CN111858384A - Efficient test method for constant false alarm detection software unit - Google Patents
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Abstract
The invention discloses a high-efficiency test method of a constant false alarm rate detection software unit, which comprises the following steps: step 1: analyzing a constant false alarm software unit, determining a large array input and output variable, and simulating to generate large array input data; step 2: creating a general drive function, assigning the large array input data, and obtaining an assigned large array input variable; and step 3: carrying out simulation test on the large array input variable after assignment to obtain a standard array; and 4, step 4: judging whether the standard array reaches a test threshold value, and if so, completing the test; and 5: if not, repeating the steps 3-5 until the test is completed. The method solves the problem of low efficiency of the traditional test constant false alarm detection software unit, parameterizes and modularizes the driving function, enhances expansibility and universality, automatically compares the expected value and the actual value of the big data output array, avoids the defects of manual input of the big data array and manual comparison of the big data output array by the traditional test tool, and improves the efficiency of software test.
Description
Technical Field
The invention relates to the technical field of software testing, in particular to an efficient testing method for a constant false alarm rate detection software unit.
Background
Constant false alarm detection is one of important contents in signal processing technology, and a constant false alarm detection software unit detects a detected signal according to a certain algorithm, so that a target signal which accords with a threshold characteristic is extracted to the maximum extent while a specified false alarm probability is maintained. When engineering is realized, the big data array reflecting the detection signal characteristics is one of the input variables of the constant false alarm detection software unit, and the target characteristic data conforming to the detection algorithm is one of the output results.
Software testing is the process of running or testing a system using manual or automated means to verify that the software meets specified requirements or to determine the difference between expected and actual results.
After the constant false alarm detection software unit engineering is realized, a reasonable test case is designed, and a test tool is used for testing and verifying the software unit, which is a necessary step. Unit testing of software is the most basic test to verify the functionality of a software unit. The testing process comprises the steps of establishing a testing case by depending on a testing tool, identifying input and output to obtain an actual running result of the software unit, and further judging the validity of the testing case by comparing an expected result with an actual result so as to verify the correctness of the constant false alarm detection software unit.
One of the input variables of the constant false alarm detection software unit is data describing the distance and frequency dimension characteristics of signals, the output result is data conforming to a detection algorithm, and when engineering is realized, a large array is usually used for representing the data in a detection unit program. When a test bench (TestBed) test tool is used for testing a software unit, the tool cannot automatically import large batch of input data, cannot directly compare expected results with actual results of large batch of output data, and can only adopt manual means, so that the unit test efficiency is low.
Disclosure of Invention
The invention aims to provide an efficient testing method for a constant false alarm detection software unit. The method aims to solve the problem that the test efficiency of the constant false alarm detection software unit is low because the traditional test tool cannot automatically read large array batch data, parameterizes and modularizes a driving function, enhances expansibility and universality, automatically compares an expected value and an actual value of a large data output array, avoids manual input of the large array data and manual comparison of the large array data by the traditional test tool, and improves the software test efficiency.
In order to achieve the purpose, the invention provides an efficient testing method of a constant false alarm detection software unit, which comprises the following steps:
step 1: analyzing the constant false alarm software unit, determining a large array input/output variable, and simulating large array input data which accords with the constant false alarm detection unit;
step 2: creating a general drive function, assigning the large array input data, and obtaining an assigned large array input variable;
and step 3: carrying out simulation test on the large array input variable after assignment to obtain a standard array of the constant false alarm detection unit;
and 4, step 4: judging whether the standard array reaches a test threshold value, if so, enabling the constant false alarm software unit to meet the test precision requirement, and completing the test;
and 5: if not, the constant false alarm software unit does not meet the requirement of the test precision, the large array input data is repeatedly assigned, and the steps 3-5 are repeated until the test is completed.
Most preferably, simulating the large array of input data further comprises the steps of:
step 1.1: analyzing the constant false alarm software unit, determining a large array input/output variable, and analyzing the programming language characteristic of the tested constant false alarm software unit and the variable type characteristic of the large array data;
step 1.2: based on Matlab software, simulating large array input data conforming to the constant false alarm detection unit according to the programming language characteristics of the constant false alarm software unit to be tested and the variable type characteristics of the large array data.
Most preferably, assigning large arrays of input data comprises the steps of:
step 2.1: respectively creating a general drive function for inputting the large array and a general drive function for outputting the large array, and simultaneously embedding TestBed test software;
step 2.2: and adding macro definition for reading the large array in the TestBed test software, assigning the input data of the large array, and obtaining the assigned input variable of the large array.
Most preferably, the parameters of the general driving function comprise a data name, a data precision digit identification, a data length and a data read-in path.
Most preferably, the simulation test comprises the steps of:
step 3.1: inputting the large array input variables after assignment into Matlab software and TestBed test software respectively to perform software simulation and software test on the constant false alarm detection unit, and obtaining an expected output value and an actual test value of the constant false alarm detection unit respectively;
step 3.2: and comparing the expected output value with the actual test value item by item, and outputting a standard array of the constant false alarm detection unit.
Most preferably, the software simulation and software testing further comprises the steps of:
step 3.1.1: inputting the large array input variable subjected to assignment into Matlab software;
step 3.1.2: matlab software simulates an expected output value of a constant false alarm detection unit;
step 3.1.3: inputting the large array input variable after being assigned into the TestBed test software;
step 3.1.4: the TestBed test software tests the constant false alarm detection unit and reads the actual test value.
Most preferably, the term-by-term alignment further comprises the steps of:
step 3.2.1: comparing and calculating the expected output value and the actual test value item by item in the TestBed test software according to the required precision of the test to obtain the comparison result of each item;
step 3.2.2: and an array formed according to the comparison results of all the items is used as a standard array of the constant false alarm detection unit.
Most preferably, the test threshold is 1, and the standard array reaches the test threshold, that is, each comparison result in the standard array outputs 1.
By using the method and the device, the problems that the traditional test tool cannot automatically read data and the test efficiency of the constant false alarm detection software unit is low are solved, the drive function is parameterized and modularized, the expansibility and the universality are enhanced, the expected value and the actual value of the big data output array are automatically compared, the defects that the traditional test tool manually inputs the big data array and manually compares the big data array and the big data output array are overcome, and the software test efficiency is improved.
Compared with the prior art, the invention has the following beneficial effects:
1. the high-efficiency test method for the constant false alarm detection software unit provided by the invention embeds the general drive function for reading the input and output large array data into the drive head file of the test tool, solves the defect that the test tool can only adopt manual input of the large array data, and improves the test efficiency.
2. The high-efficiency test method of the constant false alarm detection software unit provided by the invention has strong expansibility for inputting the general driving function of the large array data and outputting the general driving function of the large array data, and can process the large array data with different types, different precision requirements, different lengths and different storage positions.
3. The high-efficiency test method for the constant false alarm detection software unit automatically compares and outputs the expected value and the actual value of the large array data, automatically outputs the comparison result, and stores the comparison result into the dat file, solves the problem that a test tool cannot automatically compare the actual output result and the expected output result of the large array data, is beneficial to judging whether a test case passes or not, and improves the efficiency of software test.
Drawings
FIG. 1(a) is a schematic diagram of a distance-frequency two-dimensional constant false alarm detection reference unit provided by the present invention;
FIG. 1(b) is a schematic diagram of a constant false alarm detection processing software unit provided by the present invention;
FIG. 2 is a flow chart of a method for efficiently testing a constant false alarm rate detection software cell according to the present invention;
FIG. 3 is a flowchart of a method for assigning large array input data according to the present invention;
FIG. 4 is a flow chart showing assignment of large array input data according to the present invention;
fig. 5 is a flowchart of a method for determining whether a constant false alarm detection unit completes testing according to a flag array provided in the present invention.
Detailed Description
The invention will be further described by the following specific examples in conjunction with the drawings, which are provided for illustration only and are not intended to limit the scope of the invention.
The constant false alarm detection software unit detects the signal to be detected according to a certain algorithm, and extracts the target signal which accords with the threshold characteristic to the maximum extent while keeping the specified false alarm probability.
With the wide application of the pulse doppler processing technology in target detection signal processing software, the most commonly adopted technology is the distance-frequency two-dimensional constant false alarm detection technology. Fig. 1(a) is a schematic diagram of a distance-frequency two-dimensional constant false alarm detection software reference unit, wherein: t is the unit to be measured, G is the protection unit, and R is the reference unit.
The distance-frequency two-dimensional constant false alarm processing is substantially a modification of the one-dimensional distance constant false alarm, and as shown in fig. 1(b), input data is subjected to Fast Fourier Transform (FFT) processing, and then constant false alarm processing is performed through a certain algorithm, so as to obtain a signal meeting the threshold requirement. When the engineering is realized, the input signals entering the constant false alarm detection software unit are variables representing signal frequency distance gates, power characteristics and the like, and the output signals are variables representing signal characteristics.
The invention provides an efficient test method of a constant false alarm rate detection software unit, which comprises the following steps as shown in figure 2:
step 1: and analyzing the constant false alarm software unit, determining a large array input/output variable, and simulating large array input data conforming to the constant false alarm detection unit.
Wherein, simulating the large array input data conforming to the constant false alarm detection unit further comprises the following steps:
step 1.1: analyzing the constant false alarm software unit, determining a large array input/output variable, and analyzing the programming language characteristic of the tested constant false alarm software unit and the variable type characteristic of the large array data;
in this embodiment, the large array output data of the constant false alarm detection unit is 4096 frequency points and 13 range gates, 4096 × 13 ═ 53248 data needs to be detected when the constant false alarm detection unit detects, a one-dimensional floating point large array a [53248] is used to represent the input array of the signal frequency power range gate characteristic, b [53248] represents the signal power characteristic output array after the false alarm detection, and the constant false alarm detection program is implemented by using C language.
Step 1.2: based on Matlab software, simulating large array input data conforming to the constant false alarm detection unit according to the programming language characteristics of the constant false alarm software unit to be tested and the variable type characteristics of the large array data.
In this embodiment, the large array of input data that is simulated by Matlab software to be consistent with the constant false alarm detection unit is the a [53248] array stored in the format of a.
Step 2: creating a general drive function, assigning the large array input data, and obtaining an assigned large array input variable;
the assignment of the large array input data comprises the following steps:
step 2.1: respectively creating a universal drive function of an input large array and a universal drive function of an output large array, and simultaneously embedding the universal drive functions into a C language background drive head file Cbrunlun.h in a TestBed installer self-contained folder LDRA _ Toolsuite \ C in the TestBed test software.
As shown in fig. 3, the parameters of the general drive function for inputting the large Array [ ] include the parameter name consistent with the input variable type, the data precision digit number identification n, the data length len, and the location where the input data is stored. Reading data through a storage path, and performing bit-by-bit judgment on each input data in a variable cache region:
(1) if the read number is integer (int), firstly judging whether the first bit is a sign bit, if so, recording the sign, then reading the corresponding value of the rest bits, if not, directly starting to read the value, reading the value until the sign (generally, a carriage return sign) is finished, after the reading is finished, multiplying the sign bit of the sign number with the read variable value, and finishing the data reading;
(2) if the read number is a floating point (float) type, firstly judging whether the first bit is a sign bit, if so, recording the sign and then reading the corresponding value of the rest bits, if not, directly starting to read the numerical value, judging the position of a decimal point ". multidot.", and determining the bit number of the reading end according to the precision requirement n, namely, when the decimal point is read, the data is read completely, after the reading is finished, multiplying the sign bit of the signed number with the read variable value, and finishing the data reading. And after reading a variable value successfully, storing the cache variable in the corresponding position of the input library function and refreshing the cache area to start to read the next variable.
Step 2.2: and adding macro definition for reading the large array in a background driver in the TestBed test software, and assigning the input data of the large array to obtain the assigned input variable of the large array.
And adding a macro definition for reading a large array in a View \ Edit pre _ include function of background driver code inserts in the TestBed test tool, then initializing a code, reading input large array data, assigning values and obtaining assigned large array input variables.
In the present embodiment, as shown in fig. 4, the parameters of the generic driver function to which the large Array [ ] is input include a parameter name a that matches the type of the input variable a [53248], the data precision digit number flag n is 3, the data length len is 53248, and the location where the data is stored. And inputting a [0] -12.06824 in the large array, when reading the number, firstly recording the sign bit "-", wherein the precision requirement is n ═ 3, namely, keeping the value of 3 bits after the decimal, stopping reading after 3 three bits after reading the decimal, at the moment, the value of the buffer area is 12.068 × (-1) -12.068, storing the value in the library function, refreshing the buffer area, reading a [1], and circulating until the input large array variable is completely read by the drive function. The general drive function for the output large array is similar to the general drive function for the input large array.
Therefore, the general driving functions of the input large array and the output large array have strong adaptability and expansibility, and when the input and output variables, the data length and the storage position are changed, only the corresponding parameters are required to be changed.
And step 3: carrying out simulation test on the large array input variable after assignment to obtain a standard array of the constant false alarm detection unit; the simulation test comprises the following steps:
step 3.1: and respectively inputting the large array input variables after assignment into MatLab software and TestBed testing software to perform software simulation and software test on the constant false alarm detection unit, and respectively obtaining an expected output value and an actual test value of the constant false alarm detection unit.
Wherein, the software simulation and the software test also comprise the following steps:
step 3.1: inputting the large array input variable subjected to assignment into Matlab software;
step 3.2: matlab software simulates an expected output value of a constant false alarm detection unit;
step 3.3: inputting the large array input variable after being assigned into the TestBed test software;
step 3.4: the TestBed test software tests the constant false alarm detection unit and reads the actual test value.
In this embodiment, Matlab software simulates that the expected output value of the constant false alarm detection unit is big array data bout [53248] stored in the format of × dat; the TestBed test tool tests the actual test values read by the constant false alarm detection unit as an array of b 53248 stored in the format of a.
Step 3.2: and comparing the expected output value with the actual test value item by item, and outputting a standard array of the constant false alarm detection unit. As shown in fig. 5, the item-by-item comparison further includes the following steps:
step 3.2.1: according to the required precision of the test, comparing the big array data of the expected output value bout [53248] with the array of the actual test value b [53248] item by item in the clearop of a background driver CodeInserts in the TestBed test software to obtain the comparison result of each item;
step 3.2.2: and an array formed according to the comparison results of all the items is used as a standard array flag of the constant false alarm detection unit [53248 ].
In this embodiment, assuming that integer variable i is used to represent compared array items bout [ i ] and b [ i ], if the comparison result is within the required precision range, the output flag data flag [ i ] of this item is 1; if the comparison result is outside the required precision range, the output flag data flag [ i ] of the item is 0. The array formed by each comparison result generates flag array flag [53248 ].
And 4, step 4: judging whether the standard array flag [53248] reaches a test threshold value, if so, enabling the constant false alarm software unit to meet the test precision requirement, and completing the test;
and 5: if not, the constant false alarm software unit does not meet the requirement of the test precision, the large array input data is repeatedly assigned, and the steps 3-5 are repeated until the test is completed.
In this embodiment, the test threshold is 1; when the standard array flag [53248] reaches the test threshold, all comparison results in the standard array flag [53248] are output as 1; if the flag arrays flag [53248] are all 1, the actual test result is in accordance with the precision requirement, and the test case passes;
the standard array flag [53248] does not reach the test threshold, namely, the comparison results in the standard array flag [53248] are not all output 1; if the flag [53248] has a value which is not 1, the fact that the actual test result has an item with a poor precision requirement is indicated, and the test case does not pass; the reason that the test fails needs to be analyzed, the test case is redesigned or the tested program is perfected, namely, after the large array input data is repeatedly assigned, the test is carried out again until the flag array flag [53248] is all 1, and the test is completed.
The working principle of the invention is as follows:
analyzing the constant false alarm software unit, determining a large array input/output variable, and simulating large array input data which accords with the constant false alarm detection unit; creating a general drive function, assigning the large array input data, and obtaining an assigned large array input variable; carrying out simulation test on the large array input variable after assignment to obtain a standard array of the constant false alarm detection unit; judging whether the standard array reaches a test threshold value, if so, enabling the constant false alarm software unit to meet the test precision requirement, and completing the test; if not, the constant false alarm software unit does not meet the requirement of test precision, and repeatedly assigns values to the large array of input data and repeatedly tests until the test is completed.
In summary, the efficient testing method for the constant false alarm detection software unit solves the problems that the traditional testing tool does not automatically read data and the testing efficiency of the constant false alarm detection software unit is low, parameterizes and modularizes the driving function, enhances expansibility and universality, automatically compares the expected value and the actual value of the big data output array, avoids the defects of manual input and manual comparison of the big data output array by the traditional testing tool, and improves the software testing efficiency.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (8)
1. An efficient test method for a constant false alarm detection software unit is characterized by comprising the following steps:
step 1: analyzing a constant false alarm software unit, determining a large array input/output variable, and generating large array input data conforming to the constant false alarm detection unit by adopting MatLab software simulation;
step 2: creating a general drive function, assigning the large array input data, and obtaining an assigned large array input variable;
and step 3: carrying out simulation test on the large array input variable after assignment to obtain a standard array of the constant false alarm detection unit;
and 4, step 4: judging whether the standard array reaches a test threshold value, if so, enabling the constant false alarm software unit to meet the test precision requirement, and completing the test;
and 5: if not, the constant false alarm software unit does not meet the requirement of the test precision, the large array input data is repeatedly assigned, and the steps 3-5 are repeated until the test is completed.
2. The method for efficient testing of a constant false alarm detection software cell of claim 1, wherein simulating the large array of input data further comprises the steps of:
step 1.1: analyzing a constant false alarm software unit, determining a large array of input and output variables, and analyzing the programming language characteristics of the tested constant false alarm software unit and the variable type characteristics of the large array of input and output variables;
step 1.2: and simulating a large array of input data conforming to the constant false alarm detection unit according to the programming language characteristics and the variable type characteristics based on Matlab software.
3. The method for efficient testing of constant false alarm detection software cells of claim 1, wherein assigning values to the large array of input data comprises the steps of:
step 2.1: respectively creating a general drive function for inputting the large array and a general drive function for outputting the large array, and simultaneously embedding TestBed test software;
step 2.2: and adding macro definition for reading the large array in the TestBed test software, and assigning the input data of the large array to obtain the assigned input variable of the large array.
4. The method for efficient testing of a constant false alarm detection software cell of claim 3, wherein the parameters of the generic driver function comprise a data name, a data precision digit identifier, a data length, and a data read-in path.
5. The method for efficient testing of a constant false alarm detection software cell of claim 1, wherein the simulation test comprises the steps of:
step 3.1: inputting the large array input variables after assignment into Matlab software and TestBed test software respectively to perform software simulation and software test on the constant false alarm detection unit, and obtaining an expected output value and an actual test value of the constant false alarm detection unit respectively;
step 3.2: and comparing the expected output value with the actual test value item by item, and outputting a standard array of the constant false alarm detection unit.
6. The method for efficient testing of a constant false alarm detection software cell of claim 5, wherein the software simulation and software testing further comprises the steps of:
step 3.1.1: inputting the large array input variable subjected to assignment into Matlab software;
step 3.1.2: matlab software simulates an expected output value of a constant false alarm detection unit;
step 3.1.3: inputting the large array input variable after being assigned into the TestBed test software; step 3.1.4: the TestBed test software tests the constant false alarm detection unit and reads the actual test value.
7. The method for efficient testing of a constant false alarm detection software unit of claim 5, wherein said comparing item by item further comprises the steps of:
step 3.2.1: comparing and calculating the expected output value and the actual test value item by item in the TestBed test software according to the required precision of the test to obtain comparison results of the items;
step 3.2.2: and an array formed according to the comparison results of all the items is used as a standard array of the constant false alarm detection unit.
8. The method as claimed in claim 1, wherein the test threshold is 1, and the standard array reaches the test threshold, i.e. each comparison result in the standard array outputs 1.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114706745A (en) * | 2022-01-12 | 2022-07-05 | 中国电子科技集团公司第十研究所 | Method for self-adaptively identifying built-in test BIT false alarm of complex electronic system |
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