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54 results about "Software measurement" patented technology

Software measurement is a quantified attribute (see also: measurement) of a characteristic of a software product or the software process. It is a discipline within software engineering. The process of software measurement is defined and governed by ISO Standard ISO 15939 (software measurement process).

Method for evaluating implementation quality of software process

InactiveCN101710304AFlexible indicator organizationCovering the whole life cycleSoftware testing/debuggingImplementation qualityComputer Software Engineering
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.
Owner:INST OF SOFTWARE - CHINESE ACAD OF SCI

Automated open-source software quality evidence extraction method

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.
Owner:NAT UNIV OF DEFENSE TECH

Software defect prediction method based on two-stage wrapping-type feature selection

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.
Owner:南京瑞沃软件有限公司

Phosphoric acid production parameter control method based on gradient boosted decision tree

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.
Owner:上海新增鼎数据科技有限公司

Data processing method and device

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.
Owner:LE SHI ZHI ZIN ELECTRONIC TECHNOLOGY (TIANJIN) LTD

Controlling method of improving current quality of grid-connected inverter during low-load operation

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.
Owner:黄山科创中心有限责任公司

Intelligent detection system for ammonia gas in cowshed environment based on wireless sensor network

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.
Owner:恩施硒盈生态养殖有限公司

SAW (Surface Acoustic Wave) sensor based embedded electronic nose testing system and testing method

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.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Large-scene inclined image three-dimensional reconstruction zone partitioning method

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.
Owner:五维智能信息科技(北京)有限公司

Software defect detecting system based on dissymmetrical classified evaluation

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.
Owner:XIAMEN UNIV OF TECH
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