Task completion measurement method, electronic equipment, storage medium and program product

Abstract

The embodiment of the invention discloses a task completion measurement method, electronic equipment, a storage medium and a program product. The method comprises the steps of obtaining a to-be-measured task completion file, and determining a measurement index corresponding to an achievement type according to the achievement type of the to-be-measured task completion file; performing information statistics on the to-be-measured task completion file according to the measurement index to obtain a first measurement index value; obtaining a historical measurement task completion file corresponding to the to-be-measured task completion file, and performing document deduplication on the to-be-measured task completion file according to the historical measurement task completion file to obtain a deduplicated task completion file; performing information statistics on the de-duplicated task completion file according to the measurement index to obtain a second measurement index value; and according to the first measurement index value and the second measurement index value, performing task completion measurement on the to-be-measured task completion file to obtain a task completion measurement value, and realizing reliability evaluation of the task completion degree under different measurement indexes based on the longitudinal data.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a task completion measurement method, electronic device, storage medium, and program product. Background Art

[0002] After a task is completed, it's often necessary to evaluate its performance. For example, to improve efficiency, Party A can outsource some non-core or repetitive tasks to Party B. Party B regularly submits task completion results to Party A. Party A measures these results to avoid low-quality results or under-utilization.

[0003] However, in the prior art, task completion is usually measured by Party A users through manual inspection, which is inefficient and relies on personal experience, making it impossible to achieve reliable unified standard measurement. Summary of the Invention

[0004] The present invention provides a task completion measurement method, electronic device, storage medium and program product to achieve reliability evaluation of task completion under different measurement indicators based on longitudinal data.

[0005] According to one aspect of the present invention, a task completion measurement method is provided, the method comprising:

[0006] Obtaining a task completion file to be measured, and determining a measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured;

[0007] Performing information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value;

[0008] Acquire a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file;

[0009] Performing information statistics on the deduplicated task completion files according to the metric to obtain a second metric value;

[0010] According to the first metric index value and the second metric index value, task completion measurement is performed on the task completion file to be measured to obtain a task completion measurement value.

[0011] According to another aspect of the present invention, there is provided a task completion measurement device, the device comprising:

[0012] A measurement indicator determination module is used to obtain a task completion file to be measured, and determine a measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured;

[0013] A first metric value determination module is configured to perform information statistics on the task completion file to be measured according to the metric to obtain a first metric value;

[0014] A document deduplication module is used to obtain a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file;

[0015] A second metric value determination module is configured to perform information statistics on the deduplicated task completion files according to the metric to obtain a second metric value;

[0016] The task completion measurement value determination module is used to perform task completion measurement on the task completion file to be measured according to the first measurement indicator value and the second measurement indicator value to obtain a task completion measurement value.

[0017] According to another aspect of the present invention, an electronic device is provided, comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the task completion measurement method according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the task completion measurement method described in any embodiment of the present invention when executed.

[0022] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the task completion measurement method according to any embodiment of the present invention is implemented.

[0023] The technical solution of the embodiment of the present invention obtains the task completion file to be measured, and determines the measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured; performs information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value; obtains the historical measurement task completion file corresponding to the task completion file to be measured, and deduplicates the task completion file to be measured according to the historical measurement task completion file to obtain a deduplicated task completion file; performs information statistics on the deduplicated task completion file according to the measurement indicator to obtain a second measurement indicator value; performs task completion measurement on the task completion file to be measured according to the first measurement indicator value and the second measurement indicator value to obtain a task completion measurement value, which solves the problem of automated measurement of the work of the Party B user by the Party A user in outsourcing work, and realizes reliability evaluation of task completion by measuring different achievement types based on longitudinal data under different measurement indicators.

[0024] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flowchart of a task completion measurement method provided according to the first embodiment of the present invention;

[0027] Figure 2 This is a flowchart of a task completion measurement method provided in accordance with the second embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of an interface of an application system for a task completion measurement method provided in a second embodiment of the present invention;

[0029] Figure 4 This is a structural diagram of a task completion measurement device provided according to a third embodiment of the present invention;

[0030] Figure 5 It is a structural diagram of an electronic device for implementing the task completion measurement method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a task completion measurement method provided according to the first embodiment of the present invention. This embodiment is applicable to situations where automatic measurement of task completion is performed, such as measuring tasks completed by Party B users in outsourced work. This method can be performed by a task completion measurement device, which can be implemented in the form of hardware and / or software. The task completion measurement device can be configured in electronic devices such as computers or smart terminals. Figure 1 As shown, the method includes:

[0035] Step 110: Obtain the task completion file to be measured, and determine the measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured.

[0036] The task completion documents must be obtained only after user authorization, and the method of acquisition must be reasonable and legal. The task completion documents to be measured can be of various types. For example, in a computer system integration project, Party B is responsible for code writing, test case development, and test execution. In this case, the task completion documents to be measured may include test case products, code products, and remaining basic documentation products.

[0037] Different metrics can be used to measure the task completion of the task completion document for different achievement types. Task completion metrics can measure the effectiveness, richness, and redundancy of the achievement. For example, metrics can include one or more of the following: text quantity, image quantity, attachment quantity, text information volume, use case quantity, reverse use case ratio, code redundancy, code violation count, and test coverage.

[0038] By measuring and evaluating the results under multi-dimensional measurement indicators, the reliability of the measurement results can be improved, helping Party A users to timely understand the completion status of Party B users, reducing manual consumption, and avoiding the measurement results from relying on manual experience.

[0039] Step 120: Perform information statistics on the task completion files to be measured according to the measurement indicators to obtain a first measurement indicator value.

[0040] Under each metric, information from the task completion file to be measured may be extracted and the amount of information under each metric is counted to obtain a first metric value.

[0041] Step 130: Obtain a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file.

[0042] Among them, by deduplicating the task completion files to be measured through the historical measurement task completion files, the newly added information in the task completion can be understood and the reliability of the task measurement can be improved.

[0043] Step 140: Perform information statistics on the deduplicated task completion files according to the metric to obtain a second metric value.

[0044] The second metric value can be determined in the same manner as the first metric value. By obtaining the second metric value based on the first metric value, longitudinal data can be obtained for the task completion file to be measured. This longitudinal data can be used to measure task completion and improve the reliability of the measurement results. Longitudinal data combines the characteristics of cross-sectional data and time series data. Longitudinal data involves metric values for the task completion file to be measured at different points in time. This allows for analysis of differences in the task completion file to be measured at different points in time, generating dynamic measurement results for the task completion file to be measured.

[0045] Step 150: Perform task completion measurement on the task completion file to be measured based on the first measurement indicator value and the second measurement indicator value to obtain a task completion measurement value.

[0046] The task completion measurement of the task completion file to be measured can be performed in various ways based on the first metric value and the second metric value. For example, the task completion measurement can be performed based on the first metric value and the second metric value using a neural network model prediction method, a logistic regression model prediction method, or a mathematical formula calculation method.

[0047] Optionally, based on the first metric indicator value and the second metric indicator value, the task completion measurement is performed on the task completion file to be measured to obtain the task completion measurement value, including: inputting the first metric indicator value and the second metric indicator value into a pre-trained task completion measurement logistic regression model to obtain the task completion measurement value.

[0048] Among them, the pre-trained task completion metric logistic regression model can be Among them, y represents the task completion measurement value, represents the model weight, The feature vector represents the first and second metric values, and b represents the model bias. The task completion metric value can be calculated using the pre-trained task completion metric logistic regression model.

[0049] When training a task completion metric logistic regression model, multiple task completion files and corresponding historical metric task completion files can be collected. Multiple experts can evaluate the task completion metric values of the task completion files back-to-back to form a sample set. The sample set can be divided into a training set and a test set. Based on the aforementioned metrics, the first and second metric values of the task completion files in the sample set are extracted and used as input feature data for the task completion metric logistic regression model. The task completion metric values in the sample set serve as the output of the task completion metric logistic regression model.

[0050] In the task completion metric logistic regression model training, the loss function used can be the mean square error Among them, n represents the number of samples, y i represents the predicted value of the i-th sample, Indicates the true value of the i-th sample. In the task completion metric logistic regression model training, gradient descent is used to optimize the loss function. Specifically, Among them, f(θ) is the loss function, the optimization goal is to find the parameters that minimize f(θ), η is the learning rate, It means to derive f(θ) and gradually optimize the parameter θ through iteration until a satisfactory accuracy or number of iterations is achieved.

[0051] In an embodiment of the present invention, an adaptive learning rate is used for model training, and the initial learning rate can be set to 0.1. When the loss function no longer decreases, the learning rate is reduced to half of the current learning rate. When the learning rate is reduced and the loss function no longer decreases, the model is considered to have reached convergence, and the trained task completion metric logistic regression model is obtained at this time. The various parameter indicators obtained after training are used as the model default values. In practical applications, the model default values can be adjusted according to actual needs. When no adjustment is made, the first metric value and the second metric value can be calculated based on the default value of the task completion metric logistic regression model to obtain the task completion metric value.

[0052] The technical solution of this embodiment obtains the task completion file to be measured, determines the measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured; performs information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value; obtains the historical measurement task completion file corresponding to the task completion file to be measured, and deduplicates the task completion file to be measured according to the historical measurement task completion file to obtain a deduplicated task completion file; performs information statistics on the deduplicated task completion file according to the measurement indicator to obtain a second measurement indicator value; performs task completion measurement on the task completion file to be measured according to the first measurement indicator value and the second measurement indicator value to obtain a task completion measurement value, which solves the problem of automated measurement of the work of the Party B user by the Party A user in outsourcing work, and realizes reliability evaluation of task completion by measuring different achievement types based on longitudinal data under different measurement indicators.

[0053] Based on the above implementation, optionally, the method further includes: extracting key content from the task completion file to be measured to obtain a task content summary; and generating a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value.

[0054] Among them, the task content summary can be obtained based on natural language processing (NLP). For example, information is extracted from the task completion file to be measured through a text summary algorithm to obtain a task content summary. Specifically, a weight can be assigned to each sentence in the task completion file to be measured to indicate the importance of the sentence. The weight of a sentence is determined by the relevance of the sentence to other sentences and the importance of the sentence itself. Exemplarily, a text network graph can be established through the relevance between sentences. In the text network graph, edges can be constructed between sentences through relevance to achieve connections between sentences. The weight of sentence i can be expressed as: Where d is the damping coefficient, which can be 0.85, In(i) represents all sentences connected to sentence i, Out(j) represents all sentences that can be reached from sentence j, ωji It represents the correlation between sentence i and sentence j. For example, the correlation can be calculated by cosine similarity or other methods.

[0055] In the weight calculation of a sentence, the final weight of the sentence can be obtained by continuously updating the sentence weight until convergence is reached. Specifically, through the formula Perform iterative calculation. Where t represents the number of iterations, W (t) (i) represents the weight of sentence i at iteration t. When the weights converge, the top n sentences with the highest ranking among all node weights are the key sentences, thus obtaining the task content summary.

[0056] After obtaining the task content summary, a task completion measurement report can be generated based on the task content summary and task completion measurement value, so that the Party A user can intuitively understand the main content and completion status of the task completion results.

[0057] Example 2

[0058] Figure 2 This is a flowchart of a task completion measurement method provided according to the second embodiment of the present invention. This embodiment is a further refinement of the above technical solution. The technical solution in this embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the method includes:

[0059] Step 210: Extract key content from the task completion file to obtain a task content summary.

[0060] Optionally, key content is extracted from the task completion file to obtain a task content summary, including: when the task completion file to be measured is image content, preprocessing the image content to obtain text content corresponding to the task completion file to be measured; when the task completion file to be measured is text content, key content is extracted from the code comment content in the text content to obtain a task content summary.

[0061] The pre-processing of the image content may be to perform text recognition on the image content to obtain the corresponding text content, for example, by performing optical character recognition (OCR) on the image content to obtain the text content.

[0062] For task completion files that contain text content, or images that were converted to text, we can extract key content and generate a summary of the task content. By converting image content within task completion files to text, we can extract key content from multimodal task completion files. Furthermore, in computer system integration projects, when the output images are code or system operation screenshots and contain a large amount of text, we can generate a reliable summary of the task content.

[0063] When performing key content extraction, the target content in the completed document of the task to be measured can be determined based on the specific application scenario, and the task content summary can be obtained. In computer testing, the code comments can be used as the target content for key content extraction to obtain the task content summary. This allows accurate key content extraction of code-related achievements and a reliable task content summary.

[0064] Step 220: Obtain the task completion file to be measured, and determine the measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured.

[0065] Optionally, the types of deliverables include: test case deliverables, code deliverables, and remaining basic document deliverables. The remaining basic document deliverables may be task completion files other than test case deliverables and code deliverables.

[0066] According to the outcome type of the task completion file to be measured, determine the measurement indicators corresponding to the outcome type, including: when the outcome type of the task completion file to be measured is the remaining basic document type outcome, the corresponding measurement indicators are at least one of the following: the number of words, the number of pictures, the number of attachments, and the amount of text information; when the outcome type of the task completion file to be measured is the test case type outcome, the corresponding measurement indicators are at least one of the following: the number of words, the number of pictures, the number of attachments, the amount of text information, the number of use cases, and the reverse use case ratio indicator; when the outcome type of the task completion file to be measured is the code type outcome, the corresponding measurement indicators are at least one of the following: the number of words, the number of pictures, the number of attachments, the amount of text information, code redundancy, the number of code violations, and test coverage.

[0067] In task completion files of different achievement types, the key achievement information is different. Therefore, based on different achievement types, different measurement indicators can be selected to generate different task completion measurement logistic regression models to achieve differentiated task completion measurement and improve the reliability of task completion measurement values.

[0068] Step 230: Perform information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value.

[0069] Optionally, information statistics are performed on the files for completing the task to be measured according to the measurement indicators to obtain a first measurement indicator value, including: adjusting the word frequency of a preset corpus according to the type of achievement to obtain a target corpus; document splitting is performed on the files for completing the task to be measured, and based on the word frequency of the vocabulary in the target corpus, the information entropy of the files for completing the task to be measured is determined; and the information entropy is used as the amount of text information in the first measurement indicator value.

[0070] Among them, the preset corpus can be an open source corpus, and the word frequency of each word can be specified in the preset corpus. In an embodiment of the present invention, the word frequency in the preset corpus can be adjusted according to the application scenario and the result type. Specifically, when the information entropy is calculated for the task completion files to be measured of each result type, the word frequency of computer-related terms in the preset corpus can be increased. When the information entropy is calculated for the task completion files to be measured whose result type is a test case type result, the word frequency of test-related words in the preset corpus can be increased. When the information entropy is calculated for the task completion files to be measured whose result type is a code type result, the word frequency of program-related words in the preset corpus can be increased. Through word frequency adjustment, a target corpus can be obtained. For task completion files to be measured of different result types, different target corpora are used when determining the information entropy.

[0071] After determining the target corpus corresponding to the achievement type, the formula Determine the information entropy of the task to be measured. Where H represents the information entropy of the task to be measured, E represents the expectation, and p i represents the frequency of the i-th word in the target corpus, where the base of the logarithm is 2.

[0072] In this embodiment of the present invention, for the same task completion document to be measured, when it is determined to be of different achievement types, different target corpora are used in calculating information entropy, resulting in different information entropies and, consequently, different amounts of textual information. When determining the task completion measurement value, different measurement indicators are used, and different task completion measurement logistic regression models are employed. This enables differentiated evaluation of task completion documents from different perspectives.

[0073] In the embodiment of the present invention, other measurement index values except the amount of text information can be obtained through statistical methods, which will not be described in detail here.

[0074] Step 240: Obtain a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file.

[0075] Step 250: Perform information statistics on the deduplicated task completion files according to the metric to obtain a second metric value.

[0076] Among them, the method for determining the second metric index value is the same as that for the first metric index value, and will not be repeated here.

[0077] Step 260: Input the first metric indicator value and the second metric indicator value into a pre-trained task completion metric logistic regression model to obtain a task completion metric value.

[0078] Step 270: Generate a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value.

[0079] Optionally, a task completion measurement report for the task completion file to be measured is generated based on the task content summary and the task completion measurement value, including: obtaining the standard reference value of each measurement indicator corresponding to the achievement type, comparing the second measurement indicator value with the standard reference value, and obtaining the target measurement indicator that does not meet the standard; generating a task completion measurement report for the task completion file to be measured based on the target measurement indicator, the task content summary and the task completion measurement value.

[0080] By adding substandard target metrics to the task completion measurement report, Party B users can promptly understand the reasons for substandard task completion and provide follow-up guidance. In addition, excellent metrics that exceed the standard reference value can be added to the task completion measurement report.

[0081] When generating a task completion measurement report, you can categorize the task completion documents into different quality levels based on the task completion measurement values, such as excellent, meeting the standards, and failing. By setting the quality level, task content summary, substandard target measurement indicators, and excellent measurement indicators in the task completion measurement report, Party A users can accurately understand the task completion status, and Party B users can timely improve the task completion quality based on the task completion analysis.

[0082] The technical solution of the embodiment of the present invention is to extract key content from the task completion file to be measured to obtain a task content summary; obtain the task completion file to be measured, and determine the measurement indicator corresponding to the achievement type of the task completion file to be measured according to the achievement type of the task completion file to be measured; perform information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value; obtain a historical measurement task completion file corresponding to the task completion file to be measured, and deduplicate the task completion file to be measured according to the historical measurement task completion file to obtain a deduplicated task completion file; perform information statistics on the deduplicated task completion file according to the measurement indicator to obtain a second measurement indicator value; input the first measurement indicator value and the second measurement indicator value into a pre-trained task completion measurement logistic regression model, Obtain the task completion measurement value; generate a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value, which solves the problem of automated measurement of the work of Party B users by Party A users in outsourced work. When measuring task completion, the text and image key information in the result file can be automatically extracted to obtain the task content summary; when determining the task completion measurement value, the corresponding task completion measurement logistic regression model can be selected according to the result type to provide reliability and accuracy in determining the task completion measurement value, avoiding result bias caused by personal experience; when determining the task completion measurement value, the longitudinal data differences of the same individual at different time points are analyzed, and the task completion file to be measured can be differentially analyzed to improve the reliability of task measurement.

[0083] Figure 3 Schematic diagram of the interface of an application system of a task completion measurement method provided by the second embodiment of the present invention. Figure 3As shown, users can upload an outcome file, namely, a task completion file to be measured, on the system interface. The system can determine the outcome type based on the task completion file to be measured, or the user can specify the outcome type within the system. Once the outcome type is determined, the system can determine the metric corresponding to the outcome type and the corresponding task completion metric logistic regression model. The system can determine a first metric value for the task completion file to be measured based on the metric. Based on the task completion date, the system can determine the historical measured task completion file corresponding to the task completion file to be measured. Furthermore, the system deduplicates the documents to obtain deduplicated task completion files. The system then analyzes the deduplicated task completion files based on the metric to obtain a second metric value. When determining the task completion metric, the system displays the default values for each metric coefficient in the task completion metric logistic regression model. Users can adjust these default values or set weights for the first and second metric values. If there are no historical measured task completion files, the weight for the first metric can be set to 1, and the weight for the second metric can be set to 0. In this case, the weights cannot be adjusted. The system then uses the task completion metric logistic regression model to determine the task completion metric based on the first and second metric values. The system can also extract key content from the task completion file to be measured to obtain a summary of the task content. Furthermore, the system generates a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value. In the task completion measurement report, in addition to displaying the task content summary and the task completion measurement value, the task completion file to be measured can also be divided into different quality levels according to the task completion measurement value, such as excellent, meeting the standard, and unqualified. At the same time, in the task completion measurement report, the standard reference value of each measurement indicator corresponding to the outcome type can also be set, and the target measurement indicator that does not meet the standard and the excellent measurement indicator can be determined based on the standard reference value and the second measurement indicator value. In the task completion measurement report, the target measurement indicator that does not meet the standard and the excellent measurement indicator can be displayed to guide users to make targeted task improvements.

[0084] Example 3

[0085] Figure 4 Schematic diagram of a task completion measurement device according to the third embodiment of the present invention. Figure 4 As shown, the apparatus includes: a metric determination module 410, a first metric value determination module 420, a document deduplication module 430, a second metric value determination module 440 and a task completion metric value determination module 450. Among them:

[0086] The measurement indicator determination module 410 is used to obtain the task completion file to be measured and determine the measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured;

[0087] A first metric value determination module 420 is configured to collect information statistics of the task completion files to be measured based on the metric to obtain a first metric value;

[0088] The document deduplication module 430 is used to obtain a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file;

[0089] A second metric value determination module 440 is configured to perform information statistics on the deduplicated task completion files according to the metric to obtain a second metric value;

[0090] The task completion metric value determining module 450 is configured to perform task completion metric on the task completion file to be measured based on the first metric indicator value and the second metric indicator value to obtain a task completion metric value.

[0091] Optionally, the device further includes:

[0092] The task content summary determination module is used to extract key content from the completion file of the measurement task to obtain the task content summary;

[0093] The task completion measurement report generation module is used to generate a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value.

[0094] Optional, the output type includes: test case output, code output, and other basic document outputs;

[0095] The metric determination module 410 includes:

[0096] A basic document type measurement indicator determination unit is configured to determine, when the achievement type of the task completion file to be measured is a remaining basic document type achievement, a corresponding measurement indicator of at least one of the following: the number of words, the number of pictures, the number of attachments, and the amount of text information;

[0097] a test case type measurement indicator determination unit, configured to determine, when the achievement type of the task completion document to be measured is a test case type achievement, at least one of the following measurement indicators: the number of words, the number of pictures, the number of attachments, the amount of text information, the number of use cases, and the ratio of reverse use cases;

[0098] The code-type metric indicator determination unit is used to determine, when the result type of the task completion file to be measured is a code-type result, the corresponding metric indicator is at least one of the following: the number of words, the number of pictures, the number of attachments, the amount of text information, the code redundancy, the number of code violations, and the test coverage.

[0099] Optionally, the first metric value determination module 420 includes:

[0100] A word frequency adjustment unit is used to adjust the word frequency of the preset corpus according to the output type to obtain the target corpus;

[0101] An information entropy determination unit is used to split the document of the task to be measured and determine the information entropy of the task to be measured based on the word frequency of the vocabulary in the target corpus;

[0102] The text information amount determining unit is used to use information entropy as the text information amount in the first measurement index value.

[0103] Optionally, the task completion metric determination module 450 includes:

[0104] The task completion metric value determination unit is used to input the first metric indicator value and the second metric indicator value into a pre-trained task completion metric logistic regression model to obtain a task completion metric value.

[0105] Optional task content summary determination module, including:

[0106] A text content determination unit is used to pre-process the image content when the task completion file to be measured is a picture content, so as to obtain the text content corresponding to the task completion file to be measured;

[0107] The task content summary determination unit is used to extract key content from code comments in the text content when the task completion file to be measured is text content, so as to obtain the task content summary.

[0108] Optional, task completion measurement report generation module, including:

[0109] a target metric determination unit, configured to obtain a standard reference value of each metric corresponding to the achievement type, compare the second metric value with the standard reference value, and obtain a target metric that does not meet the standard;

[0110] The task completion measurement report generating unit is used to generate a task completion measurement report for the task completion file to be measured based on the target measurement indicator, the task content summary and the task completion measurement value.

[0111] The task completion measurement device provided in the embodiment of the present invention can execute the task completion measurement method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0112] In the technical solutions of the embodiments of the present invention, the collection, storage, use, processing, transmission, provision and disclosure of user personal information (such as files on completion of tasks to be measured and files on completion of historical measurement tasks, etc.) comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0113] Example 4

[0114] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0115] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0116] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0117] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors for running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the task completion measurement method.

[0118] In some embodiments, the task completion measurement method can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the task completion measurement method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the task completion measurement method in any other suitable manner (e.g., by means of firmware).

[0119] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0120] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0123] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0124] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0125] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0126] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A task completion measurement method, characterized in that: include: Obtaining a task completion file to be measured, and determining a measurement indicator corresponding to the achievement type according to the achievement type of the task completion file to be measured; Performing information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value; Acquire a historical measurement task completion file corresponding to the task completion file to be measured, and perform document deduplication on the task completion file to be measured based on the historical measurement task completion file to obtain a deduplicated task completion file; Performing information statistics on the deduplicated task completion files according to the metric to obtain a second metric value; According to the first metric index value and the second metric index value, task completion measurement is performed on the task completion file to be measured to obtain a task completion measurement value.

2. The method according to claim 1, characterized in that Also includes: Extract key content from the task completion file to obtain a task content summary; A task completion measurement report for the task completion file to be measured is generated according to the task content summary and the task completion measurement value.

3. The method according to claim 1, characterized in that The types of deliverables include: test case deliverables, code deliverables, and remaining basic document deliverables; Determine, based on the achievement type of the task completion document to be measured, a measurement indicator corresponding to the achievement type, including: When the achievement type of the task completion file to be measured is the remaining basic document achievement, the corresponding measurement indicator is at least one of the following: the number of words, the number of pictures, the number of attachments, and the amount of text information; When the achievement type of the task completion file to be measured is a test case achievement, the corresponding measurement indicator is at least one of the following: the number of words, the number of pictures, the number of attachments, the amount of text information, the number of use cases, and the reverse use case ratio indicator; When the achievement type of the task completion file to be measured is a code-related achievement, the corresponding measurement indicator is at least one of the following: the number of words, the number of pictures, the number of attachments, the amount of text information, code redundancy, the number of code violations, and test coverage.

4. The method according to claim 3, characterized in that Performing information statistics on the task completion file to be measured according to the measurement indicator to obtain a first measurement indicator value includes: Adjust the word frequency of the preset corpus according to the achievement type to obtain the target corpus; Performing document splitting on the task completion file to be measured, and determining the information entropy of the task completion file to be measured based on the word frequency of the vocabulary in the target corpus; The information entropy is used as the amount of text information in the first metric value.

5. The method according to claim 1, wherein Performing task completion measurement on the task completion file to be measured according to the first measurement indicator value and the second measurement indicator value to obtain a task completion measurement value includes: The first metric indicator value and the second metric indicator value are input into a pre-trained task completion metric logistic regression model to obtain a task completion metric value.

6. The method according to claim 2, characterized in that Extract key content from the task completion file to obtain a task content summary, including: When the task completion file to be measured is a picture content, preprocessing the picture content to obtain text content corresponding to the task completion file to be measured; When the task completion file to be measured is text content, key content is extracted from the code comments in the text content to obtain a task content summary.

7. The method according to claim 2, characterized in that Generating a task completion measurement report for the task completion file to be measured based on the task content summary and the task completion measurement value, including: Obtaining a standard reference value for each metric corresponding to the achievement type, comparing the second metric value with the standard reference value, and obtaining a target metric that does not meet the standard; Generate a task completion measurement report for the task completion file to be measured based on the target measurement indicator, the task content summary and the task completion measurement value.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the task completion measurement method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the task completion measurement method according to any one of claims 1 to 7 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the task completion measurement method according to any one of claims 1 to 7.

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