CN116954624B - Compiling method based on software development kit, software development system and server - Google Patents
Compiling method based on software development kit, software development system and server Download PDFInfo
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- 238000011161 development Methods 0.000 claims abstract description 66
- 238000004458 analytical method Methods 0.000 claims abstract description 58
- 230000002159 abnormal effect Effects 0.000 claims abstract description 15
- 238000013522 software testing Methods 0.000 claims abstract description 13
- 238000005259 measurement Methods 0.000 claims abstract description 9
- 238000012544 monitoring process Methods 0.000 claims abstract description 7
- 238000004891 communication Methods 0.000 claims abstract description 6
- 238000012549 training Methods 0.000 claims description 46
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/40—Transformation of program code
- G06F8/41—Compilation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The application belongs to the field of software development, and relates to a data analysis technology, in particular to a compiling method based on a software development kit, a software development system and a server, wherein the compiling method comprises a development platform which is in communication connection with a test analysis module, a defect analysis module, a feature analysis module and a storage module; the test analysis module is used for monitoring and analyzing the test process of the software development kit: marking a software development package to be tested as a test object, and acquiring time measurement data CS, memory data NC and functional data GN of the test object after the test object completes software testing; the application can monitor and analyze the testing process of the software development kit, comprehensively calculate and analyze a plurality of parameters in the testing process to obtain the efficiency coefficient, monitor the testing efficiency of the software development kit by combining the defect coefficient, timely feed back the testing efficiency when the testing efficiency is abnormal, and specially train the development personnel to improve the subsequent testing efficiency.
Description
Technical Field
The application belongs to the field of software development, relates to a data analysis technology, and in particular relates to a compiling method based on a software development kit, a software development system and a server.
Background
Software development is the process of building a software system or software parts of a system according to user requirements. Software development is a piece of system engineering including demand capture, demand analysis, design, implementation, and testing, and software is typically implemented in some programming language. Development is typically performed using software development tools, and software is divided into system software and application software, and is not limited to programs that can be executed on a computer, but files related to such programs are generally considered to be part of the software.
The existing software development system cannot monitor and analyze defect parameters and characteristics in the software testing process, so that the software testing efficiency cannot be improved, the development technology and operation habit of developers cannot be improved and optimized, and the operation efficiency of the software development system is low.
The application provides a solution to the technical problem.
Disclosure of Invention
The application aims to provide a compiling method based on a software development kit, a software development system and a server, which are used for solving the problem that the existing software development system cannot monitor and analyze defect parameters and characteristics in a software testing process;
the technical problems to be solved by the application are as follows: how to provide a compiling method based on a software development kit, which can monitor and analyze defect parameters and characteristics in a software testing process.
The aim of the application can be achieved by the following technical scheme:
the software development system based on the software development kit comprises a development platform, wherein the development platform is in communication connection with a test analysis module, a defect analysis module, a feature analysis module and a storage module;
the test analysis module is used for monitoring and analyzing the test process of the software development kit: marking a software development package to be tested as a test object, and acquiring time measurement data CS, memory data NC and functional data GN of the test object after the test object completes software testing; obtaining an efficiency coefficient XL of a test object by carrying out numerical calculation on time measurement data CS, memory data NC and functional data GN, and marking the ratio of the number of code lines of the test object to the number of BUGs monitored in the test process as a defect coefficient; judging whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient;
the defect analysis module is used for analyzing defects in the software development package testing process: judging whether a fatal error occurs in the test process of the test object: if yes, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager: if not, acquiring the serious data YZ, the general data YB and the optimized data YH of the test object in the test process, and performing numerical calculation to obtain a repair coefficient XF of the test object; judging whether the test passes or not through a repair coefficient XF;
the serious data YZ, the general data YB and the optimized data YH are respectively the times of serious faults, general faults and recommended optimization of the test object in the test process;
the feature analysis module is used for analyzing defect features in the testing process.
As a preferred implementation mode of the application, the time measurement data CS of the test object is the total time spent by the test object to complete the software test, the memory data NC is the total memory value of the test object, and the functional data GN is the number of functions to be tested of the test object.
As a preferred embodiment of the present application, the specific process for determining whether the test efficiency of the test object meets the requirement includes: obtaining an efficiency threshold XLmin and a defect threshold through a storage module, and comparing a defect coefficient and an efficiency coefficient XL of a test object with the defect threshold and the efficiency threshold XLmin respectively: if the defect coefficient is greater than or equal to the defect threshold value, judging that the test efficiency of the test object does not meet the requirement, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is smaller than the efficiency threshold value XLmin, judging that the test efficiency of the test object does not meet the requirement, generating a defect analysis signal and sending the defect analysis signal to a development platform, and after receiving the defect analysis signal, the development platform sends the defect analysis signal to a defect analysis module; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is larger than or equal to the efficiency threshold value XLmin, judging the efficiency requirement of the test result of the test object, generating a test qualified signal and sending the test qualified signal to the development platform.
As a preferred embodiment of the present application, a specific process of determining whether software test of a test object is passed or not includes: the restoration threshold value XFmax is obtained through the storage module, and the restoration coefficient XF is compared with the restoration threshold value XFmax: if the repair coefficient XF is smaller than the repair threshold XFmax, judging that the test is passed, generating a characteristic analysis signal and sending the characteristic analysis signal to a development platform, and sending the characteristic analysis signal to a characteristic analysis module after the development platform receives the characteristic analysis signal; if the repair coefficient XF is larger than or equal to the repair threshold XFmax, judging that the test is not passed, generating a defect abnormal signal and sending the defect abnormal signal to a development platform, and sending the defect abnormal signal to a mobile phone terminal of a manager after the development platform receives the defect abnormal signal.
As a preferred embodiment of the application, the specific process of analyzing the defect characteristics in the test process by the characteristic analysis module comprises the following steps: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a concentration coefficient, acquiring a concentration threshold by a storage module, and comparing the concentration coefficient with the concentration threshold: if the centralization coefficient is smaller than the centralization threshold value, generating a standard training signal and sending the standard training signal to a development platform, and after receiving the standard training signal, the development platform sends the standard training signal to a mobile phone terminal of a manager; if the concentration coefficient is greater than or equal to the concentration threshold, habit correction signals are generated and sent to a development platform, and after receiving the habit correction signals, the development platform sends the habit correction signals to a mobile phone terminal of a manager.
The compiling method based on the software development kit comprises the following steps:
step one: monitoring and analyzing the testing process of the software development kit: marking a software development package to be tested as a test object, acquiring an efficiency coefficient XL and a defect coefficient of the test object after the test object completes software testing, and judging whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient;
step two: analyzing defects in the software development package testing process: when the test object has no fatal error in the test process, acquiring serious data YZ, general data YB and optimized data YH of the test object in the test process, performing numerical calculation to obtain a repair coefficient XF, and judging whether software test is passed or not through the repair coefficient XF;
step three: analyzing the defect characteristics in the test process: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a centralized coefficient, generating habit correction signals or standard training signals through the centralized coefficient, and sending the habit correction signals or standard training signals to a development platform.
The server based on the software development kit comprises a processor, a machine-readable storage medium, a network interface and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one development terminal, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the machine-readable storage medium.
The application has the following beneficial effects:
the testing process of the software development kit can be monitored and analyzed through the testing and analyzing module, the efficiency coefficient is obtained through comprehensive calculation and analysis of a plurality of parameters in the testing process, the testing efficiency of the software development kit is monitored by combining the defect coefficient, feedback is timely carried out when the testing efficiency is abnormal, professional training is carried out on the development personnel, and the subsequent testing efficiency is improved;
the defect analysis module can analyze defects in the software development package testing process, each defect of the test object in the testing process is counted and analyzed to obtain a repair coefficient, whether the software test is passed or not is judged through the repair coefficient, and early warning and feedback are timely carried out when the irreparable defects exist;
the defect characteristics in the testing process can be analyzed through the characteristic analysis module, the collection is extracted through the extraction value component of the defect number, then the concentration coefficient of the extraction collection is obtained through a variance calculation mode, the defect characteristics are fed back according to the numerical value of the concentration coefficient, and accordingly the corresponding optimization signals can be generated through the defect characteristics, and the development habit of the developer is optimized.
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In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method according to a first embodiment of the application;
fig. 2 is a system block diagram of a second embodiment of the present application.
Detailed Description
The technical solutions of the present application will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Embodiment one: as shown in fig. 1, the compiling method based on the software development kit comprises the following steps:
step one: monitoring and analyzing the testing process of the software development kit: marking a software development package to be tested as a test object, acquiring an efficiency coefficient XL and a defect coefficient of the test object after the test object completes software testing, and judging whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient;
step two: analyzing defects in the software development package testing process: when the test object has no fatal error in the test process, acquiring serious data YZ, general data YB and optimized data YH of the test object in the test process, performing numerical calculation to obtain a repair coefficient XF, and judging whether software test is passed or not through the repair coefficient XF;
step three: analyzing the defect characteristics in the test process: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a centralized coefficient, generating habit correction signals or standard training signals through the centralized coefficient, and sending the habit correction signals or standard training signals to a development platform.
Embodiment two: as shown in fig. 2, the software development system based on the software development kit comprises a development platform, wherein the development platform is in communication connection with a test analysis module, a defect analysis module, a feature analysis module and a storage module.
The test analysis module is used for monitoring and analyzing the test process of the software development kit: marking a software development package to be tested as a test object, acquiring time measurement data CS, memory data NC and functional data GN of the test object after the test object completes software testing, wherein the time measurement data CS of the test object is the total time spent by the test object to complete software testing, the memory data NC is the total memory value of the test object, and the functional data GN is the number of functions to be tested of the test object; obtaining an efficiency coefficient XL of the test object through a formula XL= (alpha 1 x NC+alpha 2 x GN)/(alpha 3 x CS), wherein alpha 1, alpha 2 and alpha 3 are all proportional coefficients, alpha 1 > alpha 2 > alpha 3 > 1, and marking the ratio of the number of code lines of the test object to the number of BUGs monitored in the test process as a defect coefficient; obtaining an efficiency threshold XLmin and a defect threshold through a storage module, and comparing a defect coefficient and an efficiency coefficient XL of a test object with the defect threshold and the efficiency threshold XLmin respectively: if the defect coefficient is greater than or equal to the defect threshold value, judging that the test efficiency of the test object does not meet the requirement, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is smaller than the efficiency threshold value XLmin, judging that the test efficiency of the test object does not meet the requirement, generating a defect analysis signal and sending the defect analysis signal to a development platform, and after receiving the defect analysis signal, the development platform sends the defect analysis signal to a defect analysis module; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is larger than or equal to the efficiency threshold value XLmin, judging the efficiency requirement of the test result of the test object, generating a test qualified signal and sending the test qualified signal to the development platform; the testing process of the software development kit is monitored and analyzed, the efficiency coefficient is obtained by comprehensively calculating and analyzing a plurality of parameters in the testing process, the testing efficiency of the software development kit is monitored by combining the defect coefficient, feedback is timely carried out when the testing efficiency is abnormal, professional training is carried out on the development personnel, and the subsequent testing efficiency is improved.
The defect analysis module is used for analyzing defects in the software development package testing process: judging whether a fatal error occurs in the test process of the test object: if yes, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager: if not, acquiring the serious data YZ, the general data YB and the optimized data YH of the test object in the test process, wherein the serious data YZ, the general data YB and the optimized data YH are the times of serious faults, general faults and recommended optimization of the test object in the test process respectively, and obtaining a repair coefficient XF of the test object through a formula XF=β1xYZ+β2xYB+β3xYH, wherein β1, β2 and β3 are all proportional coefficients, and β1 > β2 > β3 > 1; the fatal errors comprise memory leakage, serious numerical calculation errors, easy system breakdown, serious discrepancy between function design and requirements, incapability of logging in the system, cyclic error reporting and incapability of normally logging out; the restoration threshold value XFmax is obtained through the storage module, and the restoration coefficient XF is compared with the restoration threshold value XFmax: if the repair coefficient XF is smaller than the repair threshold XFmax, judging that the test is passed, generating a characteristic analysis signal and sending the characteristic analysis signal to a development platform, and sending the characteristic analysis signal to a characteristic analysis module after the development platform receives the characteristic analysis signal; if the repair coefficient XF is larger than or equal to the repair threshold XFmax, judging that the test is not passed, generating a defect abnormal signal and sending the defect abnormal signal to a development platform, and sending the defect abnormal signal to a mobile phone terminal of a manager after the development platform receives the defect abnormal signal; analyzing defects in the software development package testing process, obtaining repair coefficients by counting and analyzing various defects of a test object in the testing process, judging whether software testing is passed or not by the repair coefficients, and timely performing early warning and feedback when unrepairable defects exist.
The feature analysis module is used for analyzing defect features in the test process: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a concentration coefficient, acquiring a concentration threshold by a storage module, and comparing the concentration coefficient with the concentration threshold: if the centralization coefficient is smaller than the centralization threshold value, generating a standard training signal and sending the standard training signal to a development platform, and after receiving the standard training signal, the development platform sends the standard training signal to a mobile phone terminal of a manager; if the concentration coefficient is greater than or equal to the concentration threshold, habit correction signals are generated and sent to a development platform, and after receiving the habit correction signals, the development platform sends the habit correction signals to a mobile phone terminal of a manager; analyzing the defect characteristics in the test process, extracting a set by an extraction value component of the defect number, obtaining a concentration coefficient of the extraction set by a variance calculation mode, feeding back the defect characteristics according to the numerical value of the concentration coefficient, and generating a corresponding optimization signal through the defect characteristics to optimize the development habit of the developer.
The server based on the software development kit comprises a processor, a machine-readable storage medium, a network interface and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one development terminal, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the machine-readable storage medium.
The software development system based on the software development kit marks the software development kit to be tested as a test object in operation, acquires an efficiency coefficient XL and a defect coefficient of the test object after the test object completes software test, and judges whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient; when the test object has no fatal error in the test process, acquiring serious data YZ, general data YB and optimized data YH of the test object in the test process, performing numerical calculation to obtain a repair coefficient XF, and judging whether software test is passed or not through the repair coefficient XF; extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a centralized coefficient, generating habit correction signals or standard training signals through the centralized coefficient, and sending the habit correction signals or standard training signals to a development platform.
The foregoing is merely illustrative of the structures of this application and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the application or from the scope of the application as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula xl= (α1×nc+α2×gn)/(α3×cs); collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding efficiency coefficient for each group of sample data; substituting the set efficiency coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 5.48, 3.25 and 2.17 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding efficiency coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the efficiency coefficient is in direct proportion to the value of the memory.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the application disclosed above are intended only to assist in the explanation of the application. The preferred embodiments are not intended to be exhaustive or to limit the application to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and the practical application, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and the full scope and equivalents thereof.
Claims (3)
1. The software development system based on the software development kit is characterized by comprising a development platform, wherein the development platform is in communication connection with a test analysis module, a defect analysis module, a feature analysis module and a storage module;
the test analysis module is used for monitoring and analyzing the test process of the software development kit: marking a software development package to be tested as a test object, and acquiring time measurement data CS, memory data NC and functional data GN of the test object after the test object completes software testing; obtaining an efficiency coefficient XL of a test object by carrying out numerical calculation on time measurement data CS, memory data NC and functional data GN, and marking the ratio of the number of code lines of the test object to the number of BUGs monitored in the test process as a defect coefficient; judging whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient;
the defect analysis module is used for analyzing defects in the software development package testing process: judging whether a fatal error occurs in the test process of the test object: if yes, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager: if not, acquiring the serious data YZ, the general data YB and the optimized data YH of the test object in the test process, and performing numerical calculation to obtain a repair coefficient XF of the test object; judging whether the test passes or not through a repair coefficient XF;
the serious data YZ, the general data YB and the optimized data YH are respectively the times of serious faults, general faults and recommended optimization of the test object in the test process;
the feature analysis module is used for analyzing defect features in the test process;
the time measurement data CS of the test object is the total time spent by the test object to finish software test, the memory data NC is the total memory value of the test object, and the functional data GN is the number of functions to be tested of the test object;
the specific process for judging whether the test efficiency of the test object meets the requirement comprises the following steps: obtaining an efficiency threshold XLmin and a defect threshold through a storage module, and comparing a defect coefficient and an efficiency coefficient XL of a test object with the defect threshold and the efficiency threshold XLmin respectively: if the defect coefficient is greater than or equal to the defect threshold value, judging that the test efficiency of the test object does not meet the requirement, generating a professional training signal and sending the professional training signal to a development platform, and after receiving the professional training signal, the development platform sends the professional training signal to a mobile phone terminal of a manager; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is smaller than the efficiency threshold value XLmin, judging that the test efficiency of the test object does not meet the requirement, generating a defect analysis signal and sending the defect analysis signal to a development platform, and after receiving the defect analysis signal, the development platform sends the defect analysis signal to a defect analysis module; if the defect coefficient is smaller than the defect threshold value and the efficiency coefficient XL is larger than or equal to the efficiency threshold value XLmin, judging the efficiency requirement of the test result of the test object, generating a test qualified signal and sending the test qualified signal to the development platform;
the specific process of judging whether the software test of the test object is passed or not includes: the restoration threshold value XFmax is obtained through the storage module, and the restoration coefficient XF is compared with the restoration threshold value XFmax: if the repair coefficient XF is smaller than the repair threshold XFmax, judging that the test is passed, generating a characteristic analysis signal and sending the characteristic analysis signal to a development platform, and sending the characteristic analysis signal to a characteristic analysis module after the development platform receives the characteristic analysis signal; if the repair coefficient XF is larger than or equal to the repair threshold XFmax, judging that the test is not passed, generating a defect abnormal signal and sending the defect abnormal signal to a development platform, and sending the defect abnormal signal to a mobile phone terminal of a manager after the development platform receives the defect abnormal signal;
the specific process of analyzing the defect characteristics in the test process by the characteristic analysis module comprises the following steps: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a concentration coefficient, acquiring a concentration threshold by a storage module, and comparing the concentration coefficient with the concentration threshold: if the centralization coefficient is smaller than the centralization threshold value, generating a standard training signal and sending the standard training signal to a development platform, and after receiving the standard training signal, the development platform sends the standard training signal to a mobile phone terminal of a manager; if the concentration coefficient is greater than or equal to the concentration threshold, habit correction signals are generated and sent to a development platform, and after receiving the habit correction signals, the development platform sends the habit correction signals to a mobile phone terminal of a manager.
2. A compiling method of a software development kit applied to the software development system based on the software development kit as claimed in claim 1, comprising the steps of:
step one: monitoring and analyzing the testing process of the software development kit: marking a software development package to be tested as a test object, acquiring an efficiency coefficient XL and a defect coefficient of the test object after the test object completes software testing, and judging whether the test efficiency of the test object meets the requirement or not through the efficiency coefficient XL and the defect coefficient;
step two: analyzing defects in the software development package testing process: when the test object has no fatal error in the test process, acquiring serious data YZ, general data YB and optimized data YH of the test object in the test process, performing numerical calculation to obtain a repair coefficient XF, and judging whether software test is passed or not through the repair coefficient XF;
step three: analyzing the defect characteristics in the test process: extracting the defect numbers of the test object in the test process, marking the extraction times of each defect number as the extraction value of the defect number, forming an extraction set by the extraction values of all the defect numbers, performing variance calculation on the extraction set to obtain a centralized coefficient, generating habit correction signals or standard training signals through the centralized coefficient, and sending the habit correction signals or standard training signals to a development platform.
3. A software development kit based server, comprising a processor, a machine-readable storage medium, the network interface and a network interface, the machine-readable storage medium, the network interface and the processor being connected by a bus system, the network interface being configured to be communicatively connected to at least one development terminal, the machine-readable storage medium being configured to store a program, instructions or code, and the processor being configured to execute the program, instructions or code in the machine-readable storage medium to perform the method of compiling a software development kit according to claim 2.
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