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 PDFInfo
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- 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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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
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.
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Cited By (1)
| 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)
| 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 |
-
2018
- 2018-11-06 CN CN201811314413.1A patent/CN109460478A/en active Pending
Patent Citations (6)
| 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)
| 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)
| 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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