54 results about "Software measurement" patented technology

The invention discloses a method for evaluating the implementation quality of a software process, which belongs to the field of computer software engineering. The method comprises the following steps that: 1) a user selects an evaluation model or a standard of the software process from an evaluation standard library by using an evaluation standard selection module; 2) an index system establishment module establishes an measurement index system by adopting a target-problem-measurement method or a utility software measurement method; 3) an index measurement data acquisition module performs data acquisition on the software process to be evaluated according to the established measurement index system, and simultaneously, an index weight determination module determines the weight of each measurement index according to the established measurement index system; 4) a comprehensive evaluation computing module performs numerical value standardization and form unitization on the acquired data; and 5) the comprehensive evaluation computing module evaluates the processed data by adopting a fuzzy comprehensive evaluation method and outputs the evaluation result. The method not only ensures flexibility and the strictness of the result, but also ensures the accuracy of the evaluation process and the validity of the evaluation result.

The invention provides a construction method of a software defect evaluation model on the basis of a complex network, and can predict potential defects in a software system. The construction method comprises the following steps: 1) taking classes in software as nodes and a relationship between the nodes as edges to construct the directed network model of the software; 2) according to the directed network model obtained in 1), carrying out the characteristic measurement calculation of the complex network; 3) scanning a software source code to carry out structured program measurement, and obtaining the measurement values of cyclomatic complexity and function depth; 4) scanning the software source code to carry out object-oriented software measurement; 5) utilizing a FindBugs static analysis tool and a software defect report on an open-source tool official website to search and analyze software defect information; and 6) constructing a defect evaluation formula: using the calculation data of a corresponding effective measurement index for different classes of software, establishing a corresponding multiple linear regression model, and obtaining the software defect evaluation model.

The invention relates to an area measurement technology of the broad leaved plant vane, particularly to a method using the digital camera to combine the squared paper, the Photograph software measurement and the computation of the broad leaved plant vane. The method includes the steps of collecting the plant vane, soaking with water, extracting the vane when in the measurement, blotting by filter paper, laying on the transparent plastic plate arranged in the row. The plastic plate is put on the fixed standard squared paper, shot by the digital camera, computing the pixel of the vane by the Photoshop software, dividing the pixel value with the area of 1 cm2 of the standard squared paper. A plurality of samples are measured to obtain the mean, namely the vane area of the plant. The method is simple, correct, low in cost, strong in the field maneuverability, especially used for measuring the dehydration broad leaved plant vane, which is a practical method for the scientific research.

The invention discloses an automated open-source software quality evidence extraction method, comprising the following steps: a local server receives a user request and inquires whether a local database has newest change data of target software; if update data in a preset time period are existent, the local server provides various quality evidences and measurement scores of the target software and returns the evidences and the scores to a user, periodically checks and updates corresponding resource bases of the existing items, and recalculates each measurement value; and if the local database hasn't the newest change data of the target software, the local server searches on the Internet and determines a remote server with the newest change data of the target software, downloads the newest change data to the local database, analyzes the newly-downloaded newest change data of the target software so as to extract and store structured data items, extracts software quality measurement from the analyzed structured data, provides various quality evidences and measurement scores of the target software and returns the evidences and the scores to the user. According to the automated open-source software quality evidence extraction method, the local resource bases are updated periodically, so that the automatic extraction of the open-source software quality evidences is realized.

The invention discloses a software defect prediction method based on two-stage wrapping-type feature selection, and belongs to the field of software quality assurance. The software defect prediction method comprises the following steps: (1) mining the version control system and the defect tracking system of a software project, extracting a program module from the version control system and the defect tracking system, and carrying out type marking and software measurement on the program module to generate a defect prediction data set D; (2) carrying out two-stage wrapping-type feature selection on the defect prediction data set so as to remove redundant features and irrelevant features in the data set D as many as possible, and finally, selecting an optimal feature subset FS' from an original feature set FS; and (3) on the basis of the optimal feature subset FS', preprocessing the data set D, forming a preprocessed data set D', and finally, constructing a defect prediction model in virtue of a decision tree which is a classification method. By use of the software defect prediction method, on one hand, the redundant features and the irrelevant features in the defect prediction data set can be effectively identified and removed, on the other hand, a class imbalance problem in the defect prediction data set can be effectively alleviated, and finally, the performance of the defect prediction model can be effectively improved.

The present invention provides a method for software measurement of ground phosphate rock consumption and a phosphoric acid production parameter control method in a feed-grade calcium hydrophosphate production process. The phosphoric acid production parameter control method comprises the steps of: analyzing relevant factors for influencing consumption, based on the method theory of machine learning, transmitting and storing pulp flow real-time data and vitriol flow real-time data automatically collected by an internet-of-things collection device and pulp flow data manually collected by a lab to a cloud platform, allowing a python language-based analysis platform to be directly connected with a database to extract features based on time sequence data to perform analysis and modeling, and establishing a real-time soft measurement technology for the ground phosphate rock consumption to replace a ground phosphate rock physical measurement device with high investment and easy damaging. Theimplementation process of the method mainly comprises the steps of: pulp flow collection, vitriol flow, pulp storage tank intensity, mineral powder consumption historical data, data preprocessing, training of a gradient boosted decision tree (GBDT) regression model, and prediction of the mineral powder consumption to control phosphoric acid for generation of parameters through adoption of the trained GBDT regression model.

The invention discloses a modeling method of a support vector machine (SVM)-based software measurement instrument in a biological fermentation process. The modeling method uses an optimized SVM modelto estimate fermentation products in the biological fermentation process and comprises two steps: the SVM modeling of the biological fermentation process and the confirmation of an optimal model basedon a genetic simulated annealing algorithm and an akaike information criterion. The invention provides an optimal SVM software measurement instrument model for variables difficult in online measurement in the biological fermentation process, eliminates a phenomenon of untimely control caused by time lag of a traditional offline measuring method, lays a reliable foundation for establishing the SVMmodel in the biological fermentation software measurement and has the advantages of online measurement, automatic parameter optimization, automatic input variable selection, small sample demand and high precision.

The invention discloses a deep belief network-support vector machine (DBN-SVM)-based software defect prediction method. A DBN is adopted to perform dimensionality reduction on a software measurement attribute extracted from to-be-predicted software; and data after the dimensionality reduction enters an SVM for performing classification, thereby obtaining a software defect prediction result. A novel software defect distribution prediction model-DBN-SVM is adopted to solve the problem that the prediction precision is reduced due to data redundancy caused by multi-dimensional measurement in software defect distribution prediction.

The invention discloses a method for testing an improved host-oriented embedded software white box, and belongs to the technical field of embedded software test. The method comprises the following steps: 1, a first stage test (coarse prediction), comprising extraction of program invariable, machine learning, machine prediction and the like based on a support vector machine, and preliminarily revealing hidden error; 2, a second stage test (prior white box test), namely carrying out embedded software white box coverage test on the program removed with revealed error attribute, and removing problems appearing during removal test, wherein the white box test comprises lexical analysis, grammar analysis, software measurement analysis and coverage rate analysis; and 3, a third stage test (precise prediction), namely identifying the program removed with the problems appearing during coverage test by using a machine predication step in the first stage to acquire possibly hidden deeper program error. The method can be applied to different programs and has strong universality.

The invention relates to a hydraulic support electro-hydraulic control system testing device, which mainly comprises three parts such as fully-mechanized coal mining working face three-machine operating relation control, fully-mechanized coal mining working face environmental condition simulation and system hardware and software measurement and control. The hydraulic support electro-hydraulic control system testing device can perform detection and inspection on a tested sample on the aspects of system functions, technical performance, working stability, safety, interference resistance, reliability and the like without damaging the tested sample. A testing platform is of an operating condition that a hydraulic support, a coal mining machine and a scarper conveyer operate in a coordinated manner, so that service conditions of an electro-hydraulic control system in a coal mine underground can be simulated to the maximum extent. Assessment for the hydraulic support electro-hydraulic control system is completed strictly according to safety standard specifications and national standards.

The invention discloses a method and a system for measuring accuracy of crystal oscillators. The method includes enabling a first timer and a second timer to respectively start counting clock frequency of a first crystal oscillator and clock frequency of a second crystal oscillator; circularly reading a count value of the second timer until the count value of the second timer is equal to the clock frequency of the second crystal oscillator; and reading a count value of the first timer and acquiring actual clock frequency of the second crystal oscillator according to the count value of the first timer so as to judge the accuracy of the second crystal oscillator. Measurement by the aid of instruments or machine detachment are omitted in a troubleshooting process for problematic crystal oscillators, mobile phones with the problematic crystal oscillators are screened only by the aid of software measurement, work efficiency is greatly improved, troubleshooting time and labor cost are greatly saved, and the method and the system are applicable to large-scale production.

Embodiments of the invention provide a data processing method and device, relates to the technical field of computers, and mainly aims at realizing the automatic and uniform acquisition and measurement of research development data through integrating data information of the whole research and development process of distributed software so as to judge the software quality. The technical scheme of the embodiments is that the method comprises the following steps: obtaining a measurement report obtaining request sent by a server, wherein the measurement report is obtained through carrying out measurement and calculation on software research and development data; obtaining software research and development data and a report template in a resource data platform according to the obtaining request, wherein the resource data platform is used for storing research and development data of a plurality of software products and corresponding report templates; calculating the software research and development data according to a preset software measurement and calculation model so as to obtain a software measurement value; adding the software research and development data and the software measurement value into the report template to generate a measurement report; sending the measurement report to the server. The method and device are mainly used for the processing of software research and development data.

The invention discloses a controlling method of improving current quality of a grid-connected inverter when operated in low load. The controlling method of improving the current quality of the grid-connected inverter when operated in low load achieves judgment of the operating mode of the grid-connected inverter according to the difference of the ratio of the actual output power and rated power of the inverter. When the ratio ranges from 0.6 to 1, the grid-connected inverter is in the normal working mode, and the classic voltage current double closed-loop PI controlling is adopted; when the ratio ranges from 0.3 to 0.6, the grid-connected inverter is in the mild low-load working mode, the classic voltage current double closed-loop PI controlling is adopted at the moment, and software measurements are added, wherein the software measurements comprise improving the switch frequency by one time, enabling an inner ring PI adjuster to be merged into a repetition controller and the like; when the ratio is less than 0.3, the grid-connected inverter is in the severe low load working mode, at the moment hardware measurements are added on the basis of the mild low load controlling method, the hardware measurements comprise starting a controlling relay and enabling a bridge-arm side addition inductor to be merged. The controlling method of improving the current quality of the grid-connected inverter when operated in low load ensures grid current when the grid-connected inverter runs under low load, can reduce the quantity of the added inductor, and saves cost.

The invention discloses an automated measurement method for security software of a B / S framework, and belongs to the field of automated software measurement. According to the method, a rule configuration interface API is controlled through forced access to the security software of the B / S framework so that the rule configuration interface API can be called by a Python script program; after a file of a parameter format is arranged on the this basis, testers without development experience can complete automated use case compiling and maintaining through the cooperation with an open-source automated testing management framework, the use case compiling and managing difficulty is lowered, and the problem that the dual-computer interface operation can hardly be automated is solved; the method can be perfectly compatible with a Windows system and a Linux system, the complexity of an automation system is lowered, and the testers can conveniently conduct deployment and use; meanwhile, a web interface can be slightly and internally regulated through a subsequent version of the security software by only slightly modifying the rule configuration method, use cases can be normally used, and the maintenance cost is reduced.

The invention discloses an intelligent detection system for ammonia gas in a cowshed environment based on a wireless sensor network. The intelligent detection system is characterized by being composed of an intelligent cowshed environment parameter detection platform based on the wireless sensor network and an intelligent cowshed environment ammonia gas detection model, wherein the intelligent cowshed environment parameter detection platform based on the wireless sensor network is capable of detecting, regulating and monitoring cowshed environment factor parameters; the intelligent cowshed environment ammonia gas detection model comprises a clustering classifier based on a genetic algorithm (GA) and a fuzzy C mean (FCM), a plurality of fuzzy wavelet neural network ammonia gas models, and an ammonia gas concentration value fusion model based on Euclidean distance, so that intelligent software measurement of the cowshed environment ammonia gas is realized. According to the system disclosed by the invention, the problems that the ammonia gas concentration in the cowshed is influenced by multiple environmental factors such as temperature, humidity, ventilation, illumination conditions in the cowshed and an accurate measurement model is hard to establish by the traditional mathematical method are effectively solved.

The invention discloses an electronic label-based programmable control semi-automatic guide rail-type piano tuner. The piano tuner comprises a motor, a planetary speed reducer, a power transfer mechanism of a turbine worm mechanism, a controller, an electronic label and a guide rail-type piano tuning mechanism, wherein the power transfer mechanism is fixed on the guide rail-type piano tuning mechanism; and the electronic label is annularly stuck on the saddle of the piano. The tuning method of the invention comprises the following steps: an electronic label module of the controller reads a frequency set by the saddle to be tuned; a pickup reads the saddle to be tuned to obtain a software measurement frequency; and the frequency difference is converted into a certain step length drive amount by an algorithm of a central processing unit of the controller to send an instruction to the power transfer mechanism so as to finish semi-automatic tuning of the saddle and gradual tuning of the saddle of the piano, wherein the step length can be flexibly adjusted according to precision and experience. The invention saves manual tuning and is a high-precision special tuning tool for professional tuners and tuning lovers.

The invention discloses an SAW (Surface Acoustic Wave) sensor based embedded electronic nose testing system and testing method. The testing method comprises the steps of: (1) obtaining relevant training data and test data by a microcontroller; (2) if the format of the obtained data does not conform to a specification, processing; otherwise, skipping this step; (2) if a parameter setting signal is received, skipping to a step (6); otherwise, setting relevant parameters automatically; (4) adjusting relevant parameters according rules of neural networks until the training is finished; (5) if the training result reaches to requirements, skipping to a step (8); otherwise, continuing; (6) setting relevant parameters according to the reference setting signal until the training is finished; (7) if the training result reaches to the requirements, skipping to the step (8); otherwise, skipping back to the step (6); and (8) using the training result to mode identification or software measurement and obtaining practical output according to test data. According to the SAW sensor based embedded electronic nose testing system and testing method, disclosed by the invention, neural network algorithm is simplified and optimized, and the training process of the neural network can be transplanted in an embedded platform.

The invention, which belongs to the underwater special measurement field, discloses a computer-vision-based underwater laser datum line measuring system for measuring a relative position parameter for underwater structure installation and assisting in underwater engineering building. According to the measuring system, a laser ray generated by a high-power laser is used as a preset datum line and a measuring scale, thereby providing an image feature for computer vision software measurement. An underwater camera carried by the system obtains an underwater on-the-spot picture; the computer vision software extracts an image feature; a relative distance between an underwater structure and a preset position is obtained by using a built-in algorithm; and a difference of elevation or a tooth malocclusion parameter between two adjacent regular structures is measured by extracting other features of the picture. Therefore, a plane attitude or relative position of a structure can be reflected; and an objective of assisting in precise installation of underwater work can be achieved.

The invention relates to a bank microservice-based software test analysis method, which comprises the following steps of: A, dividing test analysis of a bank system into four object dimensions, namelya product scene layer, a user scene layer, a microservice layer and an interface layer, according to a product of a bank, a user group and an architecture of the bank system; b, decomposing all the functional logics of each layer into minimum units, sorting out all test points, forming father / child nodes by the test points in each layer, and then respectively establishing an element hierarchy tree; c, determining the type of a test analysis model needing to be established according to actual test requirements; d, according to the determined types of the test analysis models, nodes under the element level trees are combined in a crossed mode to form the corresponding test analysis models. According to the method, the test analysis is easier under the conditions of huge number of bank software systems and complex business logic at present, the test requirements can be comprehensively covered, and the test range can be well evaluated.

The present invention provides a computer protection apparatus and method. The apparatus comprises: a policy management unit, a hardware measurement unit, a software measurement unit and an execution unit, wherein the policy management unit is used for configuring a to-be-measured hardware device and a to-be-measured kernel file according to received policy configuration information; the hardware measurement unit is used for measuring the to-be-measured hardware device when a computer powered on to obtain a first measurement value; the software measurement unit is used for measuring the to-be-measured kernel file to obtain a second measurement value; and the execution unit is used for determining whether the first measurement and the second measurement value are the same as corresponding standard measurement values, if yes, the to-be-measured hardware device or a guiding operating system is allowed to be started, and if not, after a starting privileged code from the outside is received or a warning message is sent to the outside, the to-be-measured hardware device or the guiding operating system is allowed to be started. The scheme provided by the present invention can improve the security of a computer.

The invention discloses a tunnel sedimentation convergence automatic measurement system and belongs to the technical field of tunnel monitoring and measurement, and especially relates to a measurementinstrument device and measurement method used for tunnel crown settlement, clearance convergence and ground surface settlement. The system is mainly composed of a clearance convergence measurement unit, a settlement measurement unit (including a crown settlement measurement device and a ground surface settlement device), a control terminal, a temperature / humidity sensor, accessories (a dedicatedmeasurement connection pipe, a connection cable, a light reflecting board and the like) and a set of measurement software. A laser phase ranging submillimeter measurement technology, a precision levelmeasurement technology, a self-networking ultra-low power consumption wireless communication technology, a function conversion indirect measurement technology, a height reference importing technology, a software measurement technology and a rapid assembly and disassembly connection method are adopted integrally, so that high precision and automation of the system are ensured.

The invention relates to a high-stability mobile phone software test device having a cooling function. The high-stability mobile phone software test device comprises a box body and a control panel, wherein the shape of the box body is cuboid, the control panel is arranged on the box body, a test device is arranged in the box body, a connection mechanism and a cooling mechanism are arranged in thebox body, the connection mechanism comprises a driving assembly and two connection assemblies, the driving assembly is arranged between the two connection assemblies, and each connection assembly comprises a rotation shaft, a bearing seat, a driven bevel gear, a lead screw, a sliding block, a connection rod and a strip-shaped groove. In the high-stability mobile phone software test device having the cooling function, the stability is improved by the connection mechanism, and the displacement of a mobile phone during the mobile phone software test process is prevented; and moreover, a cooling effect is also achieved by the cooling mechanism, and the influence on mobile phone software measurement accuracy due to overheat of the mobile phone is prevented.

The invention discloses a method for online soft measurement of mill power in an ore grinding process, and relates to a mill power measurement method. According to the method, a computer is utilized to acquire real-time process data in the ore grinding process; and through constructing a POS-BP network ore grinding process soft measurement model, an estimated value of the mill power is calculated so as to realize online measurement of the mill power. According to the method, the trained POS-BP soft measurement model is realized in a computer control system by a program; six process parameters are acquired on the spot in real time to serve as inputs of the software measurement model and the mill power serves as an output to realize online estimation of the mill power, so that a mill swelling frequency is decreased, a mill processing amount and an ore grinding granularity quantification rate are improved, lining plate loss and steel ball loss are reduced, and economic benefits of mine enterprises are improved.

The invention discloses an ion chromatography system for controlling a double-conductance-cell series technology through a virtual instrument. The system comprises an ion chromatography separation module fixed to an ion chromatography instrument, a suppressor flow path module, a conductance cell series module, an ion chromatography interface equipment card inserted into a microcomputer PCI slot, and a software measurement and control module located in a microcomputer. A specific analog or digital circuit in a traditional ion chromatography instrument is obtained through a software program to complete measuring and testing functions, noise can be greatly lowered, the signal to noise ratio is increased, and the measuring result is more precise. Samples with large concentration differences are tested at a time through the double-conductance-cell series technology, the temperature is unified, and measuring precision is improved. It is not needed to carry out high-concentration ion pretreatment on the samples with the large concentration differences, analysis time is shortened, measuring efficiency is improved, and the detection and operation cost is reduced.

The invention discloses a method for testing an improved host-oriented embedded software white box, and belongs to the technical field of embedded software test. The method comprises the following steps: 1, a first stage test (coarse prediction), comprising extraction of program invariable, machine learning, machine prediction and the like based on a support vector machine, and preliminarily revealing hidden error; 2, a second stage test (prior white box test), namely carrying out embedded software white box coverage test on the program removed with revealed error attribute, and removing problems appearing during removal test, wherein the white box test comprises lexical analysis, grammar analysis, software measurement analysis and coverage rate analysis; and 3, a third stage test (preciseprediction), namely identifying the program removed with the problems appearing during coverage test by using a machine predication step in the first stage to acquire possibly hidden deeper program error. The method can be applied to different programs and has strong universality.

The invention discloses a large-scene inclined image three-dimensional reconstruction zone partitioning method, and relates to the technical field of surveying and mapping photography. The method comprises the following steps of (1) after an inclined photo requiring the zone partitioning is input, performing software measurement to obtain the position, the posture and the ground coordinates X, Y and Z of each connecting point of each image during the photo taking by a camera. The method disclosed by the invention has the advantages that the design is novel; the method is strict; the large-region image is reconstructed after the zone partitioning; the time and the energy consumption can be effectively saved; the work efficiency is improved; the problem of great time and resource waste of one-step reconstruction due to too great data volume of the large-region image can be solved; in addition, since the internal memory of a computer is limited, the computer freeze or system halting can be caused by too great data during the operation; through the zone partitioning operation by aerotriangulation software, the reasonable zone partitioning can be ensured when the model precision is ensured; the model data completeness is ensured; and the problem of model holes caused by photo taking image absence due to insufficient zone partitioning precision can be solved.

The invention discloses a software measurement detection method and system. The method comprises the steps that a detection device performs acceptance identification on tested software; the detection device calls and executes an acceptance case based on the acceptance identifier to perform acceptance on the tested software; the detection device outputs a measurement report according to an acceptance result, wherein the measurement report comprises a coverage rate report and a cyclomatic complexity report. By the adoption of the software measurement detection method and system, the software measurement detection system automatically executes the acceptance case instead of manual execution according to the software measurement detection method and ranks the cyclomatic complexity and the coverage rate of the tested software according to the result of the acceptance case, and therefore the effects of relieving the heavy task load brought by manual operation, lowering labor cost, improving software measurement efficiency and increasing software measurement speed are achieved.

The invention provides a software defect detection method for effective data processing. The method includes the steps of firstly, detecting a received software module, obtaining an original softwaremeasurement data set, and conducting preprocessing on the data of the original software measurement data set to divide the data into a training sample and a testing sample; forming a dictionary learning model for the training sample data, discriminating and structuralizing a dictionary, adopting an asymmetric classifier for conducting performance assessment, detecting and shifting the testing sample, using the module to conduct defect detection on the software detection module, feeding back an assessment result to a tester, and completing the whole detection. By means of the software defect detection method for effective data processing, the expression capability of the dictionary can be improved, great discrimination performance is achieved, errors caused by unbalanced data are effectively solved at the same time, and the positions of the software defects are accurately located.

The invention discloses an experiment device for recycling ammonia in LED (light emitting diode) mixed waste gas by a compression refrigeration method and a verifying method of the experiment device. The verifying method is mainly used for verifying that GaN is deposited by the ammonia and a trimethyl gallium gas phase of a semiconductor light emitting diode (LED); the mixed gas of ammonia, nitrogen and hydrogen is discharged in a production process, and a little of ammonia in the mixed gas is recycled by the compression refrigeration method technology; the correctness of chemically technical software measurement during technical design is verified; the possible deflection in a design and actual implementation process is prevented; the design precision is improved; the investment loss is reduced.

The invention provides a software defect detecting system based on dissymmetrical classified evaluation. The system comprises a software data input interface, a controller and a detection result output port. The controller is used for firstly detecting a received software module, obtaining an original software measurement dataset, preprocessing data of the original software measurement dataset, dividing the data into a training sample and a testing sample, conducting dictionary learning modeling on the data of the training sample, distinguishing and structuralizing dictionaries, using a dissymmetrical classifier to conduct performance evaluation, detecting and shifting the testing sample, using the model to conduct defect detection on the software detection module, feeding an evaluation result back to a tester, and completing the detection; then outputting the detection result to a user through the detection result output port. By means of the software defect detecting system based onthe dissymmetrical classified evaluation, the expression capability of the dictionaries can be strengthened, and the software defect detecting system has great discriminating performance; meanwhile,the errors caused by data imbalance are effectively reduced, and software defects are accurately located.