CN117196394A - Evaluation index processing method, device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to an evaluation index processing method, an evaluation index processing device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index; acquiring a target keyword of a target software development project; determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword; and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index. The method can achieve the effect of improving the accuracy of the evaluation index aiming at the software development project.
Description
Technical Field
The present application relates to the field of computer technology, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for processing an evaluation index.
Background
With the expansion of the size of software projects and the complexity of requirements, the selection and management of quality operation indexes becomes more and more important.
In the traditional technology, the evaluation index related to the software development project is selected by relying on manual experience.
However, the operation indexes selected by the traditional measurement index selection method are often inaccurate, and cannot effectively guide the development flow of optimized software.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an evaluation index processing method, apparatus, computer device, computer-readable storage medium, and computer program product capable of improving the accuracy of an evaluation index.
In a first aspect, the present application provides an evaluation index processing method, including:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
Acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In one embodiment, determining a target evaluation index corresponding to a target keyword from a mapping relationship between the evaluation index and the keyword includes:
traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes;
calculating the information entropy of each candidate evaluation index;
calculating information utility values of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility values to determine entropy weights of the candidate evaluation indexes;
calculating the distinguishing degree of candidate evaluation indexes according to the information entropy and the entropy weight;
and selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
In one embodiment, the mapping relationship between the evaluation index and the keyword is pre-constructed according to the occurrence times of the keyword and the evaluation index, and includes:
traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index;
Selecting a historical evaluation index with occurrence times larger than a threshold value;
and correlating the keywords with the historical evaluation indexes with occurrence times larger than the threshold value to generate a mapping relation between the evaluation indexes and the keywords.
In one embodiment, after determining the target evaluation index set corresponding to the target software development project based on the target evaluation index, the method further includes:
acquiring a current state value corresponding to each target evaluation index in the target evaluation index set from the current data;
and comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
In one embodiment, the method further comprises: and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
In one embodiment, the method further comprises:
constructing an objective function based on the objective evaluation index set, and acquiring initial data;
inputting initial data into an objective function to obtain an objective function value;
when the objective function value is smaller than the threshold value, the numerical value of each objective evaluation index in the objective evaluation index set is adjusted to obtain new initial data, the step of inputting the initial data into the objective function to obtain the objective function value is carried out, and the step is finished until the objective function value is larger than or equal to the threshold value.
In a second aspect, the present application also provides an evaluation index processing apparatus, including:
the construction module is used for constructing an evaluation index set aiming at the software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
the acquisition module is used for acquiring target keywords of the target software development project;
the selecting module is used for determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
the determining module determines a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
Acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In a fifth aspect, the application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
The above-described evaluation index processing method, apparatus, computer device, storage medium, and computer program product are provided by constructing an evaluation index set including at least one evaluation index for a software development project; acquiring a target keyword of a target software development project; and then, determining a target evaluation index corresponding to the target keyword based on a mapping relation between the evaluation index and the keyword, and finally, determining a target evaluation index set corresponding to a target software development project based on the target evaluation index, wherein the evaluation index matched with the project keyword is selected through the project keyword, so that the evaluation index and the software development project are more matched, the effect of improving the adaptation degree of the evaluation index and the software development project can be realized, and the accuracy of the evaluation index is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.
FIG. 1 is a diagram of an application environment for an evaluation index processing method in one embodiment;
FIG. 2 is a flow chart of a method for processing an evaluation index according to an embodiment;
FIG. 3 is a flow chart of determining a target evaluation index corresponding to a target keyword from a mapping relationship between the evaluation index and the keyword in one embodiment;
FIG. 4 is a schematic flow chart of mapping relationship construction between evaluation indexes and keywords in one embodiment;
FIG. 5 is a flow chart illustrating a process after determining a target evaluation index set corresponding to a target software development project based on target evaluation indexes in one embodiment;
FIG. 6 is a flowchart of a method for processing an evaluation index according to another embodiment;
FIG. 7 is a block diagram showing a configuration of an evaluation index processing apparatus in one embodiment;
Fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The evaluation index processing method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The server 104 builds an evaluation index set for the software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index; acquiring a target keyword of a target software development project; determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword; and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In an exemplary embodiment, as shown in fig. 2, an evaluation index method is provided, and an example of application of the method to the server in fig. 1 is described, including the following steps S202 to S206. Wherein:
step S202, constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related index, the demand related index, the test related index, the release related index, the service line quality related index and the quality related index of each equipment end respectively comprise at least one evaluation index.
Among them, the software development project is a temporary work performed to deliver unique software results. Management of the software development project comprises project planning, measurement and monitoring, configuration management, quality assurance and the like, and in order to effectively optimize the software development project flow and improve the software project delivery quality, the software development project needs to be evaluated through evaluation indexes. The evaluation index set is a set of evaluation indexes, and comprises process indexes and quality indexes, wherein the process indexes comprise research and development related indexes, demand related indexes, test related indexes and release related indexes; the quality index comprises a service line quality related index and quality related indexes of all equipment ends.
Optionally, the server collects a plurality of evaluation indexes for different software development projects; the evaluation index can be a process index or a quality index; the process indexes can be research and development related indexes, demand related indexes, test related indexes and release related indexes, and concretely can be code coverage rate, smoking execution rate, demand change rate, demand on-time delivery rate, smoking case coverage rate, release rollback rate and the like; the quality index can be a service line quality related index and a quality related index of each equipment end; forming an evaluation index set according to the collected multiple evaluation indexes; the evaluation index set is not an empty set.
Step S204, obtaining target keywords of the target software development project.
Wherein the keywords are fields that can characterize the business characteristics of the target software development project. Keywords may be Web applications, mobile applications, desktop applications; but also a program flow.
Optionally, before the server obtains the target keyword of the target software development project, the server invokes a pre-deployed keyword template from the database, and then adjusts the keyword template according to the business characteristics of the target software development project and the user requirements to obtain the target keyword.
Step S206, determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword.
Wherein, the mapping relation between the evaluation index and the keywords is pre-constructed.
Optionally, the server determines the target evaluation index corresponding to the target keyword according to the obtained target keyword of the target software development project and through the mapping relation between the pre-constructed evaluation index and the keyword. For example, the server determines at least one evaluation index corresponding to different target keywords according to the obtained 5 target keywords of the target software development project through the mapping relation between the evaluation indexes and the keywords, and performs union calculation on at least one evaluation index corresponding to different 5 target keywords to obtain target evaluation indexes.
Step S208, a target evaluation index set corresponding to the target software development project is determined based on the target evaluation index.
Optionally, the server selects target evaluation indexes according to the mapping relation, gathers the target evaluation indexes, and determines a target evaluation index set corresponding to the target software development project.
In the evaluation index processing method, the evaluation index set is constructed aiming at the software development project, the evaluation index set comprises at least one evaluation index, the target keywords of the target software development project are obtained, then the target evaluation indexes corresponding to the target keywords are determined based on the mapping relation between the evaluation indexes and the keywords, finally the target evaluation index set corresponding to the target software development project is determined based on the target evaluation indexes, and the evaluation indexes matched with the project keywords are selected through the project keywords and are matched with each other, so that the effect of improving the adaptation degree of the evaluation indexes and the software development project can be achieved, and the accuracy of the evaluation indexes is improved.
In an exemplary embodiment, as shown in fig. 3, a target evaluation index corresponding to a target keyword is determined from a mapping relationship between the evaluation index and the keyword, including steps S302 to S306.
Wherein:
and step S302, traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes.
Optionally, the mapping relation table records a plurality of mapping relations; and traversing the mapping relation in the mapping relation table according to the obtained target keyword by the server to obtain a candidate evaluation index. For example, the target keyword is development efficiency, the server traverses a mapping relation related to development efficiency, and candidate evaluation indexes such as task completion rate, average task completion rate, defect resolution rate, code submission frequency and the like are obtained through the mapping relation.
Step S304, calculating the information entropy of each candidate evaluation index.
The information entropy is used for solving the quantization problem of information, and the originally blurred information concept is calculated to obtain an accurate information entropy value, wherein the information entropy is a value for describing uncertainty in the message.
Optionally, the server calculates the information entropy of each candidate index; the formula for calculating the candidate evaluation index is as follows: Wherein m is the number of indexes, P i The candidate evaluation index is used as the probability of the random event.
And step S306, calculating information utility values of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility values to determine entropy weights of the candidate evaluation indexes.
Wherein the information utility value of an index depends on the difference between the information entropy of the index and 1, and its value directly affects the magnitude of the weight. The greater the information utility value, the greater the importance to the assessment and the greater the weight. The information utility value is also called the difference coefficient.
Optionally, the server calculates an information utility value according to the information entropy of each candidate evaluation index, and the calculation formula is as follows: di=1-Ei; ei is the information entropy of the candidate evaluation index; the server normalizes the information utility value of each candidate evaluation index, so as to calculate the entropy weight of each candidate evaluation index; the entropy weight wi calculation formula of the candidate evaluation index is as follows:
wherein m is the number of indexes, and Ei is the information entropy of candidate evaluation indexes.
And step S308, calculating the distinguishing degree of the candidate evaluation indexes according to the information entropy and the entropy weight.
The degree of distinction refers to the degree of distinction between the corresponding substantial differences of the evaluation objects.
Optionally, the server calculates the degree of distinction of the candidate evaluation indexes according to the information entropy and the entropy weight of each candidate evaluation index. The calculation formula of the distinguishing degree xi of the candidate evaluation index is as follows:
wherein m is the number of indexes; wi is the entropy weight of the candidate evaluation index; ei is the information entropy of the candidate evaluation index.
And step S310, selecting candidate evaluation indexes with differentiation degree higher than a threshold value to obtain target evaluation indexes.
Optionally, the server selects candidate evaluation indexes with the discrimination degree higher than a threshold value, deletes candidate indexes with the discrimination degree lower than or equal to the discrimination degree to obtain a target evaluation index, wherein the threshold value can be adjusted according to actual conditions.
In this embodiment, the candidate evaluation indexes are selected by traversing the mapping relationship, and then the candidate evaluation indexes are screened, so that the target evaluation indexes can be more suitable for the characteristics of the software development project.
In an exemplary embodiment, as shown in fig. 4, the mapping relationship between the evaluation index and the keyword is pre-constructed according to the number of occurrences of the keyword and the evaluation index, including steps S402 to S406.
Wherein:
step S402, traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index.
Optionally, the server traverses each historical evaluation index of the software development project based on the keywords, and counts the occurrence times of each historical evaluation index.
Step S404, selecting a history evaluation index with occurrence times larger than a threshold value.
Optionally, the server selects a historical evaluation index with occurrence times greater than a preset threshold, and the threshold can be adjusted according to actual conditions, which is not limited herein.
Step S406, the keywords are associated with the historical evaluation indexes with the occurrence times larger than the threshold value, and the mapping relation between the evaluation indexes and the keywords is generated.
Optionally, the server keywords are associated with historical evaluation indexes with occurrence times larger than a threshold value, and a mapping relation between the evaluation indexes and the keywords is generated. If the keyword is development efficiency, the historical evaluation indexes with occurrence times larger than a threshold value respectively have task completion rate and average task completion rate; and establishing an association relation between the keywords 'development efficiency' and 'task completion rate' and 'average task completion rate', thereby generating a mapping relation.
In this embodiment, the mapping relationship between the evaluation index and the keyword can be generated by counting the number of occurrences of the keyword and the history evaluation index.
In an exemplary embodiment, as shown in fig. 5, after determining the target evaluation index set corresponding to the target software development project based on the target evaluation index, steps S502 to S504 are further included. Wherein:
step S502, obtaining the current state value corresponding to each target evaluation index in the target evaluation index set from the current data.
Optionally, after determining the target evaluation index set corresponding to the target software development project, the server performs data acquisition and analysis. The server acquires the current state value corresponding to each target evaluation index in the target evaluation index set from the current data, wherein the current state value corresponding to each target evaluation index is a quantifiable value.
Step S504, comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
Optionally, the server compares the current state value with a reference range corresponding to a preset target evaluation index, wherein the reference range can be determined according to a historical state value or manually; and if the evaluation index exceeds the reference range, alarming the evaluation index exceeding the reference range. For example, the test coverage exceeds the lower limit of the reference range, and the test coverage is alerted.
In this embodiment, the current state value corresponding to each target evaluation index is compared with the reference range, and the target evaluation index exceeding the reference range value is alarmed, so that the abnormal target evaluation index can be found in time.
In an exemplary embodiment, the evaluation index processing method further includes:
and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
Wherein the visual trend graph shows trend changes of the fluctuation condition of the data with time or the ordered category.
Optionally, the server dynamically generates a visual trend graph according to the timestamp information by developing a dashboard or other visual tools to the state values corresponding to the target evaluation indexes in the target evaluation index set, and displays the visual trend graph. The server can combine the target evaluation indexes according to different dimensionalities in the target evaluation index set, and dynamically generate a visual trend graph according to the state values corresponding to the target evaluation indexes and the timestamp information. Or selecting a state value corresponding to a target evaluation index to dynamically generate a visual trend graph according to the timestamp information.
In this embodiment, the target evaluation index state value is visualized, so that the target evaluation index is more intuitive and easier to understand.
In an exemplary embodiment, as shown in fig. 6, the evaluation index processing method further includes steps S602 to S606. Wherein:
step S602, constructing an objective function based on the objective evaluation index set, and acquiring initial data.
Optionally, the server constructs an objective function based on the set of objective evaluation indicators, the objective function F (X) =w1×i1 (X) +w2×i2 (X) -w3×i3 (X), wherein: f (X) is an objective function representing a composite metric. X is a parameter vector and may include a plurality of parameters for controlling the weights of the different factors. I1 (X), I2 (X), I3 (X) and the like are evaluation indexes, and w1, w2 and w3 are weights for adjusting the importance of different evaluation indexes. Wherein the objective function can be constructed by Newton's method or genetic algorithm; and after the objective function is constructed, acquiring corresponding initial data.
Step S604, inputting the initial data into the objective function to obtain the objective function value.
Optionally, the server performs preprocessing on the obtained initial data, including denoising, normalization, missing value processing, and the like. And inputting the preprocessed initial data into an objective function, and solving the objective function to obtain an objective function value.
And step S606, when the objective function value is smaller than the threshold value, adjusting the numerical value of each objective evaluation index in the objective evaluation index set to obtain new initial data, and returning to execute the step of inputting the initial data into the objective function to obtain the objective function value until the objective function value is larger than or equal to the threshold value.
Optionally, judging the relation between the objective function value and the threshold value; when the objective function value is smaller than the threshold value, the numerical value of each objective evaluation index in the objective evaluation index set is adjusted to obtain new initial data, the step of inputting the initial data into the objective function to obtain the objective function value is carried out, and the step is finished until the objective function value is larger than or equal to the threshold value.
In this embodiment, by constructing the objective function and calculating the objective function value, by comparing with the threshold value, the objective evaluation index can be iteratively optimized, so that the evaluation index more accords with the software development project.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides an evaluation index processing device for realizing the above related evaluation index processing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation of the embodiment of the one or more evaluation index processing devices provided below may refer to the limitation of the evaluation index processing method hereinabove, and will not be described herein.
In an exemplary embodiment, as shown in fig. 7, there is provided an evaluation index processing apparatus including: a construction module 701, an acquisition module 702, a selection module 703 and a determination module 704, wherein:
a construction module 701, configured to construct an evaluation index set for a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related index, the demand related index, the test related index, the release related index, the service line quality related index and the quality related index of each equipment end respectively comprise at least one evaluation index.
The obtaining module 702 is configured to obtain a target keyword … of a target software development project.
The selecting module 703 is configured to determine a target evaluation index corresponding to the target keyword from a mapping relationship between the evaluation index and the keyword.
And a determining module 704, configured to determine a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In an exemplary embodiment, the selecting module 703 further includes:
and the traversing unit is used for traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes.
And the information entropy calculation unit is used for calculating the information entropy of each candidate evaluation index.
The entropy weight calculation unit is used for calculating the information utility value of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility value to determine the entropy weight of the candidate evaluation index;
the distinguishing degree calculating unit is used for calculating the distinguishing degree of the candidate evaluation indexes according to the information entropy and the entropy weight;
and the selection determining unit is used for selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
In an exemplary embodiment, the mapping relationship between the evaluation index and the keyword is pre-constructed according to the number of occurrences of the keyword and the evaluation index, including:
And the traversal counting module is used for traversing each historical evaluation index based on the keywords and counting the occurrence times of each historical evaluation index.
The history evaluation index selecting module is used for selecting a history evaluation index with the occurrence number larger than a threshold value;
and the generation module is used for associating the keywords with the historical evaluation indexes with the occurrence times larger than the threshold value to generate the mapping relation between the evaluation indexes and the keywords.
In an exemplary embodiment, further comprising:
the state value acquisition module is used for acquiring the current state value corresponding to each target evaluation index in the target evaluation index set from the current data;
and the comparison module is used for comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
In an exemplary embodiment, further comprising:
and the visualization module is used for dynamically generating a visualization trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set and the timestamp information, and displaying the visualization trend graph.
In an exemplary embodiment, further comprising:
the initial data acquisition module is used for constructing an objective function based on the objective evaluation index set and acquiring initial data;
The objective function value calculation module is used for inputting the initial data into the objective function to obtain an objective function value;
and the adjustment return module is used for adjusting the numerical value of each target evaluation index in the target evaluation index set to obtain new initial data when the target function value is smaller than the threshold value, and returning to execute the step of inputting the initial data into the target function to obtain the target function value until the target function value is larger than or equal to the threshold value.
The respective modules in the above-described evaluation index processing apparatus may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 8. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing evaluation index data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements an evaluation index processing method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 8 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
And determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In one embodiment, the processor when executing the computer program further performs the steps of:
traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes; calculating the information entropy of each candidate evaluation index; calculating information utility values of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility values to determine entropy weights of the candidate evaluation indexes; calculating the distinguishing degree of candidate evaluation indexes according to the information entropy and the entropy weight; and selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
In one embodiment, the processor when executing the computer program further performs the steps of:
traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index; selecting a historical evaluation index with occurrence times larger than a threshold value; and correlating the keywords with the historical evaluation indexes with occurrence times larger than the threshold value to generate a mapping relation between the evaluation indexes and the keywords.
In one embodiment, the processor when executing the computer program further performs the steps of:
Acquiring a current state value corresponding to each target evaluation index in the target evaluation index set from the current data; and comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
In one embodiment, the processor when executing the computer program further performs the steps of:
and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
In one embodiment, the processor when executing the computer program further performs the steps of:
constructing an objective function based on the objective evaluation index set, and acquiring initial data; inputting initial data into an objective function to obtain an objective function value; when the objective function value is smaller than the threshold value, the numerical value of each objective evaluation index in the objective evaluation index set is adjusted to obtain new initial data, the step of inputting the initial data into the objective function to obtain the objective function value is carried out, and the step is finished until the objective function value is larger than or equal to the threshold value.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In one embodiment, the computer program when executed by the processor further performs the steps of:
traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes; calculating the information entropy of each candidate evaluation index; calculating information utility values of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility values to determine entropy weights of the candidate evaluation indexes; calculating the distinguishing degree of candidate evaluation indexes according to the information entropy and the entropy weight; and selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index; selecting a historical evaluation index with occurrence times larger than a threshold value; and correlating the keywords with the historical evaluation indexes with occurrence times larger than the threshold value to generate a mapping relation between the evaluation indexes and the keywords.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a current state value corresponding to each target evaluation index in the target evaluation index set from the current data; and comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
In one embodiment, the computer program when executed by the processor further performs the steps of:
constructing an objective function based on the objective evaluation index set, and acquiring initial data; inputting initial data into an objective function to obtain an objective function value; when the objective function value is smaller than the threshold value, the numerical value of each objective evaluation index in the objective evaluation index set is adjusted to obtain new initial data, the step of inputting the initial data into the objective function to obtain the objective function value is carried out, and the step is finished until the objective function value is larger than or equal to the threshold value.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of each equipment end; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
In one embodiment, the computer program when executed by the processor further performs the steps of:
traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes; calculating the information entropy of each candidate evaluation index; calculating information utility values of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility values to determine entropy weights of the candidate evaluation indexes; calculating the distinguishing degree of candidate evaluation indexes according to the information entropy and the entropy weight; and selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index; selecting a historical evaluation index with occurrence times larger than a threshold value; and correlating the keywords with the historical evaluation indexes with occurrence times larger than the threshold value to generate a mapping relation between the evaluation indexes and the keywords.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a current state value corresponding to each target evaluation index in the target evaluation index set from the current data; and comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
In one embodiment, the computer program when executed by the processor further performs the steps of:
constructing an objective function based on the objective evaluation index set, and acquiring initial data; inputting initial data into an objective function to obtain an objective function value; when the objective function value is smaller than the threshold value, the numerical value of each objective evaluation index in the objective evaluation index set is adjusted to obtain new initial data, the step of inputting the initial data into the objective function to obtain the objective function value is carried out, and the step is finished until the objective function value is larger than or equal to the threshold value.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. An evaluation index processing method, characterized in that the method comprises:
constructing an evaluation index set aiming at a software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of all equipment ends; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
Acquiring a target keyword of a target software development project;
determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
2. The method according to claim 1, wherein the determining a target evaluation index corresponding to the target keyword from the mapping relationship between the evaluation index and the keyword comprises:
traversing the mapping relation in the mapping relation table according to the target keyword to obtain candidate evaluation indexes;
calculating the information entropy of each candidate evaluation index;
calculating the information utility value of each candidate evaluation index according to the information entropy, and carrying out normalization processing on the information utility value to determine the entropy weight of the candidate evaluation index;
calculating the distinguishing degree of the candidate evaluation indexes according to the information entropy and the entropy weight;
and selecting candidate evaluation indexes with the discrimination degree higher than the threshold value to obtain target evaluation indexes.
3. The method according to claim 1, wherein the construction method of the mapping relationship between the evaluation index and the keyword comprises:
Traversing each historical evaluation index based on the keywords, and counting the occurrence times of each historical evaluation index;
selecting a historical evaluation index with occurrence times larger than a threshold value;
and correlating the keywords with the historical evaluation indexes with the occurrence times larger than a threshold value to generate a mapping relation between the evaluation indexes and the keywords.
4. The method of claim 1, wherein after determining a target evaluation index set corresponding to the target software development project based on the target evaluation index, further comprising:
acquiring a current state value corresponding to each target evaluation index in the target evaluation index set from current data;
and comparing the current state value with a reference range corresponding to the target evaluation index, and giving an alarm if the current state value exceeds the reference range.
5. The method according to claim 4, wherein the method further comprises:
and dynamically generating a visual trend graph according to the state values corresponding to the target evaluation indexes in the target evaluation index set according to the timestamp information, and displaying the visual trend graph.
6. The method according to claim 1, wherein the method further comprises:
Constructing an objective function based on the objective evaluation index set, and acquiring initial data;
inputting the initial data into the objective function to obtain an objective function value;
and when the objective function value is smaller than a threshold value, adjusting the numerical value of each objective evaluation index in the objective evaluation index set to obtain new initial data, and returning to the step of inputting the initial data into the objective function to obtain the objective function value until the objective function value is larger than or equal to the threshold value.
7. An evaluation index processing apparatus, characterized by comprising:
the construction module is used for constructing an evaluation index set aiming at the software development project; the evaluation index set comprises research and development related indexes, demand related indexes, test related indexes, release related indexes, service line quality related indexes and quality related indexes of all equipment ends; the research and development related indexes, the demand related indexes, the test related indexes, the release related indexes, the service line quality related indexes and the quality related indexes of each equipment end respectively comprise at least one evaluation index;
the acquisition module is used for acquiring target keywords of the target software development project;
The selecting module is used for determining a target evaluation index corresponding to the target keyword from the mapping relation between the evaluation index and the keyword;
and the determining module is used for determining a target evaluation index set corresponding to the target software development project based on the target evaluation index.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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