CN110795351A - Reliability increase testing and evaluating method for component-based star software - Google Patents
Reliability increase testing and evaluating method for component-based star software Download PDFInfo
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Abstract
The invention provides a reliability increase testing and evaluating method for component-based star software. The method is based on a subcomponent operation profile, models are conducted on a trigger excitation source and input probability distribution of the trigger excitation source to generate test data, reliability estimation is conducted according to a test result, and design optimization is further conducted on componentized star affair software to enable the software reliability to meet task requirements.
Description
Technical Field
The invention belongs to the technical field of satellite reliability testing, and particularly relates to reliability growth testing and evaluation of component satellite software for a microsatellite.
Background
With the continuous development of basic technologies such as computer science technology, microelectronic technology, control theory and the like, modern microsatellites tend to develop towards micronano, low power consumption, light weight and software densification, and meanwhile, the proportion of software in the whole satellite occupying all components is also larger and larger.
For software in a satellite, satellite users are primarily concerned about two factors: on the one hand the degree of realization of the software for the overall functional requirements, and on the other hand the quality and reliability of the software. At present, an evaluation method for software function requirement achievement degree is relatively perfect, and generally, in the phases of a single machine docking test, a desktop combined test, a simulated flight test and the like of a satellite, relatively comprehensive function verification, interface test, boundary test and performance test or unit-level, component-level and system-level test verification is performed through conventional software test methods such as unit test, integrated test, system test, third-party evaluation and the like. However, regarding the quality and reliability of software, the current conventional testing means has difficulty in effectively finding potential hazards influencing the reliability of the satellite in software codes, and is more difficult to quantitatively give the reliability testing result evaluation of the whole satellite software.
With the increasing requirement of the current satellite user on the reliability of the whole satellite system, software reliability indexes are already explicitly proposed in software development task books of part satellite models and an effective verification method is required to be provided. Because the currently adopted design mode of the component formation of the star software is still in a starting exploration stage, the component source code has certain unknownness relative to the application mode and the decomposition of the operation section of the component. In a component-based star software design mode, when component source codes are designed, the requirement full envelope of historical satellite models is included, and then when specific satellites are implemented, satellites of different models can cut and increase source codes to a certain extent according to specific tasks. For the change of the code and the component integration, corresponding strategies are still lacked at present, and the reliability verification is carried out on the caused influence. On the other hand, when the componentized software of the complex satellite system runs dynamically, when each component and each sub-component trigger excitation in input/output, the data access interface matching performance also has reliability risks, and the reliability increase test verification method and the quantitative evaluation of the risks are still fuzzy and blind at present.
Disclosure of Invention
The invention provides a reliability growth test and evaluation method for component-based satellite software, which is used for verifying whether a reliability quantitative result of the component-based satellite software meets the requirement of a satellite software reliability index. Meanwhile, modeling analysis is carried out on failure data of the substandard project in the satellite service component reliability increase test so as to evaluate the reliability level of the current software system component and predict the level which can be reached in the future, thereby providing decision basis for a satellite software designer and satellite operation and maintenance.
A reliability growth testing and evaluating method for component-based star service software comprises the following steps:
a reliability growth target value is determined. The target value is used to determine whether to continue the reliability growth test. Analyzing the requirement of the whole satellite task on the satellite affair software to determine the running mode of the software, determining the component failure mode and failure grade criteria, and then determining a target value of the reliability increase according to the reliability index value distributed to each component by the whole satellite affair software;
calculating the occurrence rate of the sub-components. Determining the operation profile of the system, determining the excitation source for awakening the components and the subcomponents, establishing a component and subcomponent activation probability form according to historical test data, determining the activation probability of each subcomponent, and calculating the occurrence rate of the subcomponents by combining the total activation rate of the system components (such as a normal mode or a minimum mode) in a historical random test log;
generating reliability growth test data, comprising:
the simulation generates a reliability growth test input stimulus. According to the attributes of analog quantity and digital quantity or time-varying and time-invariant, the triggering excitation sources of all the house servant subcomponents are statistically analyzed, the input rule of the excitation elements is determined according to historical satellite data, and finally, a corresponding probability distribution model is selected for fitting simulation to obtain a simulation excitation source;
and acquiring test data, decomposing the task operation profile of the satellite component, determining the operation mode of the sub-component, and calculating the potential probability range of the component according to the occurrence probability of the sub-component.
Testing, inputting the generated simulation excitation source according to the calculated potential probability range of the sub-component, executing the test item, storing the output test data in a local log, and uploading the test data to a test data server;
collecting component failure data including failure time and failure count of the collected component;
measuring reliability, namely taking the collected failure data as input of reliability measurement, fitting the change trend of the failure data, selecting a corresponding reliability model or a corresponding combination model, and performing reliability estimation on the average time before failure MTTF, the average time between failures MTBF, the failure rate and the like based on the fitting model;
judging and evaluating, comparing the reliability measurement of the system component obtained in the step with the reliability index requirement, and if the reliability measurement reaches the standard, terminating the test and giving out reliability evaluation; if the standard is not met, the problem is submitted, a software change suggestion is given, and regression testing is carried out after software is modified.
Further, the operating profile includes a normal operating mode and a safe mode.
Further, in the normal operation mode, each component of the star software periodically and circularly operates according to the following sequence: the system comprises a house component, an acquisition component, an orbit component, an attitude determination component, an attitude control component, an energy component, a thermal control component, a remote measurement component, a remote control component and other components.
Further, the excitation source comprises external uplink instruction triggering, housekeeping autonomous control flow triggering and the like. For example, the excitation source of the star component is an operating system or hardware signal trigger, and the excitation sources of the telemetry component, the remote control component and other components are star components, other components or an uplink control command trigger.
Further, the activation probability form includes components, sub-components, and activation probabilities.
Further, the failure data is collected from two dimensions, failure count and failure time. The failure count is the number of failures per unit time, which may be daily, weekly, or monthly. The failure time is the component running time collected by the test front end, and comprises the accumulated execution time or interval execution time of each failure, and the execution time adjusts the clock time calculation through the average utilization factor in the unit clock time.
The reliability growth test and evaluation method for the componentized star affair software analyzes the trigger excitation source and the input probability distribution thereof based on the operation section of the sub-component so as to achieve the purpose of the reliability growth test and evaluation of the componentized star affair software. The testers can quickly expose the reliability weak links or defects of the components formed by the satellite software through the testing and evaluating method, and provide corresponding component system-level reliability evaluation to provide a basis for the reliability increase of the whole satellite.
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To further clarify the above and other advantages and features of embodiments of the present invention, a more particular description of embodiments of the present invention will be rendered by reference to the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. In the drawings, the same or corresponding parts will be denoted by the same or similar reference numerals for clarity.
FIG. 1 illustrates a flow diagram of a reliability growth testing and evaluation method for componentized star software according to one embodiment of the present invention;
FIG. 2 illustrates a star member trigger excitation schematic according to one embodiment of the present invention; and
FIG. 3 is a diagram of an activation probability form, according to one embodiment of the invention.
Detailed Description
In the following description, the invention is described with reference to various embodiments. One skilled in the relevant art will recognize, however, that the embodiments may be practiced without one or more of the specific details, or with other alternative and/or additional methods, materials, or components. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of embodiments of the invention. Similarly, for purposes of explanation, specific numbers, materials and configurations are set forth in order to provide a thorough understanding of the embodiments of the invention. However, the invention may be practiced without specific details. Further, it should be understood that the embodiments shown in the figures are illustrative representations and are not necessarily drawn to scale.
Reference in the specification to "one embodiment" or "the embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.
It should be noted that, in the embodiments of the present invention, the process steps are described in a specific order, however, this is only for convenience of distinguishing the steps, and the order of the steps is not limited, and in different embodiments of the present invention, the order of the steps may be adjusted according to the adjustment of the process.
As shown in fig. 1, a reliability growth testing and evaluating method for a component-based star software includes:
step 101, analyzing the requirement of the satellite service component, determining a failure mode and a failure grade, and determining a reliability increase target value. Firstly, the requirement of the whole satellite task on the satellite affair software is analyzed to determine the running mode of the software and clarify the component failure mode and failure grade criterion. Then, a reliability growth target value is determined according to the reliability index value distributed to each component by the whole star service software. The target value is used as a criterion for judging whether the reliability growth test is continued.
Step 102, constructing a running profile of the star member. And calculating the incidence of each sub-component under different operation profiles.
According to different satellite input excitations, the whole-satellite-level component system comprises two operation profiles of a normal operation mode and a safety mode. In the normal operation mode, all components circularly operate according to the following sequence: the system comprises a house component, an acquisition component, an orbit component, an attitude determination component, an attitude control component, an energy component, a thermal control component, a remote measurement component, a remote control component and other components.
In the safety mode, part of the components are not operated, and the operation sequence of the components is different from the normal operation mode. Therefore, the two operation profiles need different test inputs, and when the reliability increase test is performed, the operation profile needs to be determined first, so that the test input can be generated subsequently;
next, the excitation source for the component and the sub-component to wake up is determined, so that the activation probability of the sub-component can be counted subsequently. The excitation source of the component or the sub-component comprises uplink control instruction triggering, star autonomous control flow triggering and the like. As shown in fig. 2, the star member is activated by an operating system and hardware signal, and the activation of the telemetry member, the remote control member and other members is triggered by mutual release of semaphore or internal command between the star member and other members;
next, the building and sub-building activation probability forms are created. According to historical test data, the probability that each sub-component is triggered by different excitation sources under different operation profiles is counted, then summation calculation is carried out, the activation probability of each sub-component is obtained, and a probability form shown in figure 3 is formed, wherein the probability form comprises component names, sub-component names and activation probability information; it is understood that in other embodiments provided by the present invention, the probability list may also be a graph or any other form containing the three items of information;
finally, the subcomponent incidence A is calculatedi：
Ai＝Bi*C；
Wherein, BiAnd C is the activation probability of the sub-component i, and the activation rate of the current operation section in the historical random test log.
Step 103, generating component test data, including:
the simulation generates a reliability growth test input stimulus. According to the attributes of analog quantity and digital quantity or time-varying and time-invariant, the triggering excitation sources of all the house servant subcomponents are statistically analyzed, the input rule of the excitation elements is determined according to historical satellite data, and finally, a corresponding probability distribution model is selected for fitting simulation to obtain a simulation excitation source;
obtaining test data, decomposing task operation section of the housekeeping component, determining operation mode of the subcomponents and determining occurrence probability A of the subcomponents according to the task operation sectioniCalculating to obtain the potential probability range of the member to which the component belongs
Wherein n is the number of the sub-components included in the component.
Generating test input data according to the calculated component potential probability range.
Step 104, testing, executing the test items, storing the output test data in a local log, and uploading the test data to a test data server;
step 105, testing failure collection, including collecting failure time and failure count of the component, and performing failure propagation and influence domain analysis thereof.
The failure count refers to the number of failures per unit time. The statistical unit time may be daily, weekly, or monthly. The failure time refers to the component running time collected by a testing front end such as a ground testing terminal database, a testing log and the like, and comprises the accumulated execution time or the interval execution time of each failure, wherein the actual execution time is calculated by adjusting the clock time through an average utilization factor in unit clock time;
step 106, reliability estimation, namely, using the collected failure data as input of reliability measurement, fitting the change trend of the failure data, selecting a corresponding reliability model or a corresponding combination model, and performing reliability estimation on the average time before failure MTTF, the average time between failures MTBF, the failure rate and the like based on the fitting model;
step 107, judging whether the reliability meets the index requirement, comparing the reliability measurement of the system component obtained in the step with the reliability index requirement, and if the reliability measurement meets the index requirement, terminating the test and giving out reliability evaluation; if the standard is not met, the problem is submitted, a software change suggestion is given, and regression testing is carried out after software is modified.
While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various combinations, modifications, and changes can be made thereto without departing from the spirit and scope of the invention. Thus, the breadth and scope of the present invention disclosed herein should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
Claims (8)
1. A reliability growth testing and evaluating method for component-based star service software comprises the following steps:
analyzing the requirement of the whole satellite task on the satellite affair software to determine the operation mode, the component failure mode and the failure grade criterion of the software, and then determining the target value of the reliability increase according to the reliability index value distributed to each component by the whole satellite affair software;
determining an operation profile of a system and an excitation source for awakening the components and the subcomponents, establishing a component and subcomponent activation probability form according to historical test data to determine the activation probability of each subcomponent, and calculating the occurrence rate of the subcomponents by combining the total activation rate of the system components in a historical random test log;
statistically analyzing the trigger excitation sources of all the subcomponents, determining the input rule of the excitation source according to historical satellite data, and selecting a probability distribution model for fitting simulation to obtain a simulated excitation source;
calculating a component potential probability range according to the sub-component incidence;
inputting the generated simulation excitation source according to the potential probability range of the component, executing the test item, storing the output test data in a local log, and uploading the test data to a test data server;
collecting a time to failure, and a count of failures of the component;
taking the failure time and the failure count as the input of reliability measurement, fitting the change trend of failure data, selecting a reliability model or a combination model, and calculating the reliability measurement based on the fitting model;
comparing the reliability measurement with the target value of the reliability increase, if the reliability measurement reaches the target value of the reliability increase, terminating the test and giving out reliability evaluation; if the standard is not met, the problem is submitted, a software change suggestion is given, and the regression test is carried out after the software is modified.
2. The method of claim 1, wherein the operating profile includes a normal operating mode and a safe mode.
3. The method of claim 2, wherein in the normal operating mode, the components of the star software periodically cycle in the following order: the system comprises a star affair component, a collection component, a track component, a posture fixing component, a posture control component, an energy component, a thermal control component, a remote measuring component and a remote control component.
4. The method of claim 1, wherein the stimulus sources comprise an operating system trigger, a hardware signal trigger, a star feature trigger, and an up control instruction trigger.
5. The method of claim 1, wherein the activation probability form comprises components, sub-components, and activation probabilities.
6. The method of claim 1, wherein the failure count comprises a number of failures per unit of time, the unit of time being daily, weekly, or monthly.
7. The method of claim 1, wherein the failure time comprises a component runtime collected by a test front end, wherein the component runtime comprises a cumulative execution time or an interval execution time for each failure occurrence.
8. The method of claim 1, wherein the reliability metrics include mean time before failure (MTTF), Mean Time Between Failure (MTBF), and failure rate.
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| CN111679924B (en) * | 2020-04-29 | 2024-03-26 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Reliability simulation method and device for componentized software system and electronic equipment |
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