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Android App program evolution change prediction method based on Gaussian process regression

A technology of Gaussian process regression and prediction method, which is applied in the field of prediction of Android App program evolution and change based on Gaussian process regression. It can solve problems such as rough statistics and no calculation evolution process, and achieve easy maintenance and management, detailed prediction results, and optimized prediction results. Effect

Active Publication Date: 2018-10-02
TIANJIN UNIV
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Problems solved by technology

One author proposed an indicator based on evolution. Although the entire evolution process was counted, it only calculated the number of changes, the version number of the first change, and the version number of the last change. It did not calculate the more detailed evolution process. This kind of statistics is too too rough

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  • Android App program evolution change prediction method based on Gaussian process regression
  • Android App program evolution change prediction method based on Gaussian process regression
  • Android App program evolution change prediction method based on Gaussian process regression

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Embodiment Construction

[0042] The invention provides a method for crawling and preprocessing the historical information of software evolution and change, based on the Gaussian process regression model and the optimal prediction window size, mining potential laws in the evolution process, and predicting which classes in the Android App will be released in the new release Changes occur in the version of the class, and finally get a sorted list of changes according to the size of the class changes. In this way, priority testing and in-depth testing can be performed on the classes at the front of the list, saving testing time and cost.

[0043] The present invention proposes a method for predicting the degree of change of Android App variable class. We predict the change tendency class through evolution history information. The prediction framework is divided into two main parts, the data collection stage and the training and prediction stage. The data collection phase includes two sub-phases, data craw...

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Abstract

The invention relates to the fields of software engineering technology and application, and aims to finally output a variable-class sorting list about class change sizes, give a project manager and developers a more granular version evolution result, and save test time and costs. The invention discloses an Android App program evolution change prediction method based on Gaussian process regression.The method includes the following steps: phase 1, carrying out data crawling; phase 2, carrying out data preprocessing; phase 3, obtaining an optimal prediction window size; and phase 4, constructinga Gaussian process regression prediction model, and finally, outputting a next-version class change degree sorting list through the prediction model. The method is mainly applied to software engineering technology occasions.

Description

technical field [0001] The invention relates to the field of software engineering technology and application, in particular to a method for predicting the evolution and change of Android App (Android application) programs based on Gaussian process regression. Background technique [0002] The real world is constantly changing and developing, and when the system environment changes, new requirements will appear. In order to adapt to the needs of changing environments, software systems need continuous maintenance and evolution. Therefore, software evolution is a process in which programs are constantly adjusted to meet new software requirements. However, on the one hand: software maintenance costs usually exceed 50% of the total cost of the software life cycle, and volatile classes in open source products cost developers a lot of time and energy, which also increases project costs. On the other hand: It has been verified that Pareto's Law (Pareto's Law) is also established i...

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Application Information

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IPC IPC(8): G06F11/36
CPCG06F11/3672
Inventor 陈世展张頔楠冯志勇黄科满
Owner TIANJIN UNIV
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