplied by the ratio of the requirement item of the module to the total requirement item.
Step 3, calculating risk factors of the module caused by defect repair and complexity;
repairing defects is another factor causing code modification, and in the code modification process, the original defects can be repaired, but new defects can be generated; the more the number of the modified defects is, the greater the risk degree is;
meanwhile, the complexity of the modification process can cause the increase of risk factors, and the more the number of lines of code modification is, the greater the risk degree is;
the risk factor of a module due to repair defects and complexity can be represented by the ratio of the number of modified defects to the total number of defects multiplied by the ratio of the number of rows of the module modification code to the total number of rows of the module code.
Step 4, calculating risk factors of the module caused by code complexity and code quantity;
generally, codes with more complex logic use more judgment and circulation, which can result in increased risk level, which can be measured by circle complexity;
meanwhile, the code amount reflects the complexity of the code to a certain extent, and the code amount can be measured by the code line number of the module;
the risk factor of a module caused by code complexity and code amount can be represented by the ratio of the circle complexity of the module to the maximum circle complexity of all modules, and the ratio of the code line number of the module to the maximum code line number of all modules.
Step 5, calculating the module error occurrence probability caused by the risk factors;
the module error occurs, which means that the module has operation error in the operation process and behavior that the module does not reach the expected function, and is also called module failure;
the probability of a module occurring an error can be expressed as the product of the risk factors for that module calculated in steps 2-4.
Step 6, manually appointing an importance value of the module;
the importance value of a module characterizes how much the module should be valued, specified manually.
Step 7, counting the dynamic calling relation among modules in the test case;
the calling relation among the modules reflects the dependency relation among the modules in the software; if a module contains errors, the modules which directly or indirectly call the module are obviously influenced when faults occur;
the calling relation between the test case execution time modules is called as dynamic calling relation; the collection of all the modules to be actually called is called as the dynamic sub-module collection of the test case;
for a module in a test case, when the test case executes, a set of all called modules of the module is called a set of dynamic sub-modules of the module in the test case.
Step 8, calculating a module failure dynamic impact value in the test case;
in the running process of the test case, when a certain module fails, all other modules calling the module are affected;
the module failure dynamic impact value in the test case can be expressed as a ratio of an average value of importance of all modules to a maximum value of importance of all modules in all dynamic sub-module sets of the module of the test case.
Step 9, calculating the dynamic risk factor of a single module in the test case;
the dynamic risk factor of a single module in a test case can be expressed as the product of the module error occurrence probability of the module and the dynamic impact value of the module failure in the test case.
Step 10, calculating a dynamic risk value of a test case and a priority of the test case;
the dynamic risk value of the test case can be expressed as the sum of the dynamic risk factors of all modules in the dynamic sub-module set of the test case;
sequencing according to the dynamic risk values of the test cases, wherein the priority with the maximum dynamic risk value is the highest;
therefore, the calculation of the priority of the test cases and the sequencing of the test cases are realized.
Aiming at the priority problem of a regression test case in an integrated test, the method calculates the module error occurrence probability according to factors such as demand change, defect modification, code complexity and the like, calculates the module failure dynamic impact value brought by the module when the module fails in the test case according to the dynamic calling relation among the modules in the test case, and takes the product of the two as the dynamic risk factor of the module in the test case; and accumulating the dynamic risk factors of all modules dynamically called when the test case runs to obtain the dynamic risk value of the test case, and sequencing the dynamic risk value to obtain the priority of the test case. According to the method, the execution condition of the code in the actual test operation process is accurately reflected by calculating the static module error occurrence probability and the dynamic module failure impact value, and is more consistent with the actual operation condition; the algorithm has the characteristics of simplicity, high efficiency and the like, and has a good application effect.
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FIG. 1 is a schematic flow diagram of the process of the present invention.
Detailed Description
In order to more clearly show the objects and technical solutions of the present invention, the following will describe the specific embodiments and parameters of the present invention in more detail with reference to the specific implementation processes and the attached drawings.
Step 1, collecting and counting code change conditions caused by repairing defects by taking a module as a unit; and collecting and counting code change conditions caused by the change based on the demand.
Step 2, calculating risk factors of the module caused by requirement change and requirement complexity;
the risk factor of a module due to requirement change and requirement complexity can be represented by the ratio of the requirement change quantity contained in the module to the total requirement change quantity, and multiplied by the ratio of the requirement item of the module to the total requirement item.
If the requirement change quantity of a certain module is 3, the total requirement change quantity of the regression is 100, and the ratio of the two is 0.03; the corresponding requirement item of the module is 5, the total requirement item is 100, and the ratio of the two is 0.05; the final value of the risk factor is 1.5E-3.
Step 3, calculating risk factors of the module caused by defect repair and complexity;
the risk factor of a module due to repair defects and complexity can be represented by the ratio of the number of modified defects to the total number of defects multiplied by the ratio of the number of rows of the module modification code to the total number of rows of the module code.
If a certain module repairs 2 defects at this time, the total number of the defects repaired by the regression at this time is 20, and the ratio of the two is 0.10; the corresponding module code is modified into 15 lines, the module code amount is 150 lines, and the ratio of the two is 0.10; the value of the risk factor is finally 1E-2.
Step 4, calculating risk factors of the module caused by code complexity and code quantity;
the risk factor of a module caused by code complexity and code amount can be represented by the ratio of the circle complexity of the module to the maximum circle complexity of all modules, and the ratio of the code line number of the module to the maximum code line number of all modules.
If the circle complexity of a certain module is 10, the maximum circle complexity of all the modules is 100, and the ratio of the circle complexity to the maximum circle complexity is 0.10; the total code amount of the module is 150 lines, the maximum code line number in all the modules is 300 lines, and the ratio of the two lines is 0.50, so that the value of the risk factor is 5E-2 finally.
Step 5, calculating the module error occurrence probability caused by the risk;
the probability of a module occurring an error can be expressed as the product of the risk factors for that module calculated in steps 2-4.
As with the above process, the probability of error for this module is 1.5E-3X 1E-2X 5E-2, with a final value of 7.5E-7.
Step 6, manually appointing an importance value of the module;
the importance value of the module represents the degree to which the module should be valued, and is manually specified;
the importance values of the modules can be classified into 5 levels of 1-5, wherein 1 represents the least important and 5 represents the most important.
Step 7, counting the dynamic calling relation among modules in the test case;
for a module in a test case, when the test case is executed, the set of all called modules is called as a dynamic sub-module set of the module in the test case;
if a test case contains an M1 module, and the M1 module dynamically calls M3 and M5, and the M5 dynamically calls M6 and M7, the dynamic sub-module set of the M1 module in the test case is: { M3, M5, M6, M7 }.
Step 8, calculating a module failure dynamic impact value in the test case;
the module failure dynamic impact value in the test case can be expressed as a ratio of an average value of importance of all modules to a maximum value of importance of all modules in all dynamic sub-module sets of the module of the test case.
In the example in step 7, assuming that the importance of M3, M5, M6 and M7 are 2, 3, 1 and 4, respectively, the average value of the importance of the dynamic sub-modules of the module M1 is: (2+3+1+4)/4= 2.5; assuming that the maximum value of importance of all modules in all test cases is 4, the dynamic impact value of the M1 module in the test case is 2.5/4= 0.625.
Step 9, calculating the dynamic risk value of a single module in the test case;
the dynamic risk factor of a single module in a test case can be expressed as the product of the module error occurrence probability of the module and the dynamic impact value of the module failure in the test case.
If the probability of the error occurrence of a certain module in the test case is 7.5E-7, and the dynamic impact value of the module failure is 0.625, the dynamic risk factor of the module in the test case is 4.7E-7.
Step 10, calculating a dynamic risk value of a test case and a priority of the test case;
the dynamic risk value of the test case can be expressed as the sum of the dynamic risk factors of all modules in the dynamic sub-module set of the test case;
sequencing according to the dynamic risk values of the test cases, wherein the priority with the maximum dynamic risk value is the highest;
therefore, the calculation of the priority of the test cases and the sequencing of the test cases are realized.
For example, the test case T1 dynamically calls the modules M1 and M2, the test case T2 dynamically calls the modules M3 and M4, and the dynamic risk factors of the modules M1, M2, M3, and M4 are 3.75e-5, 1e-5, 3e-5, and 2e-6, respectively, then the dynamic risk value of the test case T1 is 4.75e-5, the dynamic risk value of the test case T2 is 3.2e-5, the dynamic risk value of the test case T1 is greater than T2, and the priority is greater than T2.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the foregoing embodiments illustrate the present invention in detail, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; or the use sequence of each step is modified, and the modifications or the substitutions do not cause the essence of the corresponding technical scheme to depart from the scope of the technical scheme of each embodiment of the invention; the values of the various thresholds and ranges of the present invention may vary depending on the particular situation.
Claims (10)
1. The regression test case priority calculation method based on the dynamic risk is characterized by comprising the following steps of:
step 1, collecting and counting code change conditions caused by repairing defects by taking a module as a unit; collecting and counting code change conditions caused by change based on requirements;
step 2, calculating risk factors of the module caused by requirement change and requirement complexity;
step 3, calculating risk factors of the module caused by defect repair and complexity;
step 4, calculating risk factors of the module caused by code complexity and code quantity;
step 5, calculating the module error occurrence probability caused by the risk factors;
step 6, manually appointing an importance value of the module;
step 7, counting the dynamic calling relation among modules in the test case;
step 8, calculating a module failure dynamic impact value in the test case;
step 9, calculating the dynamic risk factor of a single module in the test case;
step 10, calculating a dynamic risk value of a test case and a priority of the test case;
therefore, the calculation of the priority of the test cases and the sequencing of the test cases are realized.
2. In step 2, the risk factor of the calculation module caused by the requirement change and the requirement complexity includes:
the risk factor of a module due to requirement change and requirement complexity can be represented by the ratio of the requirement change quantity contained in the module to the total requirement change quantity, and multiplied by the ratio of the requirement item of the module to the total requirement item.
3. Step 3, calculating risk factors of the module caused by repairing defects and complexity, including:
the risk factor of a module due to repair defects and complexity can be represented by the ratio of the number of modified defects to the total number of defects multiplied by the ratio of the number of rows of the module modification code to the total number of rows of the module code.
4. Step 4, calculating the risk factors of the module caused by the code complexity and the code quantity, including:
the risk factor of a module caused by code complexity and code amount can be represented by the ratio of the circle complexity of the module to the maximum circle complexity of all modules, and the ratio of the code line number of the module to the maximum code line number of all modules.
5. Step 5, calculating a module error occurrence probability caused by the risk factor, including:
the module error occurs, which means that the module has operation error in the operation process and behavior that the module does not reach the expected function, and is also called module failure;
the probability of a module occurring an error can be expressed as the product of the risk factors for that module calculated in steps 2-4.
6. Step 6, manually assigning the importance value of the module, including:
the importance value of a module characterizes how much the module should be valued, specified manually.
7. Step 7, counting the dynamic call relationship between modules in the test case, including:
the calling relation between the test case execution time modules is called as dynamic calling relation; the collection of all the modules to be actually called is called as the dynamic sub-module collection of the test case;
for a module in a test case, when the test case executes, a set of all called modules of the module is called a set of dynamic sub-modules of the module in the test case.
8. Step 8, calculating a module failure dynamic impact value in the test case, including:
the dynamic impact value of module failure in a test case can be represented as a ratio of an average value of importance of all modules to a maximum value of importance of all modules in all dynamic sub-module sets of the module of the test case.
9. Step 9, calculating the dynamic risk factor of a single module in the test case, including:
the dynamic risk factor of a single module in a test case can be expressed as the product of the module error occurrence probability of the module and the dynamic impact value of the module failure in the test case.
10. The step 10 of calculating the dynamic risk value of the test case and the priority of the test case includes:
the dynamic risk value of the test case can be expressed as the sum of the dynamic risk factors of all modules in the dynamic sub-module set of the test case;
and sequencing according to the dynamic risk values of the test cases, wherein the priority with the maximum dynamic risk value is the highest.
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