Method for testing improved host-oriented embedded software white box

An embedded software, white-box testing technology, applied in software testing/debugging directions, can solve the problems of large manpower and material resources, single coverage index, inconvenient use, etc., to achieve the effect of strong versatility

Inactive Publication Date: 2009-11-11
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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AI Technical Summary

Problems solved by technology

[0006] (1) It can only be tested for a single software, such as 51 series embedded software, or ARM embedded software;
[0007] (2) Software reliability evaluation is only an overall concept, predicting the number of software defects, but cannot specifically point out the location of defects;
[0008] (3) The effect of the h

Method used

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  • Method for testing improved host-oriented embedded software white box
  • Method for testing improved host-oriented embedded software white box
  • Method for testing improved host-oriented embedded software white box

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Embodiment Construction

[0020] 1. Workflow

[0021] Attached below figure 1 The workflow of the present invention is described in detail.

[0022] SVM pattern recognition and regression adopt the LibSVM toolkit of support vector machine, which has been integrated into the automated software testing tool developed by us, and users can easily call it.

[0023] Such as figure 1 As shown, the improved host-oriented embedded software white-box testing workflow has the following software testing steps:

[0024] 1.1. The first stage of testing (coarse prediction)

[0025] These include: (1) the code containing known errors is detected and arranged through lexical syntax analysis to obtain attribute invariants containing errors, and the code after removing errors is detected and arranged through lexical syntax analysis to obtain attribute invariants after removing errors; (2) The attribute invariants containing errors described in step (1) and the attribute invariants after removing errors are respective...

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Abstract

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.

Description

technical field [0001] The invention relates to an improved host-oriented embedded software white box testing method, which belongs to the technical field of embedded software testing. Background technique [0002] Software testing is an important means to ensure the correctness of software systems, and it is also a major component of computer software engineering methods and technologies. Although testing cannot prove the correctness of the software system, it finds errors in the software by running selected test cases, and makes the quality of the software reach a satisfactory level by correcting the errors. Therefore, testing is still the main means to ensure software quality for a long time to come. [0003] The Institute of Reliability Engineering of Beihang University proposed an early prediction method of software reliability based on fuzzy neural network, and demonstrated the early prediction model of software reliability based on fuzzy neural network from theory an...

Claims

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Application Information

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IPC IPC(8): G06F11/36
Inventor 刘久富杨振兴孙琳娄坚波李金奎王伟
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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