CN112527671A - Multi-task time sequence conflict detection method based on event stream analysis - Google Patents

Multi-task time sequence conflict detection method based on event stream analysis Download PDF

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CN112527671A
CN112527671A CN202011514108.4A CN202011514108A CN112527671A CN 112527671 A CN112527671 A CN 112527671A CN 202011514108 A CN202011514108 A CN 202011514108A CN 112527671 A CN112527671 A CN 112527671A
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胡逸琳
欧阳昭
于清华
魏冬冬
代晓倩
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Shanghai aerospace computer technology research institute
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    • G06F11/3668—Software testing
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Abstract

The invention discloses a multi-task time sequence conflict detection method based on event stream analysis, which comprises the following steps: s1: constructing an event time slice set of each event processing completion time; s2: constructing a task running time set; s3: determining the relationship of any task in each event calling software architecture to form an event-task relationship set; s4: sequencing tasks called by the time periods of event time slice sets in the event-task relation set according to the sequence to form a task time slice sequence set; s5: calculating the task time occupied by processing each event in the task time slice sequence set, and judging whether the overtime phenomenon occurs or not; and judging whether conflicts exist or not, and outputting the conflicts occurring events and tasks. The method is used for dynamically detecting the software time sequence conflict situation, can accurately position the software time sequence conflict according to the actual application scene of the software, and prompts testers according to the conflict events and tasks.

Description

Multi-task time sequence conflict detection method based on event stream analysis
Technical Field
The invention relates to the technical field of time sequence conflicts in software engineering, in particular to a multi-task time sequence conflict detection method based on event stream analysis.
Background
With the advance of software engineering, when software is implemented in a large-scale system, the same underlying task is called repeatedly in multiple events, and when the same task is called by multiple events at the same time, timing conflicts can be caused to the multiple events, so that the events are delayed to be executed or the events are overtime to be executed.
In the research process, the inventor of the application finds that in the current software test, the time sequence conflict analysis is usually tested by adopting a manual analysis or pressure test method, but for some software with more events and tasks and high time sequence requirement, the time sequence with conflict possibly occurs is sporadic, the manual analysis cannot be fully covered, so that the conflict detection method has low efficiency and is not accurate enough in positioning.
Disclosure of Invention
The embodiment of the application provides a multi-task time sequence conflict detection method based on event stream analysis, which is used for solving the time sequence conflict phenomenon in the existing software engineering system, accurately analyzing and calling each task according to the actual application scene, and ensuring the time sequence conflict accurately so as to prompt testers for conflict events and tasks.
The embodiment of the application provides a multitask time sequence conflict detection method based on event stream analysis, which comprises the following steps:
s1: according to a software sequence and a system environment, an event stream is constructed, and the event name, the event triggering cycle time and the processing completion time of each event in the event stream are determined to form an event time slice set of each event processing completion time;
s2: determining all tasks and the running time thereof in each software architecture according to each software architecture in the software sequence to form a task running time set;
s3: determining the relationship of each event for calling any task in the software architecture according to each software architecture to form an event-task relationship set;
s4: according to the calling task relationships of all events, sorting the tasks called by the time periods of the event time slice set coincidence in the event-task relationship set according to the sequence to form a task time slice sequence set;
s5: calculating the task time occupied by processing each event in the task time slice sequence set, and judging whether the overtime phenomenon occurs or not according to the maximum time of processing each event; and judging whether conflicts exist according to the maximum processing time of the single task, and outputting the events and tasks with the conflicts.
Further, in the step S4, a new task time slice sequence set { M }3In when { M }1When a single event is in the corresponding sequence, recording an event sequence number, an event priority and an event time corresponding to the event.
Further, in the step S4, when { M }3An event in includes { M }2When a plurality of tasks in the system are required, the tasks are respectively recorded in the { M } state2Run time and priority of tasks in.
Further, in the step S4, for { M }1The method for sequencing the event trigger period, the event priority and the event sequence number in the method comprises the following steps:
s41: sequencing the events in sequence from high to low according to the priority of the events;
s42: the events with the same priority are sorted by the event period; wherein, the accidental events are ranked in the front, and the events with shorter periods are ranked in the front;
s43: and the events with the same priority and consistent periods are sequentially sequenced according to the sequence of the sequence numbers.
Further, in the step S5, { M ] is calculated3In (M) }1The method of the time period occupied by each event in the system is as follows:
{M3the execution time of each event in the } is: acquiring a certain time point { M3} in { M3}2For one or more tasks in said { M }2The execution times of one or more tasks in the queue are accumulated.
Further, in the step S5, { M ] is calculated3In (M) }2The method of the time period occupied by each task in the system is as follows:
whenM2Some task in { M }1When a single event in { M } is executed3The start time of the task in the event should be the sum of the accumulations of all task times before the task is executed in the event for a single event start time; the ending time of the task is the accumulated sum of the accumulated time of all tasks before the task is executed in the event of the starting time of a single event;
when { M2Some task in { M }1When a plurality of events in the event are executed, time periods of tasks in the single event are respectively calculated, the cycle time of the event is superposed to be used as the starting time, the time period of the task executed in the event is formed, and then the time periods of the tasks in the events are superposed.
The method for detecting the multi-task time sequence conflict based on the event stream analysis, provided by the embodiment of the application, has the following technical effects:
1. the algorithm complexity is low, is linear and can support large-scale software time sequence analysis.
2. The algorithm is simple to implement, and the process can be deleted according to the application. Such as: if only the conflict exists in the analysis interval, the conflict can be detected and the interruption can be realized.
3. Comprehensive detection data of the time sequence conflict interval can be obtained.
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FIG. 1 is a timing diagram of events in an embodiment of the present application.
Detailed Description
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
The embodiment of the application provides a multitask time sequence conflict detection method based on event stream analysis, which comprises the following steps:
step S1: according to the software sequence and the system environment, an event stream is constructed, and the event name, the event triggering cycle time and the processing completion time of each event in the event stream are determined, so that an event time slice set of each event processing completion time is formed.
In the step S1, the event time slice set { M }1The data structure model of } is: mi 1{ti 1，type，ci，Tk1，Pk1}； wherein ,ti 1Indicating the time when the event should be processed, and type indicating whether the event is a periodic event; when type is an incident, ciA value of 0, Tk1Denotes the k-th event, Pk1Indicating the priority of the event.
Set of event slots { M }1The data structure model of (1) is as table (one), wherein the smaller the priority contract priority value, the higher the priority.
Figure BDA0002844319120000041
Watch 1
Step S2: and determining all tasks and the running time thereof in each software architecture according to each software architecture in the software sequence so as to form a task running time set. In the step, a task running time set is constructed through the running times of all tasks.
In the step S2, the task runtime set { M }2The data structure model of (1) is Mi 2{ti 2，Tk2，Pk2}； wherein ：ti 2Indicating the completion time of task processing, Tk2Indicating the k-th task, Pk2Indicating the priority of the task.
Set of task runtime { M2The data structure model of (b) is as in table (b), where the smaller the priority contract priority value, the higher the priority.
Serial number (Tk) Task name Task time ti Priority Pk
1 Task 1 1 0
2 Task 2 2 0
3 Task 3 5 1
4 Task 4 5 1
5 Task 5 5 2
6 Task 6 2 2
7 Task 7 1 2
Watch 2
Step S3: and determining the relationship of each event for calling any task in the software architecture according to each software architecture to form an event-task relationship set. In the step, the tasks and the events are associated to form a calling relation, and an event-task relation set is constructed.
In step S3, the set of event-task relationships { R }1The data structure model of Ri 1{Tk1，Ma 2，Mb 2，Mc 2,.. }, wherein: tk1Denotes the kth event, Mk 2Represents Tk1Event correspondence { M2The task set model of.
Set of event-task relationships { R }1The data structure model of (c) is as in table (d).
Figure BDA0002844319120000051
Watch (III)
Step S4: and according to the calling task relationships of all events, sequencing the tasks called by the time periods of the event time slice sets in the event-task relationship sets according to the sequence to form a task time slice sequence set.
In step S4, the set of task time slice sequences { M }3The data structure model of } is: mi 3{Mi 1，Ma 2，Mb 2，Mc 2,... wherein Mi 1Representing a corresponding set of current events { M }1Event model of. Of course, Mk 2Representing a corresponding set of current events { M }2And f, setting the value of k as a, b, c and the like.
In one embodiment, inIn step S4, the task time slice sequence set { M }3The set of event slots { M } in1When a single event is in the corresponding sequence, recording an event sequence number, an event priority and an event time corresponding to the event.
In one embodiment, in the step S4, when the task time slice sequence set { M }3An event in includes { M }2When a plurality of tasks in the system are required, the tasks are respectively recorded in the { M } state2Run time and priority of tasks in.
In step S4, referring to fig. 1, the method for sorting according to the sequence includes:
s41: sequencing the events in sequence from high to low according to the priority of the events;
s42: the events with the same priority are sorted by the event period; wherein, the accidental events are ranked in the front, and the events with shorter periods are ranked in the front;
s43: and the events with the same priority and consistent periods are sequentially sequenced according to the sequence of the sequence numbers.
And constructing a task time period according to the event-task relation set, such as a table (IV).
Figure BDA0002844319120000061
Figure BDA0002844319120000071
Watch (IV)
And sorting according to the event priority, the event period and the event sequence number, such as a table (five).
Figure BDA0002844319120000072
Figure BDA0002844319120000081
Watch (five)
Step S5: calculating the task time occupied by processing each event in the task time slice sequence set, and judging whether the overtime phenomenon occurs or not according to the maximum time of processing each event; and judging whether conflicts exist according to the maximum processing time of the single task, and outputting the events and tasks with the conflicts.
In step S5, the method includes calculating a time period occupied by each event in the set of task time slices: the set of task time slice sequences { M }3The execution time of each event in the } is: obtaining the task time slice sequence set { M3At some point in time in the set { M } of task running times2Run time set { M } for one or more tasks in { M } for the task2The execution times of one or more tasks in the queue are accumulated.
In step S5, the method further includes: calculating the time period occupied by each task in the task time slice sequence set:
when task runtime set { M }2In a set of event slots { M } for a certain task1When a single event in { M } is executed, a set of task time slice sequences { M }3The start time of the task in the event should be the sum of the accumulations of all task times before the task is executed in the event for a single event start time; the ending time of the task is the accumulated sum of the accumulated time of all tasks before the task is executed in the event of the starting time of a single event;
when task runtime set { M }2In a set of event slots { M } for a certain task1When a plurality of events in the event are executed, time periods of tasks in the single event are respectively calculated, the cycle time of the event is superposed to be used as the starting time, the time period of the task executed in the event is formed, and then the time periods of the tasks in the events are superposed.
And according to the calling relation of the events and the tasks, obtaining the following table (six) of the linear time of the single event of the task time period, wherein x represents the indefinite time, and n represents the period number.
Figure BDA0002844319120000091
Watch (six)
From the sorting results in table (six), the following timing conflicts can be seen:
1) event C, event D execute timeout.
2) When the event B or C or D occurs simultaneously with the event E, the event E may time out since the task 2 may be executed first at the event B or C or D, causing the task to be occupied and then delayed.
3) When the event B occurs simultaneously with the event E, the beat event E may time out since the task 4 may be executed first at the event B, resulting in a delay after the task is occupied.
4) When the event B occurs simultaneously with the event E, the beat event E may time out since the task 3 may be executed first at the event B, resulting in a delay after the task is occupied.
4) When the event B occurs simultaneously with the event E, the beat event E may time out since the task 3 may be executed first at the event B, resulting in a delay after the task is occupied.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. A multitask time sequence conflict detection method based on event stream analysis is characterized by comprising the following steps:
s1: according to a software sequence and a system environment, an event stream is constructed, and the event name, the event triggering cycle time and the processing completion time of each event in the event stream are determined to form an event time slice set of each event processing completion time;
s2: determining all tasks and the running time thereof in each software architecture according to each software architecture in the software sequence to form a task running time set;
s3: determining the relationship of each event for calling any task in the software architecture according to each software architecture to form an event-task relationship set;
s4: according to the calling task relationships of all events, sorting the tasks called by the time periods of the event time slice set coincidence in the event-task relationship set according to the sequence to form a task time slice sequence set;
s5: calculating the task time occupied by processing each event in the task time slice sequence set, and judging whether the overtime phenomenon occurs or not according to the maximum time of processing each event; and judging whether conflicts exist according to the maximum processing time of the single task, and outputting the events and tasks with the conflicts.
2. The method for detecting the multi-task timing conflict based on the event stream analysis according to claim 1, wherein in the step S1, the event time slice set { M }1The data structure model of } is: mi 1{tj 1，type，cj，Tk1，Pk1}；
wherein ,tj 1Indicating the time when the event should be processed, and type indicating whether the event is a periodic event; when type is an incident, ciA value of 0, Tk1Denotes the k-th event, Pk1Indicating the priority of the event.
3. The method for detecting multi-task timing conflict based on event stream analysis according to claim 1, wherein in the step S2, the task runtime set { M }2The data structure model of (1) is Mi 2{ti 2，Tk2，Pk2}；
wherein ：ti 2Indicating the completion time of task processing, Tk2Indicating the k-th task, Pk2Indicating the priority of the task.
4. The method for detecting multi-task timing conflict based on event stream analysis according to claim 1, wherein in the step S3, the set of event-task relationships { R } is1The data structure model of Ri 1{Tk1，Ma 2，Mb 2，Mc 2，......}；
wherein ：Tk1Denotes the kth event, Mk 2Represents Tk1Event correspondence { M2The task set model of.
5. The method for detecting the multi-task timing conflict based on the event stream analysis according to claim 1, wherein in the step S4, the task time slice sequence set { M }3The data structure model of } is:
Figure FDA0002844319110000021
wherein ,Mi 1Representing a corresponding set of current events { M }1Event model of.
6. The method for detecting the multi-task timing conflict based on the event stream analysis according to claim 3, wherein in the step S4, the task time slice sequence set { M }3The set of event slots { M } in1When a single event is in the corresponding sequence, recording an event sequence number, an event priority and an event time corresponding to the event.
7. The method for detecting the multi-task timing conflict based on the event stream analysis as recited in claim 3, wherein in the step S4, when the task time slice isSet of sequences { M3An event in includes { M }2When a plurality of tasks in the system are required, the tasks are respectively recorded in the { M } state2Run time and priority of tasks in.
8. The method for detecting the multi-task time-series conflict based on the event flow analysis as claimed in claim 3, wherein in the step S4, the method for sorting according to the sequence includes:
s41: sequencing the events in sequence from high to low according to the priority of the events;
s42: the events with the same priority are sorted by the event period; wherein, the accidental events are ranked in the front, and the events with shorter periods are ranked in the front;
s43: and the events with the same priority and consistent periods are sequentially sequenced according to the sequence of the sequence numbers.
9. The method for detecting the multi-task timing conflict based on the event stream analysis according to claim 3, wherein the step S5 comprises calculating the time period occupied by each event in the task time slice sequence set:
the set of task time slice sequences { M }3The execution time of each event in the } is: obtaining the task time slice sequence set { M3At some point in time in the set { M } of task running times2Run time set { M } for one or more tasks in { M } for the task2The execution times of one or more tasks in the queue are accumulated.
10. The method for detecting a multi-tasking timing conflict based on event stream analysis of claim 9, wherein in the step S5, the method further comprises: calculating the time period occupied by each task in the task time slice sequence set:
when task runtime set { M }2In a set of event slots { M } for a certain task1When a single event in { M } is executed, a set of task time slice sequences { M }3The start time of the task in (j) should be accumulated for a single event start timeThe cumulative sum of all task times before the task is executed in the event; the ending time of the task is the accumulated sum of the accumulated time of all tasks before the task is executed in the event of the starting time of a single event;
when task runtime set { M }2In a set of event slots { M } for a certain task1When a plurality of events in the event are executed, time periods of tasks in the single event are respectively calculated, the cycle time of the event is superposed to be used as the starting time, the time period of the task executed in the event is formed, and then the time periods of the tasks in the events are superposed.
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