CN117349169A - Software orientation test method and system combined with Internet of things - Google Patents
Software orientation test method and system combined with Internet of things Download PDFInfo
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Abstract
The invention relates to the technical field of software testing, in particular to a software directional testing method and system combined with the Internet of things, comprising a control layer, a processing layer and an evaluation layer; the invention can carry out logic control on the network speed of the software operation application network, further drive each subprogram to operate in the software based on the logic control of the network speed, collect the operation result of the software subprogram in the network speed configuration state, and carry out distributed continuous analysis and evaluation on the software subprogram and the software by the collected data so as to achieve the aim of testing the software, thereby reflecting the operation robustness and feasibility of the software in the network configuration state.
Description
Technical Field
The invention relates to the technical field of software testing, in particular to a software directional testing method and system combined with the Internet of things.
Background
Software testing is understood to be a process used to facilitate the verification of the correctness, integrity, security, and quality of software. In other words, the software test is an audit or comparison process between the actual output and the expected output. Classical definitions of software testing are: and (3) operating the program under the specified conditions to find out program errors, measuring the quality of the software and evaluating whether the software can meet the design requirements.
The invention patent with application number 202111035101.9 discloses an embedded software testing system based on the Internet of things, which is characterized in that: the system comprises a data acquisition module, a prediction module, a deviation adjustment module, a model construction module and an output module; the data acquisition module is used for acquiring real-time data generated in each step in the embedded software testing process of the communication equipment: the prediction module is used for predicting the success rate of each step in the embedded software test process of the communication equipment: the deviation adjusting module is used for carrying out deviation adjustment on the predicted data in the testing process of the embedded software of the communication equipment so as to improve the accuracy of the predicted data; the model construction module is used for constructing a deviation correction model of the embedded software test prediction deviation value and adjusting the prediction data: the output module is used for finally outputting a new predicted value: the output end of the data acquisition module is connected with the input end of the prediction module: the output end of the prediction module is connected with the input end of the deviation adjusting module: the output end of the deviation adjusting module is connected with the input end of the model building module: the output end of the model building module is connected with the input end of the output module.
The application aims at solving the problems: the success rate prediction of each step of the embedded software test of the communication equipment is very important, so that the problem that the test failure loss caused by the existing factors is avoided, and the basic prediction is lacking in the prior art or the water product is difficult to achieve the desired effect is solved.
However, the current research and development software test tends to tend to the situation that the software has running logic integrity and rationality to moisten whether the BUG exists, and the robustness and feasibility of the software based on the running of each subprogram in the network connection state are easily ignored, so that the software has powerful functions and great use, and cannot be used well by users.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a software directional testing method and a system combined with the Internet of things, which solve the technical problems in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
in a first aspect, a software orientation test system combined with an internet of things comprises a control layer, a processing layer and an evaluation layer;
the method comprises the steps that the real-time configuration network speed of a software application network is regulated and controlled through a control layer, a software component subprogram is controlled to run in the control layer based on each network speed control regulation result, the running state of the subprogram under the configuration of each network speed control regulation result is recorded, a processing layer synchronously receives software subprogram running state recording data, the adaptability of each software subprogram is analyzed based on the software subprogram running state recording data, the comprehensive performance of the software is evaluated based on the software subprogram adaptability, and a subprogram with poor adaptability in the software is compared and output;
the processing layer comprises a receiving module and an analyzing module, wherein the receiving module is used for receiving the running state of the subprogram under each network speed control and regulation result recorded in the recording module, the analyzing module is used for traversing and reading the running state data of the subprogram under each network speed control and regulation result received by the receiving module, and the application of the running state data of the subprogram under each network speed control and regulation result analyzes the adaptability of each software subprogram;
the software subroutine adaptability analysis logic is expressed as:
wherein: psi is the software subroutine adaptability representation value; u is a set of application network speed adjustment results when the software subprogram drives to run;a starting point for the software subprogram based on the 1 st group network speed adjusting result k; />Adjusting the response time of the result k for the software subroutine based on the 1 st group network speed; m is the number of network speed adjusting gears; n is the total amount of subroutines in the software;
wherein said (k) 1 、k 2 、k 3 (v.) are respectively corresponding to kmin, Epsilon=0 when the software subroutine is not started up as a result of the configured net speed adjustment, and epsilon=1 otherwise.
Further, the control layer comprises a setting module, a matching module and a recording module, wherein the setting module is used for setting the number of network speed adjustment gears, the matching module is used for configuring corresponding network speeds under different network speed adjustment gears for the software subroutines, the control software subroutines are driven to run based on the different network speeds, and the recording module is used for receiving the driving running results of the control software subroutines in the matching module based on the different network speeds;
after the setting module sets the number of network speed adjusting gears, the network speed of the software application network is equally divided based on the number of network speed adjusting gears, so that the network speed difference values of two adjacent groups of network speed adjusting gears are equal, the matching logic of the network speed corresponding to the network speed adjusting gears in the matching module is that each software subprogram is matched with the network speed corresponding to all network speed adjusting gears, the recording module carries out distinguishing recording on the driving operation results of the software subprograms under different network speeds based on the software subprograms, and the operation result contents of the software subprograms comprise: whether the software subroutine is complete to start, software subroutine response time.
Furthermore, the number of network speed adjusting gear numbers set by the setting module is calculated by the following formula:
wherein: m is the number of network speed adjusting gears; n is the number of network speed adjusting gears to obtain an association set; m is m 1 The associated gear base number is obtained for the 1 st group; k (k) max Is the peak value of network speed; k (k) min Is a network speed valley; epsilon is the total amount of network threads; m is m 2 The associated gear base number is obtained for the group 2; ζ is software complexity; s is S size The memory size is occupied for the first installation of the software;
wherein, the result of M is rounded upwards, and the M is as follows 1 M 2 Respectively corresponding to network layer correlation and software layer correlation when the network speed adjustment gear number is calculated, m 1 M 2 Is initially set to m 1 ＝m 2 The number of network speed adjustment gears set in the setting module is calculated as above or manually set by a user at the system end, and after calculation, the number of network speed adjustment gears M is further calculated to correspond to the network speed of each network speed adjustment gear, and the calculation result of the network speed corresponding to the network speed adjustment gear is expressed as (k min 、
Further, the software complexity zeta is calculated based on the number of subprograms in the software, the value of the software complexity zeta is compliant, the larger the number of subprograms in the software is, the larger the value of the software complexity zeta is, the smaller the number of subprograms in the software is, the smaller the value of the software complexity zeta is, and the value of the software complexity zeta is set to be equal to or more than 0;
wherein, the software complexity ζ is calculated and logically expressed as:
wherein: η is the number of subroutines in the software; lambda (lambda) in Page jump logic in the software contained in the software; lambda (lambda) all All page jump logic contained in the software; f is the average frequency of use of the software relative to the population of software use; g is the download times counted by the background of the software management end.
Furthermore, after the software subroutine adaptability representation value psi is obtained, refinement processing is further performed, and the refinement result based on the software subroutine adaptability representation value psi is sent to the evaluation layer for the evaluation layer to evaluate the comprehensive performance of the software, and refinement logic of the software subroutine adaptability representation value psi is expressed as:
wherein: psi phi type ref Expressing the refinement result of the value psi for the software subroutine adaptability; l is the number of operational modes of the software subroutine; delta is the global weight of the software subroutine for software operation; the memory required by the v software subprogram when running;
wherein the software subroutine is operable in a manner comprising: voice control, gesture control and touch control, wherein the value of the weight delta is larger as the value of the compliance upsilon is larger; setting logic that the smaller the value of v is, the smaller the value of delta is.
Further, in the operation stage of the receiving module, when the operation state of the software subprogram is received in the recording module, the operation state data of the software subprogram is sequentially received based on the source software subprogram of the operation state of the software subprogram, so that the operation state data of the software subprogram received by the receiving module in each operation is derived from the same software subprogram;
wherein the software subprogram running state data is the running result of the software subprogram.
Further, the evaluation layer comprises a comprehensive evaluation module and a capturing module, wherein the comprehensive evaluation module is used for receiving the adaptive capacity refinement results of each software subprogram analyzed by the analysis module in the processing layer, comprehensively evaluating the adaptive capacity of the software based on the adaptive capacity refinement results of each software subprogram, and the capturing module is used for setting a decision threshold to be optimized, comparing the decision threshold to be optimized with the adaptive capacity refinement results of each software subprogram to obtain a software subprogram at the decision threshold to be optimized, and feeding the obtained software subprogram back to a system end user as an output target;
the software subroutines at the decision threshold to be optimized are software subroutines with poor adaptability.
Still further, the software adaptation performance evaluation logic is expressed as:
wherein: CP is a software adaptation performance representation value; q is a set of refinement results of the software subroutine adaptability representation value ψ; psi phi type ref1 Expressing the refinement result of the value psi for the group 1 software subroutine adaptability; delta 1 Running global weights for the group 1 software subroutines for the software; q 0 Representing the total amount of refinement results of the value ψ for the software subroutine adaptability;
wherein, the system end user evaluates the comprehensive adaptability of the software based on the software adaptability performance expression value CP.
Furthermore, the setting module is electrically connected with the matching module and the recording module through a medium, the recording module is electrically connected with the receiving module through a medium, the receiving module is electrically connected with the analyzing module through a medium, the analyzing module is electrically connected with the comprehensive evaluation module through a medium, and the comprehensive evaluation module is electrically connected with the receiving module through a medium;
the setting module is connected with the software application network in a wireless way, the network speed is set and controlled, and the matching module is connected with computer equipment loaded with software through the software application network, and controls all subroutines in the software.
In a second aspect, a method for directional testing of software in combination with the internet of things includes the steps of:
step 1: setting the real-time network speed of a software application network, and driving each subprogram of software to run based on the set real-time network speed;
step 11: a design stage of network real-time network setting logic;
step 2: recording the running result of each subprogram of the software in the set network real-time network speed state;
step 3: acquiring an operation result of each subprogram of the software in a real-time network speed state based on each network, and analyzing the adaptability of each subprogram of the software based on operation result data;
step 31: analyzing a logic configuration stage by software subroutine adaptability;
step 32: a software subroutine adaptability analysis result refinement stage;
step 4: receiving analysis results of software subroutine adaptability, and evaluating the comprehensive performance of the software based on the analysis results;
step 41: a setting stage of software comprehensive performance evaluation logic;
step 5: setting a judging threshold value, comparing the judging threshold value with a software subprogram adaptability analysis result, acquiring a software subprogram in the judging threshold value, taking the acquired software subprogram as an output target, and outputting to a user terminal.
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
1. the invention provides a software directional test system combining with the Internet of things, which can carry out logic control on the network speed of a software operation application network in the operation process, further drive each subprogram in the software to operate based on the logic control of the network speed, collect the operation result of the software subprogram in each network speed configuration state, and carry out distributed continuous analysis and evaluation on the software subprogram and the software by the collected data so as to achieve the aim of testing the software, thereby reflecting the operation robustness and feasibility of the software in the network configuration state, ensuring the software tested by the mode, and ensuring better software use experience when being used by users.
2. In the running process of the system, the data are acquired through setting the network speed gear and performing matching control running with all subroutines of the software, so that the acquired data are more comprehensive, the accuracy of the running output result of the method is better, and subroutines with optimization requirements in the software are synchronously output in the running result output stage of the system, so that software development users can further upgrade the software.
3. The invention provides a software directional testing method combined with the Internet of things, which can further maintain the stability of system operation by executing steps in the method, provides more comprehensive operation logic for the system operation in the executing process of the steps of the method, and ensures that a technical scheme consisting of the system and the method brings more stable testing effect for software testing in a specific implementation stage.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a software orientation test system incorporating the Internet of things;
FIG. 2 is a flow chart of a software orientation test method combined with the Internet of things;
fig. 3 is a schematic diagram of a matching result between a network speed corresponding to each network speed adjustment gear and a software subroutine in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Example 1
The software orientation test system combined with the internet of things in the embodiment, as shown in fig. 1, comprises a control layer, a processing layer and an evaluation layer;
the method comprises the steps that the real-time configuration network speed of a software application network is regulated and controlled through a control layer, a software component subprogram is controlled to run in the control layer based on each network speed control regulation result, the running state of the subprogram under the configuration of each network speed control regulation result is recorded, a processing layer synchronously receives software subprogram running state recording data, the adaptability of each software subprogram is analyzed based on the software subprogram running state recording data, the comprehensive performance of the software is evaluated based on the software subprogram adaptability, and a subprogram with poor adaptability in the software is compared and output;
the processing layer comprises a receiving module and an analyzing module, wherein the receiving module is used for receiving the running state of the subprogram under each network speed control and regulation result recorded in the recording module, the analyzing module is used for traversing and reading the running state data of the subprogram under each network speed control and regulation result received by the receiving module, and the application of the running state data of the subprogram under each network speed control and regulation result analyzes the adaptability of each software subprogram;
the software subroutine adaptability analysis logic is expressed as:
wherein: psi is the software subroutine adaptability representation value; u is a set of application network speed adjustment results when the software subprogram drives to run;a starting point for the software subprogram based on the 1 st group network speed adjusting result k; />Adjusting the response time of the result k for the software subroutine based on the 1 st group network speed; m is the number of network speed adjusting gears; n is the total amount of subroutines in the software;
wherein, (k) 1 、k 2 、k 3 (v.) are respectively corresponding to kmin, Epsilon=0 when the software subroutine is not started under the configured net speed regulation result, and epsilon=1 otherwise;
the control layer comprises a setting module, a matching module and a recording module, wherein the setting module is used for setting the number of network speed adjustment gears, the matching module is used for configuring corresponding network speeds under different network speed adjustment gears for the software subroutines, the control software subroutines are driven to run based on the different network speeds, and the recording module is used for receiving the driving running results of the control software subroutines in the matching module based on the different network speeds;
after the setting module sets the number of network speed adjusting gears, the network speed of the software application network is equally divided based on the number of network speed adjusting gears, so that the network speed difference values of two adjacent groups of network speed adjusting gears are equal, the matching logic of the network speed corresponding to the network speed adjusting gears in the matching module is that each software subprogram is matched with the network speed corresponding to all network speed adjusting gears, and the recording module carries out distinguishing recording on the driving operation results of the software subprograms under different network speeds based on the software subprograms, wherein the operation result contents of the software subprograms comprise: whether the software subprogram is started or not, and the response time of the software subprogram;
the evaluation layer comprises a comprehensive evaluation module and a capturing module, wherein the comprehensive evaluation module is used for receiving the adaptive capacity refinement results of all software subroutines analyzed by the analysis module in the processing layer, comprehensively evaluating the adaptive capacity of the software based on the adaptive capacity refinement results of all software subroutines, and the capturing module is used for setting a to-be-optimized judgment threshold value, comparing the to-be-optimized judgment threshold value with the adaptive capacity refinement results of all software subroutines to obtain a software subroutine at the to-be-optimized judgment threshold value, and feeding back the obtained software subroutine as an output target to a system end user;
the software subprogram which is positioned at the judging threshold value to be optimized, namely the software subprogram with poor adaptability;
the software adaptation performance evaluation logic is expressed as:
wherein: CP is a software adaptation performance representation value; q is a set of refinement results of the software subroutine adaptability representation value ψ; psi phi type ref1 Expressing the refinement result of the value psi for the group 1 software subroutine adaptability; delta 1 Running global weights for the group 1 software subroutines for the software; q 0 Representing the total amount of refinement results of the value ψ for the software subroutine adaptability;
the system end user evaluates the comprehensive adaptability of the software based on the software adaptability performance representation value CP;
the setting module is electrically connected with the matching module and the recording module through a medium, the recording module is electrically connected with the receiving module through a medium, the receiving module is electrically connected with the analyzing module through a medium, the analyzing module is electrically connected with the comprehensive evaluation module through a medium, and the comprehensive evaluation module is electrically connected with the capturing module through a medium;
the setting module is connected with the software application network in a wireless way, the network speed is set and controlled, and the matching module is connected with computer equipment loaded with software through the software application network, and controls all subroutines in the software.
In this embodiment, the setting module operates to set the number of network speed adjustment gears, the matching module synchronously operates as software subroutines to configure corresponding network speeds under different network speed adjustment gears, the control software subroutines operate based on different configuration network speed driving, the recording module post-operates to receive control software subroutines in the matching module based on different configuration network speed driving operation results, the receiving module further receives the running state of each subroutine under the network speed control adjustment results recorded in the recording module, the analysis module traverses and reads the running state data of each subroutine under the network speed control adjustment results received by the receiving module, the adaptive capacity of each software subroutine is analyzed by applying the running state data of each subroutine under each network speed control adjustment result, finally the comprehensive evaluation module receives the adaptive capacity refinement results of each software subroutine analyzed by the processing layer, the adaptive capacity refinement results of each software subroutine are comprehensively evaluated, the capturing module operates to set a decision threshold to be optimized, the software subroutines are compared with the adaptive capacity refinement results of each software subroutines based on the decision threshold to be optimized, and the obtained software subroutines are fed back to the user terminal as target software subroutines.
The software subroutine adaptability analysis logic is limited by the formula, the software adaptability evaluation logic is limited, necessary data support is further provided for the operation of subsequent modules of the system, and the data reference of the system end user is provided in the digitalized output mode, so that the system end user can obtain more definite data, and the software is further optimized and improved.
Referring to FIG. 3, the test logic for the software subroutine in the system is further illustrated by the configuration of the network speed to software subroutine connection in FIG. 3.
Example 2
On the aspect of implementation, based on embodiment 1, this embodiment further specifically describes, with reference to fig. 1, a software orientation test system for the internet of things in embodiment 1:
the network speed adjusting gear number set by the setting module is calculated by the following formula:
wherein: m is the number of network speed adjusting gears; n is the number of network speed adjusting gears to obtain an association set; m is m 1 The associated gear base number is obtained for the 1 st group; k (k) max Is the peak value of network speed; k (k) min Is a network speed valley; epsilon is the total amount of network threads; m is m 2 The associated gear base number is obtained for the group 2; ζ is software complexity; s is S size The memory size is occupied for the first installation of the software;
wherein, the result of M is rounded up, M 1 M 2 Respectively corresponding to network layer correlation and software layer correlation when the network speed adjustment gear number is calculated, m 1 M 2 Is initially set to m 1 ＝m 2 The number of network speed adjustment gears set in the setting module is calculated as above or manually set by a user at the system end, and after calculation, the number of network speed adjustment gears M is further calculated to correspond to the network speed of each network speed adjustment gear, and the calculation result of the network speed corresponding to the network speed adjustment gear is expressed as (k min 、
The software complexity zeta is calculated based on the number of subprograms in the software, the value of the software complexity zeta is compliant, the larger the number of subprograms in the software is, the larger the value of the software complexity zeta is, the smaller the number of subprograms in the software is, the smaller the value of the software complexity zeta is, and the value of the software complexity zeta is set to be logic, wherein zeta is more than or equal to 0;
wherein, the software complexity ζ is calculated and logically expressed as:
wherein: η is the number of subroutines in the software; lambda (lambda) in Page jump logic in the software contained in the software; lambda (lambda) all All page jump logic contained in the software; f is the average frequency of use of the software relative to the population of software use; g is the download times counted by the background of the software management end.
Through the calculation of the formula, the network speed adjusting gear number configured for the software subprogram in the setting module is logically limited, so that the software subprogram is ensured to obtain stable test conditions, and the system operation can control the test precision of the software, thereby being convenient for a system end user to use.
Example 3
On the aspect of implementation, based on embodiment 1, this embodiment further specifically describes, with reference to fig. 1, a software orientation test system for the internet of things in embodiment 1:
after the software subroutine adaptability expression value psi is obtained, further carrying out refinement processing, and sending the refinement result based on the software subroutine adaptability expression value psi to an evaluation layer for the evaluation layer to evaluate the comprehensive performance of the software, wherein refinement logic of the software subroutine adaptability expression value psi is expressed as:
wherein: psi phi type ref Expressing the refinement result of the value psi for the software subroutine adaptability; l is the number of operational modes of the software subroutine; delta is the global weight of the software subroutine for software operation; the memory required by the v software subprogram when running;
wherein the software subroutine is operable in a manner comprising: voice control, gesture control and touch control, wherein the value of the weight delta is larger as the value of the compliance upsilon is larger; setting logic that the smaller the value of v is, the smaller the value of delta is.
Through the calculation of the formula, the software subroutine adaptability expression value psi is further refined, so that the system operation precision is further improved.
As shown in fig. 1, in the operation stage of the receiving module, when the operation state of the software subprogram is received in the recording module, the operation state data of the software subprogram is sequentially received based on the source software subprogram of the operation state of the software subprogram, so that the operation state data of the software subprogram received by each operation of the receiving module is derived from the same software subprogram;
wherein the software subprogram running state data is the running result of the software subprogram.
Through the arrangement, the operation logic limitation of the receiving module in the processing layer is further provided, so that the system operation is more logical, and the purpose of improving the system operation stability is achieved.
Example 4
On the aspect of implementation, based on embodiment 1, this embodiment further specifically describes, with reference to fig. 2, a software orientation test system for the internet of things in embodiment 1:
the software orientation test method combined with the Internet of things comprises the following steps of:
step 1: setting the real-time network speed of a software application network, and driving each subprogram of software to run based on the set real-time network speed;
step 11: a design stage of network real-time network setting logic;
step 2: recording the running result of each subprogram of the software in the set network real-time network speed state;
step 3: acquiring an operation result of each subprogram of the software in a real-time network speed state based on each network, and analyzing the adaptability of each subprogram of the software based on operation result data;
step 31: analyzing a logic configuration stage by software subroutine adaptability;
step 32: a software subroutine adaptability analysis result refinement stage;
step 4: receiving analysis results of software subroutine adaptability, and evaluating the comprehensive performance of the software based on the analysis results;
step 41: a setting stage of software comprehensive performance evaluation logic;
step 5: setting a judging threshold value, comparing the judging threshold value with a software subprogram adaptability analysis result, acquiring a software subprogram in the judging threshold value, taking the acquired software subprogram as an output target, and outputting to a user terminal.
In summary, in the above embodiment, the system can perform logic control on the network speed of the software running application network in the running process, further drive each subroutine in the software to run based on the logic control of the network speed, collect the running result of the software subroutines in the network speed configuration state, and perform distributed continuous analysis and evaluation on the software subroutines and the software itself according to the collected data so as to achieve the purpose of testing the software, thereby reflecting the running robustness and feasibility of the software in the network configuration state, and ensuring that the software tested in this way has better software use experience when being used by users; in the running process of the system, the data are acquired through setting the network speed gear and performing matching control operation with all subroutines of the software, so that the acquired data are more comprehensive, the accuracy of a running output result of the method is better, and subroutines with optimization requirements in the software are synchronously output in the running result output stage of the system, so that software development users can further upgrade the software; meanwhile, the method provided by the embodiment can further maintain the stability of the system operation, provides more comprehensive operation logic for the system operation in the step execution process of the method, ensures that the technical scheme consisting of the system and the method brings more stable test effect for the software test in the specific implementation stage.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The software directional test system combined with the Internet of things is characterized by comprising a control layer, a processing layer and an evaluation layer;
the method comprises the steps that the real-time configuration network speed of a software application network is regulated and controlled through a control layer, a software component subprogram is controlled to run in the control layer based on each network speed control regulation result, the running state of the subprogram under the configuration of each network speed control regulation result is recorded, a processing layer synchronously receives software subprogram running state recording data, the adaptability of each software subprogram is analyzed based on the software subprogram running state recording data, the comprehensive performance of the software is evaluated based on the software subprogram adaptability, and a subprogram with poor adaptability in the software is compared and output;
the processing layer comprises a receiving module and an analyzing module, wherein the receiving module is used for receiving the running state of the subprogram under each network speed control and regulation result recorded in the recording module, the analyzing module is used for traversing and reading the running state data of the subprogram under each network speed control and regulation result received by the receiving module, and the application of the running state data of the subprogram under each network speed control and regulation result analyzes the adaptability of each software subprogram;
the software subroutine adaptability analysis logic is expressed as:
wherein: psi is the software subroutine adaptability representation value; u is a set of application network speed adjustment results when the software subprogram drives to run;a starting point for the software subprogram based on the 1 st group network speed adjusting result k; />Adjusting the response time of the result k for the software subroutine based on the 1 st group network speed; m is the number of network speed adjusting gears; n is the total amount of subroutines in the software;
wherein said (k) 1 、k 2 、k 3 A.) correspond respectively to Epsilon=0 when the software subroutine is not started up as a result of the configured net speed adjustment, and epsilon=1 otherwise.
2. The system for directional testing of software combined with internet of things according to claim 1, wherein the control layer comprises a setting module, a matching module and a recording module, the setting module is used for setting the number of network speed adjusting gears, the matching module is used for configuring corresponding network speeds under different network speed adjusting gears for the software subprogram, the control software subprogram is driven to run based on different configuration network speeds, and the recording module is used for receiving the driving running result of the control software subprogram in the matching module based on different configuration network speeds;
after the setting module sets the number of network speed adjusting gears, the network speed of the software application network is equally divided based on the number of network speed adjusting gears, so that the network speed difference values of two adjacent groups of network speed adjusting gears are equal, the matching logic of the network speed corresponding to the network speed adjusting gears in the matching module is that each software subprogram is matched with the network speed corresponding to all network speed adjusting gears, the recording module carries out distinguishing recording on the driving operation results of the software subprograms under different network speeds based on the software subprograms, and the operation result contents of the software subprograms comprise: whether the software subroutine is complete to start, software subroutine response time.
3. The system for directional testing of software combined with internet of things according to claim 2, wherein the number of network speed adjusting gears set by the setting module is calculated by the following formula:
wherein: m is the number of network speed adjusting gears; n is the number of network speed adjusting gears to obtain an association set; m is m 1 The associated gear base number is obtained for the 1 st group; k (k) max Is the peak value of network speed; k (k) min Is a network speed valley; epsilon is the total amount of network threads; m is m 2 The associated gear base number is obtained for the group 2; ζ is software complexity; s is S size The memory size is occupied for the first installation of the software;
wherein, the result of M is rounded upwards, and the M is as follows 1 M 2 Respectively corresponding to network layer correlation and software layer correlation when the network speed adjustment gear number is calculated, m 1 M 2 Is initially set to m 1 ＝m 2 The number of network speed adjusting gears set in the setting module is calculated as above or manually set by a user at the system end, and after the calculation, the number of network speed adjusting gears M is calculated, the network speed corresponding to each network speed adjusting gear is further calculated, and the calculation result of the network speed corresponding to the network speed adjusting gear is expressed as
4. The system for directional testing of software combined with the internet of things according to claim 3, wherein the software complexity ζ is calculated based on the number of subroutines in the software, the value of the software complexity ζ is obeyed, the more the number of subroutines in the software is, the larger the value of the software complexity ζ is, the fewer the number of subroutines in the software is, the smaller the value of the software complexity ζ is, and the ζ is more than or equal to 0;
wherein, the software complexity ζ is calculated and logically expressed as:
wherein: η is the number of subroutines in the software; lambda (lambda) in Page jump logic in the software contained in the software; lambda (lambda) all All page jump logic contained in the software; f is the average frequency of use of the software relative to the population of software use; g is the download times counted by the background of the software management end.
5. The system for directional testing of internet of things-based software according to claim 1, wherein after the software subroutine adaptability expression value ψ is obtained, refinement processing is further performed, and refinement results based on the software subroutine adaptability expression value ψ are sent to the evaluation layer for the evaluation layer to evaluate the comprehensive performance of the software, and refinement logic of the software subroutine adaptability expression value ψ is expressed as:
wherein: psi phi type ref Expressing the refinement result of the value psi for the software subroutine adaptability; l is the number of operational modes of the software subroutine; delta is the global weight of the software subroutine for software operation; the memory required by the v software subprogram when running;
wherein the software subroutine is operable in a manner comprising: voice control, gesture control and touch control, wherein the value of the weight delta is larger as the value of the compliance upsilon is larger; setting logic that the smaller the value of v is, the smaller the value of delta is.
6. The system according to claim 1, wherein the receiving module is configured to sequentially receive the running state data of the software subroutines based on the source software subroutines of the running states of the software subroutines when the running states of the software subroutines are received in the recording module, so that the running state data of the software subroutines received by the receiving module each time are derived from the same software subroutines;
wherein the software subprogram running state data is the running result of the software subprogram.
7. The system for directional testing of software combined with internet of things according to claim 1, wherein the evaluation layer comprises a comprehensive evaluation module and a capturing module, the comprehensive evaluation module is used for receiving the adaptive capacity refinement results of each software subprogram analyzed by the analysis module in the processing layer, comprehensively evaluating the adaptive performance of the software based on the adaptive capacity refinement results of each software subprogram, the capturing module is used for setting a decision threshold to be optimized, comparing the decision threshold to be optimized with the adaptive capacity refinement results of each software subprogram, acquiring the software subprogram at the decision threshold to be optimized, and feeding back the acquired software subprogram as an output target to a user at a system end;
the software subroutines at the decision threshold to be optimized are software subroutines with poor adaptability.
8. The internet of things-based software targeted test system of claim 7, wherein said software adaptation performance evaluation logic is expressed as:
wherein: CP is a software adaptation performance representation value; q is a set of refinement results of the software subroutine adaptability representation value ψ; psi phi type ref1 Expressing the refinement result of the value psi for the group 1 software subroutine adaptability; delta 1 Running global weights for the group 1 software subroutines for the software; q 0 Refinement results for software subroutine adaptation capability representation values ψIs a total amount of (2);
wherein, the system end user evaluates the comprehensive adaptability of the software based on the software adaptability performance expression value CP.
9. The system for directional testing of software in combination with internet of things according to claim 2, wherein the setting module is electrically connected with the matching module and the recording module through a medium, the recording module is electrically connected with the receiving module through a medium, the receiving module is electrically connected with the analyzing module through a medium, the analyzing module is electrically connected with the comprehensive evaluation module through a medium, and the comprehensive evaluation module is electrically connected with the capturing module through a medium;
the setting module is connected with the software application network in a wireless way, the network speed is set and controlled, and the matching module is connected with computer equipment loaded with software through the software application network, and controls all subroutines in the software.
10. A method for implementing the software orientation test system combined with the internet of things according to any one of claims 1 to 9, which is characterized by comprising the following steps:
step 1: setting the real-time network speed of a software application network, and driving each subprogram of software to run based on the set real-time network speed;
step 11: a design stage of network real-time network setting logic;
step 2: recording the running result of each subprogram of the software in the set network real-time network speed state;
step 3: acquiring an operation result of each subprogram of the software in a real-time network speed state based on each network, and analyzing the adaptability of each subprogram of the software based on operation result data;
step 31: analyzing a logic configuration stage by software subroutine adaptability;
step 32: a software subroutine adaptability analysis result refinement stage;
step 4: receiving analysis results of software subroutine adaptability, and evaluating the comprehensive performance of the software based on the analysis results;
step 41: a setting stage of software comprehensive performance evaluation logic;
step 5: setting a judging threshold value, comparing the judging threshold value with a software subprogram adaptability analysis result, acquiring a software subprogram in the judging threshold value, taking the acquired software subprogram as an output target, and outputting to a user terminal.
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