CN110221957A - A kind of self-adapting random test method divided equally based on iteration region with positioning - Google Patents
A kind of self-adapting random test method divided equally based on iteration region with positioning Download PDFInfo
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Abstract
The invention discloses a kind of self-adapting random test methods divided equally based on iteration region with positioning, generate for reducing the blindness of test case in random test, improve the efficiency of random test.The invention mainly comprises: 1, determine the range of input domain；2, first test case is generated at random in input domain；3, input domain is divided equally, while randomly chooses a subdomain, then divide equally (hypothetical to divide equally) again, for the subdomain after dividing equally again, generate test case at random, form candidate test case set；4, for candidate test case set, determine close region set, by the test case composition in close region, implementation of test cases set using FSCS_ART (self-adapting random of fixed size Candidate Set) algorithm determines next test case to be executed.It constantly repeats the above process, until finding program error.By experimental verification, method of the invention improves 30 percentage points than random test performance.
Description
Technical field
The invention proposes a kind of self-adapting random test methods divided equally based on iteration region with positioning, use for testing
The generation of example, belongs to the technical field of test automation.
Background technique
With the continuous expansion of software market, software size is caused to increase increasingly, software function is increasingly complicated, how to ensure
The quality of software product becomes an important research hotspot, and software test undoubtedly becomes ensures the important of software quality
Link.For software test, scientific research personnel proposes many software testing technologies, and wherein, random test is due to the letter of its concept
It singly and can automate, receive more and more attention, existing random test process is as shown in Figure 1.
Random test can detecte out mistake that people fail to predict (and the detection of this mistake seem can only by with
Machine test is accomplished), still, exist from beginning to end for the dispute of random test, and this dispute is mainly due to random test
Only test case is randomly generated in blindness, never considers the information of test case executed, so, scientific research personnel couple
Great controversial is produced in the efficiency of random test.
Meanwhile Chan et al. has found, the performance of software test is influenced by Software failure modes, and so-called failure mode is exactly
Refer to the distribution pattern in software failure region.They have found that continuous type distribution is often presented in software failure region.Chan et al. is total
Knot proposes three kinds of failure modes: (i) bulk mode, as shown in a of Fig. 3.(ii) bar like pattern, as shown in the b of Fig. 3.
(iii) dotted mode, as shown in the c of Fig. 3.Meanwhile they point out, blocky and bar like pattern is more more universal than dotted mode.
Since failed areas is successional, it is reason to believe that, it is not that the region of failed areas should also be continuity
, so, that give the very big inspirations of scientific research personnel: when test case is uniformly distributed, will increase test case and finds failure area
The chance in domain.Based on this inspiration, Chan et al. proposes ART (self-adapting random test) method.
Traditional FSCS_ART (self-adapting random of fixed size Candidate Set is tested) method, by constantly calculating distance,
Reach being uniformly distributed for test case, but this method has very big time overhead, and pass through the adaptive of region division
Random testing method, although time overhead is small, performance is bad, thus the invention proposes based on iteration divide equally and position
Self-adapting random test method both saves time overhead, while improving based on the adaptive of region division in conjunction with two kinds of thoughts
Answer the performance of random testing method.
Summary of the invention
In order to effectively improve the performance of random testing method, the invention proposes one kind to be divided equally based on iteration region
With the self-adapting random test method of positioning.In addition, the present invention is also compared with random testing method, moving party is demonstrated
The validity and advance of method.Technical solution of the present invention includes the following steps:
Step 1, according to tested program, the dimension and range of input domain are determined；
Step 2, initialization area R (i.e. entire input domain), initialization chained list L (are used to store all white spaces
Chained list), TestRegion, TempRegion, wherein catena is abstracted as Region={ Point, Length, Testcase },
TestRegion is existing test case region chained list, is used to store region containing test case；TempRegion is
Temporary realm chained list has executed test zone for temporarily storing in subsequent region division, after region division,
List item in TempRegion is all added in TestRegion chained list.Point is the coordinate of the lower-left angle point of region R
Point, Length refer to region R in the length of each dimension, and Testcase refers to having held positioned at region R in subsequent algorithm
The test case gone；
Step 3, first test case is randomly generated in entire input domain, if test case detects program error
Accidentally, then test terminates, and otherwise goes to step 4；
Step 4, the test case executed is added in the R of region, while region R is added to TestRegion
In.
Step 5, if L chained list is not sky, step 6 is gone to, step 8 is otherwise gone to.
Step 6, a region R is randomly choosed in L chained list, for the algorithm of area operation invention setting, is generated and is surveyed
Example on probation, if test case detects mistake, test terminates, otherwise, which is added in the R of region, is gone to
Step 7；
Step 7, region R is added in TestRegion chained list, if L chained list is not sky, goes to step 6, otherwise turn
To step 8.
Step 8, for each catena of TestRegion chained list, region division is carried out, step 5 is gone to.
Specific step is as follows for above-mentioned steps 1:
Step 1.1, according to the software design document of early period, determine that the input domain range of software (has and rationally to input
Set)；
Step 1.2, the input domain determined according to step 1.1, determines the dimension of software, dimension is related to input domain, when defeated
The parameter for entering domain is N, and the dimension of that input domain is N；
Specific step is as follows for above-mentioned steps 3:
Step 3.1, according to the value range of the dimension of input domain and each dimension, first test case is randomly generated.
Step 3.2, by the testing case software, if reality output result is consistent with anticipated output result, it is believed that
It does not find software error, goes to step 4, if inconsistent, it is believed that there are mistake, tests to terminate for software.
Specific step is as follows for above-mentioned steps 6:
Step 6.1, the length of chained list L is obtained, and obtains a region T in chained list at random according to its length；
Step 6.2, for region T, it is assumed that property divides equally region T, forms set of candidate regions；
Step 6.3, for each region in set of candidate regions, a test case is generated at random, forms candidate survey
Example set on probation；
Step 6.4, for region T, " neighbours " regional ensemble of region T is found, so-called " neighbours " regional ensemble just refers to
The neighbouring regional ensemble with region T, for example, for two-dimensional space, " neighbours " region of region T, just refer to region T it is upper and lower,
Left and right four regions；
Step 6.5, the Testcase for determining each region of " neighbours " regional ensemble forms neighbouring implementation of test cases
Set；
Step 6.6, to candidate test case set and neighbouring implementation of test cases set, operation FSCS_ART is (fixed
The self-adapting random of size Candidate Set) method, select best test case as next test case to be tested；
Step 6.7, if test case detects mistake, test terminates, and otherwise, which is added to region
In T, step 7 is gone to；
Specific step is as follows for above-mentioned steps 8:
Step 8.1, each catena Region T in TestRegion (having executed test zone) chained list is traversed；
Step 8.2, for Region T, length of the region in each dimension is divided equally, generates subregion set；
Step 8.3, the Testcase in Region T is redistributed, if Testcase is located at subregion t,
Testcase is added in the t of region, while region t is added to TempRegion chained list (temporary realm chained list, temporarily storage
Test zone) in, remaining subregion is added in L chained list；
Step 8.4, after TestRegion chained list traversal, the element in TempRegion chained list is all added to
In TestRegion chained list, step 5 is gone to.
Beneficial effects of the present invention:
1, the present invention construct it is a kind of self-adapting random test method with positioning is divided equally based on iteration region, solve with
The blindness of Test cases technology in machine test method improves the performance of random test, while the time overhead of this method is very
It is small, in conclusion the efficiency of this method improves a lot compared to random test.
Detailed description of the invention
Fig. 1 is random test flow chart.
Fig. 2 is the flow chart of the method for the present invention.
Fig. 3 is three kinds of failure mode schematic diagrames；
Wherein: a. bulk failed areas；B. strip failed areas；C. dotted failed areas.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples, it is noted that described case study on implementation
It is intended merely to facilitate the understanding of the present invention, and does not play any restriction effect to it.
The present invention is provided a kind of respectively adaptive with positioning based on iteration region for the purpose of improving random test efficiency
Random testing method, is effectively detected software Bug, verifies method of the invention thus, is carried out using two-dimensional simulation experiment to it
Explanation.
As shown in Fig. 2, method proposed by the present invention includes the following steps:
Step 1, two-dimension square shape is generated as input domain, wherein the range of each dimension is (0-1), while generating failure
Rate is the square failed areas of a (being preset by testing)；
Step 2, initialization area R (entire input domain) initializes chained list L, TestRegion, TempRegion, wherein
Catena is abstracted as Region={ Point, Length, Testcase }, and wherein Point is the coordinate of the lower-left angle point of region R
Point, Length refer to the length of each dimension of region R, and Testcase refers to the execution for being located at region R in subsequent algorithm
The test case crossed；
Step 3, first test case is randomly generated in entire input domain, if test case detects program error
Accidentally, test terminates, and otherwise goes to step 4；
Step 4, the test case executed is added in the R of region, while region R is added to TestRegion
In chained list.
Step 5, if L chained list is not sky, step 6 is gone to, step 8 is otherwise gone to.
Step 6, a region R is randomly choosed in L chained list, for the algorithm of area operation invention, is generated test and is used
Example, if test case detects mistake, test terminates, and otherwise, which is added in the R of region, step 7 is gone to；
Step 7, region R is added in TestRegion chained list, if L chained list is not sky, goes to step 6, otherwise
Go to step 8.
Step 8, for each catena of TestRegion chained list, region division is carried out, step 5 is gone to.
Specific step is as follows for above-mentioned steps 1:
Step 1.1, according to the software design document of early period, determine that the input domain range of software (has and rationally to input
Set), in this example, the input domain of a two-dimension square shape is generated, range of the input domain in each dimension is 0-
1；
Step 1.2, the input domain determined according to step 1.1, determines the dimension of software, and dimension is related to input domain, due to
The input domain is related to two parameters, so dimension is 2；
Step 1.3, according to step 1.1 generate input domain, acquire the area (being set as D) of input domain, in input domain with
Machine generates a failure domain square, area is a*D.
Specific step is as follows for above-mentioned steps 3:
Step 3.1, according to the value range of the dimension of input domain and each dimension, first test case is randomly generated.
Step 3.2, the test case is judged whether in failed areas, if not in failed areas, it is believed that do not send out
Existing mistake, goes to step 4, if be located in failed areas, it is believed that there are mistake, test terminates.
Specific step is as follows for above-mentioned steps 6:
Step 6.1, the length of chained list L is obtained, and obtains a region T in chained list at random according to its length；
Step 6.2, for region T, it is assumed that property divides equally region T, forms set of candidate regions；
Step 6.3, for each region in set of candidate regions, we generate a test case at random, and composition is waited
Select test case set；
Step 6.4, for region T, " neighbours " regional ensemble of region T is found, so-called " neighbours " regional ensemble just refers to
The neighbouring regional ensemble with region T, for the example, " neighbours " region of region T just refers to the upper and lower, left and right four of region T
A region；
Step 6.5, the Testcase for determining each region of " neighbours " regional ensemble forms neighbouring implementation of test cases
Set；
Step 6.6, to candidate test case set and neighbouring implementation of test cases set, operation FSCS_ART is (fixed
The self-adapting random of size Candidate Set) method, select best test case as next test case to be tested；
Step 6.7, if test case detects mistake, test terminates, and otherwise, which is added to region
In T, step 7 is gone to；
Specific step is as follows for above-mentioned steps 8:
Step 8.1, each catena Region T in TestRegion chained list is traversed；
Step 8.2, for Region T, each dimension in region is divided equally, generates subregion set；
Step 8.3, the Testcase in Region T is redistributed, if Testcase is located at subregion t,
Testcase is added in the t of region, while region t being added in TempRegion chained list, remaining subregion is added
Into L chained list；
Step 8.4, after TestRegion chained list traversal, the element in TempRegion chained list is all added to
In TestRegion chained list, step 5 is gone to.
Evaluation criteria
On the basis of guaranteeing and improving testing efficiency, the time of Test cases technology is reduced, actual
In software test procedure, tester often when finding first Bug, has begun to program reparation, so, it may be found that first
The required test case quantity of a mistake just has important practical significance as check criteria.It is assumed that estimation discovery first
The average value of test case required for mistake as measurement standard, referred to as F_measure, that for method of the invention,
Using 5% accuracy rate and 95% confidence level, according to central-limit theorem, required experiment number is at least 3000 times.
Interpretation of result
The present invention is provided with two-dimension square shape input domain, while it is 0.005,0.001 that crash rate size, which is set separately,
0.0005 this three groups of experiments, obtain the quantity of test case needed for random test and method of the invention is respectively adopted, tool
The comparing result of body is as follows.
The comparison of 1 experimental result of table
Final experimental result is also shown, year-on-year random test, the method for the invention, improves at least 30%.
The series of detailed descriptions listed above only for feasible embodiment of the invention specifically
Protection scope bright, that they are not intended to limit the invention, it is all without departing from equivalent implementations made by technical spirit of the present invention
Or change should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of self-adapting random test method divided equally based on iteration region with positioning, which comprises the steps of:
Step 1, according to tested program, the dimension and range of input domain are determined；
Step 2, initialization area R initializes chained list L, TestRegion, TempRegion, and wherein catena is abstracted as
Region={ Point, Length, Testcase }, wherein Point is the coordinate points of the lower-left angle point of region R, and Length is referred to
In the length of each dimension, Testcase refers in subsequent algorithm and uses positioned at the test that had executed of the region R region R
Example；
Step 3, first test case is randomly generated in entire input domain R, if test case detects program error,
Test terminates, and otherwise goes to step 4；
Step 4, the test case executed is added in the R of region, while region R is added in TestRegion.
Step 5, if chained list L is not sky, step 6 is gone to, step 8 is otherwise gone to；
Step 6, a region R is randomly choosed in chained list L, for the algorithm of area operation setting, generates test case, such as
Fruit test case detects mistake, then test terminates, and otherwise, which is added in the R of region, step 7 is gone to；
Step 7, region R is added in TestRegion chained list, if chained list L is not sky, goes to step 6, otherwise go to step
Rapid 8；
Step 8, for each catena of TestRegion chained list, region division is carried out, step 5 is gone to.
2. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that the specific implementation of the step 1 includes the following:
Step 1.1, it according to the software design document of early period, determines the input domain range of software, that is, there is the set rationally inputted,
The input domain of two-dimension square shape is generated, range of the input domain in each dimension is 0-1；
Step 1.2, the input domain determined according to step 1.1, determines the dimension of software, dimension is related to input domain, since this is defeated
Enter domain and be related to two parameters, setting dimension is 2；
Step 1.3, the input domain generated according to step 1.1, acquires the area of input domain, is set as D, be randomly generated in input domain
One failure domain square, area is a*D.
3. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that the specific implementation of the step 3 includes the following:
Step 3.1, according to the value range of the dimension of input domain and each dimension, first test case is randomly generated.
Step 3.2, the test case is judged whether in failed areas, if not in failed areas, it is believed that do not find mistake
Accidentally, step 4 is gone to, if be located in failed areas, it is believed that there are mistake, test terminates.
4. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that the specific implementation of the step 6 includes the following:
Specific step is as follows for the step 6:
Step 6.1, the length of chained list L is obtained, and obtains a region T in chained list at random according to its length；
Step 6.2, for region T, it is assumed that property divides equally region T, forms set of candidate regions；
Step 6.3, for each region in set of candidate regions, a test case is generated at random, is formed candidate test and is used
Example set；
Step 6.4, for region T, " neighbours " regional ensemble of region T is found, so-called " neighbours " regional ensemble just refers to and area
Domain T neighbouring regional ensemble, for example, for two-dimensional space, " neighbours " region of region T, just refer to region T it is upper and lower, left,
Right four regions；
Step 6.5, the Testcase in each region of " neighbours " regional ensemble, the neighbouring implementation of test cases collection of composition are determined
It closes；
Step 6.6, to candidate test case set and neighbouring implementation of test cases set, run FSCS_ART, i.e., it is fixed big
The self-adapting random method of small Candidate Set selects best test case as next test case to be tested；
Step 6.7, if test case detects mistake, test terminates, otherwise, which is added in the T of region,
Go to step 7.
5. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that specific step is as follows for step 8:
Step 8.1, each catena Region T in TestRegion chained list is traversed；
Step 8.2, for Region T, length of the region in each dimension is divided equally, generates subregion set；
Step 8.3, the Testcase in Region T is redistributed, it, will if Testcase is located at subregion t
Testcase is added in the t of region, while region t being added in TempRegion chained list, and remaining subregion is added to L
In chained list；
Step 8.4, after TestRegion chained list traversal, the element in TempRegion chained list is all added to
In TestRegion chained list, step 5 is gone to.
6. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that the initialization area R in the step 2 is entire input domain.
7. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is that the chained list L in the step 2 is used to store the chained list of all white spaces.
8. a kind of self-adapting random test method divided equally based on iteration region with positioning according to claim 1, special
Sign is, in the step 2, TestRegion is existing test case region chained list, is used to store and has contained test case
Region；TempRegion is that temporary realm chained list has executed test section for temporarily storing in subsequent region division
List item in TempRegion is all added in TestRegion chained list by domain after region division.
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