CN109460478A - System interface timing knowledge analysis method based on fine granularity Feature Semantics network - Google Patents

System interface timing knowledge analysis method based on fine granularity Feature Semantics network Download PDF

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Publication number
CN109460478A
CN109460478A CN201811314413.1A CN201811314413A CN109460478A CN 109460478 A CN109460478 A CN 109460478A CN 201811314413 A CN201811314413 A CN 201811314413A CN 109460478 A CN109460478 A CN 109460478A
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interface
timing
failure
fine granularity
granularity feature
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王佳佳
李娜
张晛
杨楠
王颖
唱明旭
张依漪
王栋
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Beijing Jinghang Computing Communication Research Institute
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Beijing Jinghang Computing Communication Research Institute
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/02Knowledge representation; Symbolic representation
    • G06N5/022Knowledge engineering; Knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/36Preventing errors by testing or debugging software
    • G06F11/3668Software testing
    • G06F11/3672Test management
    • G06F11/3692Test management for test results analysis

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  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
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  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
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  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computer Hardware Design (AREA)
  • Quality & Reliability (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
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Abstract

The invention belongs to technical field of software engineering, and in particular to a kind of system interface timing knowledge analysis method based on fine granularity Feature Semantics network comprising: building embedded system test fault set;The searching interface critical issue in embedded system test fault set, analysis extract failure relevant to timing, preliminarily form the relevant interface fault collection of timing;The failure with sequential key is searched in embedded system test fault set, analysis is extracted and interface related failure, forms interface related timing failure collection;Two fault sets merge to form interface sequence fault set;Interface sequence key influence factor is extracted using the method based on fine granularity Feature Semantics network according to the fault type in timing failure library, forms Interface of Embedded System timing knowledge collection.Thus obtained Interface of Embedded System timing knowledge can realize the succession of knowledge on testing, and have scalability, convenient for the push of knowledge on testing, promote testing efficiency.

Description

System interface timing knowledge analysis method based on fine granularity Feature Semantics network
Technical field
The invention belongs to technical field of software engineering, and in particular to a kind of system based on fine granularity Feature Semantics network connects Mouth timing knowledge analysis method.
Background technique
In engineer application, software quality majority is evaluated by software test.According to statistics, it is surveyed in the software of profession In test-run a machine structure, in 567 tested softwares, the problem of discovery includes code issue, document problem, sequence problem, interface problem Deng totally 31958, and the description of these problems in style, in linguistic organization, user traditionally there is biggish difference, into When row relevant issues are retrieved, since the diversity of description causes to omit bulk information, test failure problem is carried out total It is imperative to form knowledge on testing for knot.
At present for the summary of knowledge on testing, by the way of manually summarizing, description scheme between knowledge on testing is loose, Relevance is low, lacks inheritance, is not easy to the understanding of user, the maintenance of knowledge on testing, and causing test experience can not inherit, and surveys The problem of examination efficiency can not be promoted effectively.It is tight that knowledge on testing description may be implemented in the method indicated using traditional semantic network Gather, relevance is strong, has the problem of inheritance, but the granularity of the representation of knowledge is lack of consistency, and leads to knowledge in use, easy The case where in the presence of omitting, the reason of failure can not be accurately positioned.
Summary of the invention
(1) technical problems to be solved
The technical problem to be solved by the present invention is how to solve to lack system in field of software engineering in software test procedure Knowledge guidance, engineering technology experience inheriting difference problem.
(2) technical solution
In order to solve the above technical problems, the present invention provides a kind of system interface timing based on fine granularity Feature Semantics network Knowledge analysis method, described method includes following steps:
Step 1: building embedded system test fault set;
Step 2: the relevant critical failure of searching interface in embedded system test fault set, in interface related key Failure relevant to timing is extracted in analysis in failure, forms the relevant interface fault collection of timing;
Step 3: critical failure relevant to timing is searched in embedded system test fault set, in the relevant pass of timing Analysis extraction and interface related failure, form interface related timing failure collection in key failure;
Step 4: the relevant interface fault collection of timing and interface related timing failure collection being merged to form interface sequence event Barrier collection;
Step 5: according to the fault type in interface sequence fault set, utilizing the side based on fine granularity Feature Semantics network Method extracts the relevant key influence factor of interface sequence, forms Interface of Embedded System timing knowledge collection.
Wherein, described embedded system test failure centrally stored the problem of causing testing system software to break down;
The problem of specifically including the failure for encountering in test process, collecting failure title, problem description, problem class Type.
Wherein, described problem type is divided into procedural problem, code issue, document problem, sequence problem, interface problem, often The type of a problem belongs to one of which.
Wherein, in the step 2, the failure in embedded system test fault set is retrieved, search key " connects Mouthful ", after collecting with interface related critical failure, failure relevant to timing is filtered out, forms the relevant interface event of timing Barrier collection.
Wherein, in the step 3, the failure in embedded system test fault set is retrieved, search key " when Sequence ", will after relevant to timing critical failure collects, filter out with interface related failure, form interface related timing therefore Barrier collection.
Wherein, in the step 5, using the knowledge representation method based on fine granularity Feature Semantics network, in interface Data characteristic, functional characteristic are indicated, and extract data integrity, data validation, time-constrain satisfaction property, Multi-task Concurrency Key factor in terms of conflict, break sequence reasonability and shared data and access conflict is further extracted fine granularity feature and is made For the object that semantic network indicates, Interface of Embedded System timing knowledge collection is formed.
Wherein, the fine granularity feature of the data integrity is that data length, data frame losing, transmission byte and reality are different It causes.
Wherein, the fine granularity feature of the data validation is verification and judgement, the judgement of serial ports return value, sends data mark Will setting, data validity judgement.
Wherein, the fine granularity feature of the time-constrain satisfaction property is clock phase shift, data transmission time-out, cycle match Property.
Wherein, the fine granularity feature of the Multi-task Concurrency conflict is multithreading conflict, read/write dual port RAM conflict
Wherein, the rational fine granularity feature of the break sequence designs for interrupt response, interrupts initialization order;It is described Shared data and the fine granularity feature of access conflict are buffer status, FIFO empty/full state.
(3) beneficial effect
Compared with prior art, the method that the present invention uses fine granularity Feature Semantics network knowledge representation, can solve Above-mentioned problem of the prior art positions the level of Semantic Network Knowledge Representation to the most fine granularity of problem failure, so that being based on The timing knowledge that semantic network indicates more standardizes, and is convenient for the reason of failure is accurately positioned, promotes the practicability of timing knowledge.
Technical solution of the present invention can be solved effectively to lack in current software test procedure and known by taking abovementioned technology The problem of knowledge is instructed promotes Efficiency of Software Testing, reduces similar failure and occur convenient for testing the summary of Heuristics and integrating, Improve the safety of software.
Detailed description of the invention
Fig. 1 is method flow diagram provided by technical solution of the present invention.
Fig. 2 is method flow diagram provided by the embodiment of the present invention 1.
Fig. 3 is method flow diagram provided by the embodiment of the present invention 2.
Specific embodiment
To keep the purpose of the present invention, content and advantage clearer, with reference to the accompanying drawings and examples, to of the invention Specific embodiment is described in further detail.
To solve problem of the prior art, when the present invention provides a kind of system interface based on fine granularity Feature Semantics network Sequence knowledge analysis method, as shown in Figure 1, described method includes following steps:
Step 1: building embedded system test fault set;
Step 2: the relevant critical failure of searching interface in embedded system test fault set, in interface related key Failure relevant to timing is extracted in analysis in failure, forms the relevant interface fault collection of timing;
Step 3: critical failure relevant to timing is searched in embedded system test fault set, in the relevant pass of timing Analysis extraction and interface related failure, form interface related timing failure collection in key failure;
Step 4: the relevant interface fault collection of timing and interface related timing failure collection being merged to form interface sequence event Barrier collection;
Step 5: according to the fault type in interface sequence fault set, utilizing the side based on fine granularity Feature Semantics network Method extracts the relevant key influence factor of interface sequence, forms Interface of Embedded System timing knowledge collection.
Wherein, described embedded system test failure centrally stored the problem of causing testing system software to break down, The problem of according to being encountered in the evaluation and test nearly 10 years test process of mechanism;
The problem of specifically including the failure for encountering in test process, collecting failure title, problem description, problem class Type.
Wherein, described problem type is divided into procedural problem, code issue, document problem, sequence problem, interface problem, often The type of a problem belongs to one of which.
Wherein, in the step 2, the failure in embedded system test fault set is retrieved, search key " connects Mouthful ", after collecting with interface related critical failure, failure relevant to timing is filtered out, forms the relevant interface event of timing Barrier collection.
Wherein, in the step 3, the failure in embedded system test fault set is retrieved, search key " when Sequence ", will after relevant to timing critical failure collects, filter out with interface related failure, form interface related timing therefore Barrier collection.
Wherein, in the step 5, using the knowledge representation method based on fine granularity Feature Semantics network, in interface Data characteristic, functional characteristic are indicated, and extract data integrity, data validation, time-constrain satisfaction property, Multi-task Concurrency Key factor in terms of conflict, break sequence reasonability and shared data and access conflict is further extracted fine granularity feature and is made For the object that semantic network indicates, Interface of Embedded System timing knowledge collection is formed.
Wherein, the fine granularity feature of the data integrity is that data length, data frame losing, transmission byte and reality are different It causes.
Wherein, the fine granularity feature of the data validation is verification and judgement, the judgement of serial ports return value, sends data mark Will setting, data validity judgement.
Wherein, the fine granularity feature of the time-constrain satisfaction property is clock phase shift, data transmission time-out, cycle match Property.
Wherein, the fine granularity feature of the Multi-task Concurrency conflict is multithreading conflict, read/write dual port RAM conflict
Wherein, the rational fine granularity feature of the break sequence designs for interrupt response, interrupts initialization order;It is described Shared data and the fine granularity feature of access conflict are buffer status, FIFO empty/full state.
Embodiment 1
The present embodiment specifically describes the interface sequence knowledge analysis method for data validation.
As shown in Fig. 2, this method comprises:
Step 1: building embedded system test fault set provides embedded system test fault set.For test process In the failure that encounters, the problem of collecting failure title, problem description, problem types, form embedded system test fault set.
Step 2: failure relevant to timing is extracted in the searching interface problem in embedded system test fault set, analysis, Preliminarily form the relevant interface fault collection of timing.The problems in embedded system test fault set type is retrieved, and search is closed Key word " data ", " interface " after collecting the problem related to data-interface, filter out the problem related to timing, when formation The relevant data-interface fault set of sequence.
Step 3: failure relevant to timing is searched in embedded system test fault set, analysis is extracted related to interface Failure, form interface related timing failure collection, the problems in embedded system test fault set type is retrieved, search Keyword " data ", " timing " after collecting the problem related to data time sequence, filter out and interface related problem, formation Interface related data time sequence fault set.
Step 4: the relevant interface fault collection of timing and interface related timing failure collection merge to form interface sequence failure Collection;
Step 5: being mentioned according to the fault type in timing failure library using the method based on fine granularity Feature Semantics network Interface sequence key influence factor is taken, Interface of Embedded System timing knowledge collection is formed.
Using the knowledge representation method based on fine granularity Feature Semantics network, to the data validation key in interface because Element forms Interface of Embedded System timing knowledge collection.
Embodiment 2
The present embodiment specifically describes the interface sequence knowledge analysis method for data validation.
As shown in figure 3,
Step 1: building embedded system test fault set provides embedded system test fault set.For test process In the failure that encounters, the problem of collecting failure title, problem description, problem types, form embedded system test fault set.
Step 2: failure relevant to timing is extracted in the searching interface problem in embedded system test fault set, analysis, Preliminarily form the relevant interface fault collection of timing.The problems in embedded system test fault set type is retrieved, and search is closed Key word " time ", " interface " after collecting the problem related to time interface, filter out the problem related to timing, when formation The relevant time interface fault set of sequence.
Step 3: failure relevant to timing is searched in embedded system test fault set, analysis is extracted related to interface Failure, form interface related timing failure collection, the problems in embedded system test fault set type is retrieved, search Keyword " time ", " timing " after collecting the problem related to time timing, filter out and interface related problem, formation Interface related time timing failure collection.
Step 4: the relevant interface fault collection of timing and interface related timing failure collection merge to form interface sequence failure Collection;
Step 5: being mentioned according to the fault type in timing failure library using the method based on fine granularity Feature Semantics network Interface sequence key influence factor is taken, Interface of Embedded System timing knowledge collection is formed.
It is crucial to the time-constrain satisfaction property in interface using the knowledge representation method based on fine granularity Feature Semantics network Factor forms Interface of Embedded System timing knowledge collection.
To sum up, the present invention is directed to the failure that Interface of Embedded System timing encounters during the test, belongs to soft project Quality and reliability technical field.To solve to lack systematic knowledge guidance, engineering technology experience inheriting in software test procedure The problem of difference, the present invention provides a kind of method that knowledge on testing is summarized, step includes: building embedded system test failure Collection, provides embedded system test fault set;In embedded system test fault set key issues of searching interface, analysis is mentioned Failure relevant to timing is taken, the relevant interface fault collection of timing is preliminarily formed;It is searched in embedded system test fault set The crucial failure with timing etc., analysis extract with interface related failure, form interface related timing failure collection;Timing is related Interface fault collection and interface related timing failure collection merge to form interface sequence fault set;According to the event in timing failure library Hinder type, using the method based on fine granularity Feature Semantics network, extracts interface sequence key influence factor, form embedded system System interface sequence Knowledge Set.The Interface of Embedded System timing knowledge that the technical solution obtains can realize the succession of knowledge on testing, And there is scalability, convenient for the push of knowledge on testing, promote testing efficiency.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, without departing from the technical principles of the invention, several improvement and deformations can also be made, these improvement and deformations Also it should be regarded as protection scope of the present invention.

Claims (11)

1. a kind of system interface timing knowledge analysis method based on fine granularity Feature Semantics network, which is characterized in that the side Method includes the following steps:
Step 1: building embedded system test fault set;
Step 2: the relevant critical failure of searching interface in embedded system test fault set, in interface related critical failure Failure relevant to timing is extracted in middle analysis, forms the relevant interface fault collection of timing;
Step 3: critical failure relevant to timing is searched in embedded system test fault set, in the relevant crucial event of timing Analysis extraction and interface related failure, form interface related timing failure collection in barrier;
Step 4: merging the relevant interface fault collection of timing and interface related timing failure collection to form interface sequence fault set;
Step 5: being mentioned according to the fault type in interface sequence fault set using the method based on fine granularity Feature Semantics network The relevant key influence factor of interface sequence is taken, Interface of Embedded System timing knowledge collection is formed.
2. special as described in claim 1 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is, described embedded system test failure centrally stored the problem of causing testing system software to break down;
The problem of specifically including the failure for encountering in test process, collecting failure title, problem description, problem types.
3. special as claimed in claim 2 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that described problem type is divided into procedural problem, code issue, document problem, sequence problem, interface problem, each problem Type belong to one of which.
4. special as described in claim 1 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is, in the step 2, retrieves to the failure in embedded system test fault set, search key " interface ", will After collecting with interface related critical failure, failure relevant to timing is filtered out, forms the relevant interface fault collection of timing.
5. special as described in claim 1 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is, in the step 3, retrieves to the failure in embedded system test fault set, search key " timing ", will After relevant to timing critical failure is collected, filter out with interface related failure, form interface related timing failure collection.
6. special as described in claim 1 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is, special to the data in interface using the knowledge representation method based on fine granularity Feature Semantics network in the step 5 Property, functional characteristic be indicated, extract data integrity, data validation, time-constrain satisfaction property, Multi-task Concurrency conflict, Key factor in terms of break sequence reasonability and shared data and access conflict further extracts fine granularity feature as semantic The object of network representation forms Interface of Embedded System timing knowledge collection.
7. special as claimed in claim 6 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that the fine granularity feature of the data integrity is that data length, data frame losing, transmission byte and reality are inconsistent.
8. special as claimed in claim 6 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that the fine granularity feature of the data validation is that verification and judgement, the judgement of serial ports return value, transmission Data Labels are set It sets, data validity judgement.
9. special as claimed in claim 6 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that the fine granularity feature of the time-constrain satisfaction property is clock phase shift, data transmission time-out, cycle match.
10. special as claimed in claim 6 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that the fine granularity feature of the Multi-task Concurrency conflict is multithreading conflict, read/write dual port RAM conflict.
11. special as claimed in claim 6 based on the system interface timing knowledge analysis method of fine granularity Feature Semantics network Sign is that the rational fine granularity feature of break sequence designs for interrupt response, interrupts initialization order;The shared number According to and the fine granularity feature of access conflict be buffer status, FIFO empty/full state.
CN201811314413.1A 2018-11-06 2018-11-06 System interface timing knowledge analysis method based on fine granularity Feature Semantics network Pending CN109460478A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114237621A (en) * 2021-12-20 2022-03-25 重庆大学 Semantic code searching method based on fine-grained common attention mechanism

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103514079A (en) * 2012-06-15 2014-01-15 波音公司 Failure analysis validation and visualization
CN104807639A (en) * 2015-04-23 2015-07-29 广西大学 Fault diagnosis method and device for rolling bearing of running gear of locomotive
CN105224440A (en) * 2015-09-02 2016-01-06 上海斐讯数据通信技术有限公司 A kind of log collection management method and system
CN108038049A (en) * 2017-12-13 2018-05-15 西安电子科技大学 Real-time logs control system and control method, cloud computing system and server
CN108537259A (en) * 2018-03-27 2018-09-14 北京交通大学 Train control on board equipment failure modes and recognition methods based on Rough Sets Neural Networks model
CN108632086A (en) * 2018-04-19 2018-10-09 山东省计算中心(国家超级计算济南中心) A kind of concurrent job operation troubles localization method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103514079A (en) * 2012-06-15 2014-01-15 波音公司 Failure analysis validation and visualization
CN104807639A (en) * 2015-04-23 2015-07-29 广西大学 Fault diagnosis method and device for rolling bearing of running gear of locomotive
CN105224440A (en) * 2015-09-02 2016-01-06 上海斐讯数据通信技术有限公司 A kind of log collection management method and system
CN108038049A (en) * 2017-12-13 2018-05-15 西安电子科技大学 Real-time logs control system and control method, cloud computing system and server
CN108537259A (en) * 2018-03-27 2018-09-14 北京交通大学 Train control on board equipment failure modes and recognition methods based on Rough Sets Neural Networks model
CN108632086A (en) * 2018-04-19 2018-10-09 山东省计算中心(国家超级计算济南中心) A kind of concurrent job operation troubles localization method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
胡浩: ""一种基于概率神经网络建立电气系统故障的分类方法"", 《科技创新与应用》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114237621A (en) * 2021-12-20 2022-03-25 重庆大学 Semantic code searching method based on fine-grained common attention mechanism

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