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Open source software reliability modeling method based on random fault introduction

A technology of open source software and modeling methods, applied in software testing/debugging, instrumentation, electrical digital data processing, etc., can solve problems such as missed opportunities and inconformity with the actual situation of open source software

Active Publication Date: 2020-08-04
SHANXI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Second, if software is released too late, opportunities are missed
But the assumption of perfect debugging doesn't match the realities of open source software development

Method used

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  • Open source software reliability modeling method based on random fault introduction
  • Open source software reliability modeling method based on random fault introduction
  • Open source software reliability modeling method based on random fault introduction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0079] Description of Open Source Software Fault Dataset

[0080] The fault dataset used in the present invention is collected from three Apache open source software product projects (https: / / issues.apache.org / jira / issues), such as KNOX, NIFI and TEZ. Every project of open source software has three consecutive releases. The first fault dataset (DS1) collected from the Apache open source software product KNOX project has three subsets, namely KNOX 0.3.0 (DS1-1), knox0.4.0 (DS1-2) and knox0.5.0 (DS1- 3). The second set of fault data collected by Apache open source software product NIFI project has three subsets: NIFI 1.2.0 (DS2-1), NIFI 1.3.0 (DS2-2) and NIFI 1.4.0 (DS2-3). The third fault dataset collected from the TEZ project of Apache open source software products has three subsets: TEZ 0.2.0 (DS3-1), TEZ 0.3.0 (DS3-2), and TEZ 0.4.0 (DS3-3 ). Note that bug attributes in bug tracking systems include type, status, and resolution. The types of failure data we collect inclu...

Embodiment 2

[0092] Model Comparison Criteria

[0093] The present invention uses five model comparison criteria to evaluate the performance of the model.

[0094] 1. Mean Square Error (Mean Square Error, MSE)

[0095]

[0096] and

[0097]

[0098] 2. R-square (R 2 )

[0099]

[0100] 3. The Root Mean Square Error (RMSE)

[0101]

[0102] and

[0103]

[0104] 4.The Theil statistic(TS)

[0105]

[0106] and

[0107]

[0108] 5. Bias

[0109]

[0110] and

[0111]

[0112] In formula (6) ~ formula (14), ψ(t k ) means to time t k Estimate the number of detected faults so far. Λ(tk) means until time t k The number of failures observed so far. n and m denote the sample size of the failure dataset. In equations (7, 10, 12, 14), (n-m) fault points are used to estimate model parameter values, and the remaining fault points are used to calculate predicted values. MSE (MSE predict ), RMSE (RMSE predict ), TS (TS predict ) and Bias(Bias predict ) The sm...

Embodiment 3

[0114] Model performance comparison

[0115] In terms of fitting, 100% of the fault data are used to fit and estimate the model parameter values, and the fitting performance of the models is compared. In terms of prediction, 85% of the fault data is used to fit and estimate the model parameter values, and the remaining fault data (25% of the fault data) is used to compare the model prediction performance.

[0116] It can be seen from Table 6 that using 100% of the data (DS1-1), the proposed model's MSE, R 2 , RMSE, TS and Bais are 49.5, 0.9249, 7.04, 14.9 and 5.95, respectively. The model has better fitting performance than G-O model, DSS model, ISS model, Yamada imperfect adjustment model-2, P-N-Z model, GGO model, Wang model and Li model. The second place is the ISS model with MSE (52.09), R 2 (0.921), RMSE (7.22), TS (15.28), and Bais (6.16). The worst is the Li model, with MSE (178.49), R 2 (0.7292), RMSE (13.36), TS (28.29), and Bais (11.25). When using 100% of the ...

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Abstract

The invention belongs to the technical field of open source software reliability models, and particularly relates to an open source software reliability modeling method based on random fault introduction. According to the invention, the method comprises the steps: employing a stochastic differential equation for simulating a fault introduction process in an open source software development process, establishing a corresponding open source software reliability model, estimating model parameters by adopting a least square estimation (LSE) method, and employing three fault data sets from an Apache open source software project for comparing model performance. Comparison is carried out by using a closed source software reliability model and an open source software reliability model which are completely debugged and incompletely debugged, and the proposed model has optimal fitting and prediction performance. Therefore, the random change of the fault introduced by the open source software isconsidered, and the actual change of the introduced fault in the open source software development process is met. The model can be used as a tool for evaluating the reliability of the open source software, and helps developers or managers to manage and evaluate the software quality in the development process of the open source software.

Description

technical field [0001] The invention belongs to the technical field of open source software reliability models, and in particular relates to an open source software reliability modeling method based on randomly introduced faults. Background technique [0002] In recent decades, with the development of Internet technology, the development methods of open source software have developed rapidly. Compared with traditional closed source software development, open source software is developed and tested by volunteers and users all over the world through the network. Open source software is a dynamic, uncertain, networked and distributed development process. Modern well-known companies and enterprises have open source software development projects. For example, Google, Microsoft, Alibaba, etc., especially some cloud computing and big data application systems are also developed and tested in an open source way. Although open source software development is widely used in the indus...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36
CPCG06F11/3684G06F11/3688
Inventor 王金勇
Owner SHANXI UNIV
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