CN113900961A - Sample generation method, device, equipment and medium for automatic testing - Google Patents
Sample generation method, device, equipment and medium for automatic testing Download PDFInfo
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Abstract
The invention discloses a sample generation method, a sample generation device, computer equipment and a storage medium for automatic testing, wherein the method comprises the following steps: acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and department; the navigation department comprises an independent route and a common route; grouping data sources according to flight dates to obtain first-level hierarchical sampling data; screening the first-level hierarchical sampling data according to the affiliated driver to obtain second-level hierarchical sampling data; screening the second-level hierarchical sampling data by using the independent air routes and the common air routes to obtain third-level hierarchical sampling data; and performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors. According to the technical scheme, the sample data capable of covering most scenes can be selected, the coverage and the representativeness of the sample are considered, the sample data is adaptive to the search behavior of the user, and the test requirement is met.
Description
Technical Field
The present invention relates to the field of information processing, and in particular, to a method and an apparatus for generating a sample for an automated test, a computer device, and a storage medium.
Background
The automatic test of the air ticket data is an important test in the test of the mobile terminal and the interface terminal of the air ticket product. That is, as an important flow of the air ticket query service, repeated and long-term operation is performed for a long time, and whether the system is abnormal or not and whether the app runs fast or not are checked in a test; and how to automatically define the reason of the network or the system bug when the abnormity occurs, and give measures for judging whether human intervention is needed.
When the whole flight data is tested, because the number of the routes is large, and if the whole route test is carried out, the cost is too large, the sample selection is usually carried out by simply sampling at present. However, this approach does not effectively guarantee the coverage and representativeness of the sample, thereby losing or weakening the effect of the test.
Disclosure of Invention
In order to overcome the technical problems, the invention provides a sample generation method, a system, computer equipment and a storage medium for automatic testing, which select sample data capable of covering most scenes, take account of the coverage and representativeness of the samples, are adaptive to the search behavior of a user and meet the testing requirements.
A sample generation method for automated testing, comprising:
acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and department; the navigation department comprises an independent route and a common route;
grouping data sources according to flight dates to obtain first-level hierarchical sampling data;
screening the first-level hierarchical sampling data according to the affiliated driver to obtain second-level hierarchical sampling data;
screening the second-level hierarchical sampling data by using the independent air routes and the common air routes to obtain third-level hierarchical sampling data;
and performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors.
A sample generation apparatus for automated testing, comprising:
the data source acquisition module is used for acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and navigation department; the navigation department comprises an independent route and a common route;
the first-level hierarchical module is used for grouping the data sources according to the flight date to obtain first-level hierarchical sampling data;
the second-level hierarchical module is used for screening the first-level hierarchical sampling data according to the driver to obtain second-level hierarchical sampling data;
the third-level layering module is used for screening the second-level layered sampling data by using the independent route and the common route to obtain third-level layered sampling data;
and the weighted random sampling module is used for performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors.
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above-described sample generation method for automated testing when executing the computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the above-mentioned steps of the sample generation method for automated testing.
According to the sample generation method and device for the automatic test, the computer equipment and the storage medium, the data source based on the user search behavior is used as the main data source of the test case, and the data sample better adapting to the user search behavior can be generated; through a three-level hierarchical screening method, sample data capable of covering most scenes is selected by utilizing a preset weighted random sampling algorithm according to air routes and carrier navigation department data in different time periods, the coverage and representativeness of the samples are considered, whether a user search engine is normal or not is judged by using the minimum cost, the test requirement is met, and the benign development of services is facilitated.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a main flow chart of a sample generation method for automated testing in one embodiment of the present invention;
FIG. 2 is a schematic diagram of a sample generation apparatus for automated testing in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment, as shown in fig. 1, a sample generation method for automated testing is provided, wherein the sample for automated testing is taken as an example of air ticket data testing, but is not limited thereto; the sample generation method for the automatic test comprises the following steps:
s1: acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and department; the airline department includes an independent airline and a common airline.
The data source is the data source of the test case, and the closer the data source is to the data input by the user in the real application, the better the coverage and representativeness of the test sample established according to the data source is, and the better the test effect can reflect the problems of the tested system/module.
The user searching behavior refers to that the user searches through the web, APP and other modes, for example, the user searches for tickets, air tickets, flight information, and searches for gourmet and tourist attractions.
Specifically, the data source comprises a departure place, a destination, a departure date and a navigation code based on user search; the method comprises the steps of collecting an air ticket searching log, cleaning data, and recording a departure place, a destination, a departure date and a navigation department code when a user searches an air ticket to obtain airline information with flight dates and navigation departments, wherein each navigation department comprises a unique airline and/or an airline shared with other navigation departments, so that a data source based on user searching behaviors is formed and is used as a main data source of a test case.
S2: and grouping the data sources according to the flight date to obtain first-level hierarchical sampling data.
Specifically, data are layered according to dates, the data coverage rate of the approaching and hot dates is high through a reasonable sampling rate, meanwhile, the omission of routes of the long-term and cold dates is avoided, and a certain coverage proportion is given. For example, the groups are divided into "within 3 days", "3 to 7 days", "7 to 15 days", "15 to 30 days", "30 to 90 days", and "departure route after 90 days", etc.
S3: and screening the first-level hierarchical sampling data according to the affiliated driver to obtain second-level hierarchical sampling data.
The amount of routes is also distributed unevenly due to the fact that the routes of different navigation departments are different; therefore, each navigation department should theoretically cover as much as possible, and the navigation departments are layered, so that each navigation department can be covered.
Specifically, a sample is selected on the basis of the first-level hierarchical sampling data, and the sample can cover all navigation departments, so that the second-level hierarchical sampling data is obtained.
S4: and screening the second-level hierarchical sampling data by using the independent air route and the common air route to obtain third-level hierarchical sampling data.
After step S3, some navigation systems have unique routes, and the data volume is often a low proportion of the total volume; but the unique air route is more important, so that the data of the unique air route of the screening department is added to improve the sample coverage ratio of the unique air route.
Specifically, the method is divided into two types according to the unique route and the common route of the navigation department, and third-level layered sampling data is formed.
S5: and performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors.
The first preset weighted random sampling method is used for weighting the third-level hierarchical sampling data and then sampling, so that a test case data set based on user search behaviors is obtained.
In the embodiment, the test data is divided into three layers according to the date, the driver, the unique route and the common route, and the test data is extracted by adopting a weighted random sampling algorithm in the third layer, so that the coverage and representativeness of the finally obtained test case data set based on the user search behavior are better than those of a mode of selecting samples by simple sampling, and the automatic test effect is improved.
Further, regarding step S4, that is, performing sample extraction on the third-level hierarchical sampling data by using a first preset weighted random sampling method, the method specifically includes the following steps:
s41: and taking the times of searching the route information by the user as the weight, and sequencing the route information in the third-level hierarchical sampling data from large to small according to the weight.
The airline information includes departure place, destination, departure time, driver code, etc., and the more times the airline information is searched by the user, the more important the airline is represented, and the larger the weight occupied.
Specifically, a route information set X = [ X1, X2, X3,.. once.. Xn ] is included in the third-level hierarchical sampling data, where n is a total number of routes, and the ith route information Xi (including a starting place, a destination, and a travel date) is searched by the user for Wi times, that is, the weight is Wi. Then, the above-mentioned X1 to Xn are arranged from large to small according to the magnitude relation of Wi.
S42: and calculating the sum of the weights of all the route information.
Specifically, the sum of the weights sum of all the routes X1 to Xn is calculated:
s43: and randomly generating a random number, wherein the random number is between 1 and the sum of the weights.
Specifically, a random number R is generated by a random algorithm before 1 to sum, that is,
wherein random is a random number acquisition function for randomly selecting a number between 1 and sum.
S44: and accumulating the weight of the sequenced route information until the weight is larger than or equal to the random number, and taking the route information traversed during accumulation as a test case data set based on the user searching behavior.
Specifically, traversing the whole sequenced route information, and counting the sum of the weights of the traversed items. If the weight corresponding to the traversed route information is greater than or equal to R, stopping traversing, namely,
Wherein k is the k-th traversed route information; and selecting the information from the first traversed item to the kth air route, and sequentially using the information as a test case data set based on the user search behavior.
In this embodiment, by using a first preset weighted random sampling method, each route information is weighted and screened on the basis of the third-level hierarchical sampling data, so as to obtain a test case data set with a more reasonable coverage.
Further, in one embodiment, cold air route data is obtained as an important supplement to the data source based on user search behavior.
Specifically, the method comprises the following steps:
s01: and acquiring all-route data based on the flight schedule information.
S02: and obtaining cold air route data after filtering the air route information in the data source from the all-air route data.
The flight schedule information is all route data acquired from a preset database. Specifically, flight-based planning information is used as full-route data, route information in a data source is removed from the full-route data, and a cold route data set is obtained
S03: the cold air route data are sampled in the same three-level hierarchical screening mode as the steps S2 to S4, namely, the data are firstly layered according to the date and then layered according to the navigation department, and then the navigation department data are divided into a unique air route and a special air route. The cold route data comprises a departure place, a destination, a departure date, a navigation code and the like.
S04: and performing sample extraction on the third-level hierarchical sampling data screened out by the cold route data by using a second preset weighted random sampling method. Different from the first preset weighted random sampling method, the data of the cold route cannot be used as the weight because the data has no user search times, so that the number of flights corresponding to the route is selected as the weight, that is, the more the number of flights corresponding to one route is, the more important the route is, and the larger the weight is.
S05: in the manner described in steps S42 to S44, the cold route data is sampled to obtain a test case data set based on the cold route.
S06: and combining the test case data set based on the user search behavior and the test case data set based on the cold air route, and performing deduplication operation, namely, eliminating duplicate data in the test case data set based on the user search behavior and the test case data set based on the cold air route to obtain a target test case data set.
In this embodiment, the target test case dataset is derived from a data source based on a user search behavior and a test case dataset based on a cold air route, so that the data of the cold air route is covered, and the coverage of the test case is further improved to meet the test requirement.
By the sample generation method provided by the embodiment of the invention, a test case data set with high coverage rate and representativeness can be obtained; by constructing the sample data of the air ticket test case, the test requirement on the stability of the air ticket service is met by using lower cost, and the benign development of the service is facilitated.
On the basis, when the subsequent test system performs abnormity judgment, only the abnormity judgment is performed on the search result through a program, and when no result is returned to the airline, the tester performs manual reconfirmation, so that whether the whole program is abnormal is judged, and related personnel are notified to process the abnormal program.
In one embodiment, as shown in fig. 2, there is provided a sample generation apparatus for automated testing, comprising:
the data source acquisition module 21 is configured to acquire a data source based on a user search behavior, where the data source includes route information including a flight date and a navigation department; the navigation department comprises an independent route and a common route;
the first-level hierarchical module 22 is configured to group the data sources according to the flight date to obtain first-level hierarchical sampling data;
the second-level layering module 23 is configured to screen the first-level layered sampling data according to the driver to obtain second-level layered sampling data;
the third-level layering module 24 is used for screening the second-level layered sampling data by using the independent route and the common route to obtain third-level layered sampling data;
and the weighted random sampling module 25 is configured to perform sample extraction on the third-level hierarchical sampling data by using a first preset weighted random sampling method, so as to obtain a test case data set based on a user search behavior.
In this embodiment, the sample generating apparatus for the automated testing is a software module corresponding to the above sample generating method for the automated testing, and the functions thereof are not described in detail here.
In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the steps of the sample generation method for automated testing in the above embodiments, such as the steps S1 to S5 shown in fig. 1.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, implements the sample generation method for automated testing in the above-mentioned method embodiments.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A method of sample generation for automated testing, comprising:
acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and navigation; the navigation department comprises an independent route and a common route;
grouping the data sources according to the flight date to obtain first-level hierarchical sampling data;
screening the first-level hierarchical sampling data according to the driver to obtain second-level hierarchical sampling data;
screening the second-level hierarchical sampling data by the independent route and the common route to obtain third-level hierarchical sampling data;
and performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors.
2. The sample generation method for automated testing of claim 1, wherein the sampling the third-level hierarchical sampling data by a first preset weighted random sampling method comprises:
taking the times of searching the route information by a user as a weight, and sequencing the route information in the third-level hierarchical sampling data from large to small according to the weight;
calculating the weight sum of all the route information;
randomly generating a random number, wherein the random number is between 1 and the weight sum;
and accumulating the weight of the sequenced route information until the weight is larger than or equal to the random number, and taking the route information traversed during accumulation as the test case data set based on the user search behavior.
3. The sample generation method for automated testing of claim 2, wherein after the obtaining of the data source based on user search behavior and before the grouping of the data source according to the flight date, the sample generation method for automated testing further comprises:
acquiring cold airline data, wherein the cold airline data comprises airline information with flight date and airline department; the navigation department comprises an independent route and a common route;
after the accumulating the weight of the sorted route information until the weight is greater than or equal to the random number, the sample generation method for the automated test further comprises:
grouping the number of the cold air lines according to the flight date to obtain first-level hierarchical sampling data;
screening the first-level hierarchical sampling data according to the driver to obtain second-level hierarchical sampling data;
screening the second-level hierarchical sampling data by the independent route and the common route to obtain third-level hierarchical sampling data;
performing sample extraction on the third-level hierarchical sampling data through a second preset weighted random sampling method to obtain a test case data set based on the cold route;
and combining the test case data set based on the user search behavior and the test case data set based on the cold air route, and performing duplication elimination operation to obtain a target test case data set.
4. The sample generation method for automated testing of claim 3, wherein the sampling the third-level hierarchical sampling data by a second preset weighted random sampling method comprises:
taking the number of flights corresponding to the flight path information as a weight, and sequencing the flight path information in the third-level hierarchical sampling data from big to small according to the weight;
calculating the weight sum of all the route information;
randomly generating a random number, wherein the random number is between 1 and the weight sum;
and accumulating the weight of the sequenced flight path information until the weight is larger than or equal to the random number, and taking the flight path information traversed during accumulation as the test case data set based on the cold flight path.
5. The sample generation method for automated testing of claim 3, wherein the obtaining cold air route data comprises:
acquiring all-route data based on flight schedule information;
and obtaining the cold air route data after filtering the route information in the data source from the all-route data.
6. The sample generation method for automated testing of claim 3, wherein the cold air route data further comprises an origin, a destination, a departure date, a navigation code.
7. The sample generation method for automated testing of any of claims 1 to 6, wherein the course information further comprises: and based on the departure place, the destination, the departure date and the navigation code searched by the user.
8. A sample generation device for automated testing, comprising:
the data source acquisition module is used for acquiring a data source based on user search behaviors, wherein the data source comprises route information with flight date and navigation department; the navigation department comprises an independent route and a common route;
the first-level hierarchical module is used for grouping the data sources according to the flight date to obtain first-level hierarchical sampling data;
the second-level hierarchical module is used for screening the first-level hierarchical sampling data according to the driver to obtain second-level hierarchical sampling data;
the third-level layering module is used for screening the second-level layered sampling data by using the independent route and the common route to obtain third-level layered sampling data;
and the weighted random sampling module is used for performing sample extraction on the third-level hierarchical sampling data through a first preset weighted random sampling method to obtain a test case data set based on user search behaviors.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the sample generation method for automated testing according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method for sample generation for automated testing according to any one of claims 1 to 7.
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