Flash memory problem positioning method and device, equipment and storage medium

Abstract

The present application belongs to the technical field of flash memory problem positioning, and discloses a flash memory problem positioning method, device, equipment and storage medium, the method comprising: collecting threshold distribution data of key indicators of a faulty flash memory, wherein the key indicators include preset flash memory extension function parameters; inputting the threshold distribution data of the key indicators into an abnormal threshold distribution graph database to obtain a first abnormal threshold distribution graph corresponding to the key indicators in the abnormal threshold distribution graph database; determining a second abnormal threshold distribution graph with the strongest similarity to the threshold distribution data of the key indicators in the first abnormal threshold distribution graph; and determining the problem corresponding to the second abnormal threshold distribution graph as the problem of the faulty flash memory. The present application solves the problems of low positioning accuracy, low efficiency and high cost in positioning flash memory problems in related technology.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of flash memory problem positioning, and particularly relates to a flash memory problem positioning method, device, equipment and storage medium. BACKGROUND

[0002] Flash memory is widely used in many electronic devices due to its advantages of fast read-write speed, low delay, high data integrity, small size, light weight and low power consumption.

[0003] However, in the actual application process of flash memory, flash memory problems occur frequently and diagnosis and solution face many difficulties. On the one hand, due to the lack of a unified standard for determining flash memory problems, different technical personnel will have deviations in determining problems. On the other hand, the manual determination of flash memory problems is inefficient, has no fixed process and clear direction guide, and technical personnel need to rely on personal experience, the trial process is blind and time-consuming, which increases downtime and economic loss. Moreover, when determining that there is a problem with the flash memory, the technical personnel are required to have basic knowledge and extended knowledge of flash memory, and the structure domain principle of flash memory is relatively complex, involving storage unit, charge principle, transformation algorithm and other knowledge. At the same time, the product characteristics of different manufacturers are different, and the adaptation requirements in different scenarios are also different, which leads to a higher requirement for the technical quality of technical personnel, thereby increasing the difficulty of confirming flash memory problems and the cost of personnel.

[0004] To sum up, the related technology needs a flash memory problem positioning scheme to overcome the problems of low positioning accuracy, low efficiency and high cost in positioning flash memory problems in the related technology. SUMMARY

[0005] The application provides a flash memory problem positioning method, device, equipment and storage medium to solve the problems of low positioning accuracy, low efficiency and high cost in positioning flash memory problems in the related technology.

[0006] In order to solve the above technical problems, in a first aspect, the application provides a flash memory problem positioning method, comprising:

[0007] Collecting threshold value distribution data of key indicators of a faulty flash memory, wherein the key indicators include preset flash memory extended function parameters;

[0008] Inputting the threshold value distribution data of the key indicators into an abnormal threshold value distribution graph database to obtain a first abnormal threshold value distribution graph corresponding to the key indicators in the abnormal threshold value distribution graph database;

[0009] Determining a second abnormal threshold value distribution graph with the strongest similarity to the threshold value distribution data of the key indicators in the first abnormal threshold value distribution graph;

[0010] determining a problem corresponding to the second abnormal threshold distribution map as the fault flash memory problem.

[0011] Optionally, before the inputting the threshold distribution data of the key indicator into the abnormal threshold distribution map database, obtaining a first abnormal threshold distribution map corresponding to the key indicator in the abnormal threshold distribution map database, the method further comprises:

[0012] collecting third threshold distribution data of the key indicator when the flash memory is in normal operation, and collecting fourth threshold distribution data of the key indicator when the flash memory has a problem and the flash memory has the problem;

[0013] generating an abnormal threshold distribution map of the key indicator for the problem according to the third threshold distribution data and the fourth threshold distribution data;

[0014] associating the problem with the abnormal threshold distribution map of the key indicator corresponding to the problem to generate an association relationship;

[0015] storing the problem, the abnormal threshold distribution map of the key indicator corresponding to the problem, and the association relationship into the abnormal threshold distribution map database.

[0016] Optionally, the collecting the third threshold distribution data of the key indicator when the flash memory is in normal operation, and collecting the fourth threshold distribution data of the key indicator when the flash memory has a problem and the flash memory has the problem, comprises:

[0017] collecting the third threshold distribution data of a first key indicator when the flash memory is in normal operation, and collecting fifth threshold distribution data of the first key indicator when the flash memory has a historical problem and the flash memory has the historical problem;

[0018] generating sixth threshold distribution data of a second key indicator related to the historical problem, wherein the second key indicator is a flash memory extended function parameter, and the fourth threshold distribution data comprises the fifth threshold distribution data and the sixth threshold distribution data.

[0019] Optionally, the generating the sixth threshold distribution data of the second key indicator related to the historical problem, comprises:

[0020] determining the flash memory extended function parameter related to the flash memory performance and the flash memory problem;

[0021] changing a threshold value of the flash memory extended function parameter, and observing a working state of the flash memory;

[0022] when the flash memory has a fault and the fault is the historical problem, confirming that a threshold value of the flash memory extended function parameter at a current time is the sixth threshold distribution data related to the historical problem.

[0023] Optionally, the determining the flash extended function parameters related to the flash performance and the flash problem comprises:

[0024] observing the change of the value of the preset flash extended function parameter, the change of the performance parameter value of the flash and the working state of the flash;

[0025] determining the preset flash extended function parameter that will cause the change of the performance parameter value of the flash and / or the change of the working state of the flash as the flash extended function parameter related to the flash performance and the flash problem.

[0026] Optionally, the associating the problem and the abnormal threshold distribution diagram of the key indicators corresponding to the problem to generate the association relationship comprises:

[0027] dividing the key indicators into levels based on the hierarchical relationship between the key indicators, wherein the key indicators of a higher level include the key indicators of a lower level;

[0028] setting the key indicators of a higher level to have a higher problem finding order;

[0029] generating the association relationship based on the problem, the abnormal threshold distribution diagram of the key indicators corresponding to the problem and the problem finding order.

[0030] Optionally, the storing the problem, the abnormal threshold distribution diagram of the key indicators corresponding to the problem and the association relationship into the abnormal threshold distribution diagram database comprises:

[0031] tracing the key indicators corresponding to the problem, wherein the trace order is from high to low in the level of the key indicators;

[0032] generating the specific solution corresponding to the problem in stages according to the trace order of the key indicators, wherein each key indicator corresponds to a solution;

[0033] storing the problem, the abnormal threshold distribution diagram of the key indicators corresponding to the problem, the association relationship and the specific solution corresponding to the problem into the abnormal threshold distribution diagram database.

[0034] In a second aspect, the present application provides a flash problem positioning device, comprising:

[0035] a collection module configured to collect threshold distribution data of key indicators of a faulty flash, wherein the key indicators include preset flash extended function parameters;

[0036] The distribution obtaining module is configured to input the threshold value distribution data of the key indicator into an abnormal threshold value distribution database, and obtain a first abnormal threshold value distribution graph corresponding to the key indicator in the abnormal threshold value distribution database;

[0037] The similarity comparison module is configured to determine a second abnormal threshold value distribution graph with the strongest similarity to the threshold value distribution data of the key indicator in the first abnormal threshold value distribution graph.

[0038] The problem determining module is configured to determine a problem corresponding to the second abnormal threshold value distribution graph as the problem of the faulty flash memory.

[0039] In a third aspect, the present application provides a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete the communication among each other through the communication bus.

[0040] The memory is configured to store a computer program.

[0041] The processor is configured to execute the program stored on the memory, and realize the steps of the flash memory problem positioning method provided in the first aspect.

[0042] In a fourth aspect, the present application provides a computer readable storage medium, which stores a readable computer program, and the program is executed by the processor to realize the steps of the flash memory problem positioning method provided in the first aspect.

[0043] Compared with the prior art, the flash memory problem positioning method, device, equipment and storage medium provided by the present application have the following beneficial effects:

[0044] In this invention, when determining the problem of a faulty flash memory, a second abnormal threshold distribution map corresponding to the threshold distribution data of the key indicators of the faulty flash memory is found. The problem corresponding to the second abnormal threshold distribution map stored in the abnormal threshold distribution map database is then taken as the problem occurring in the faulty flash memory. Since the abnormal threshold distribution maps and their corresponding problems stored in the abnormal threshold distribution map database are fixed, a unified judgment standard is provided for determining the problem of the faulty flash memory. This avoids the problem deviation caused by inconsistencies in judgment standards among different technicians, thereby improving the accuracy of faulty flash memory problem localization. Furthermore, this embodiment of the invention considers flash memory extended function parameters when considering key indicators, thus comprehensively covering the influencing factors causing the problem as comprehensively as possible when determining the problem of the faulty flash memory, resulting in higher accuracy of the problem obtained based on these influencing factors. In addition, since the problems are already set in the abnormal threshold distribution map database, it is not necessary to require technicians to analyze the cause of the problem step by step when the flash memory fails, thereby avoiding the inefficiency of manually determining flash memory problems. Furthermore, when identifying problems with faulty flash memory, even if technical personnel are required to make the judgment, they only need to find the second abnormal threshold distribution map corresponding to the threshold distribution data of the key indicators of the faulty flash memory. This does not require technical personnel to have professional knowledge of the system, thus avoiding the problems of low efficiency and high cost in flash memory problem localization caused by the need for technical personnel to have professional knowledge of the system in related technologies. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart of a method for locating flash memory problems provided in an embodiment of the present invention.

[0047] Figure 2 This is another flowchart of the flash memory problem localization method provided in the embodiments of the present invention.

[0048] Figure 3 yes Figure 2 The flowchart for step S121.

[0049] Figure 4 yes Figure 3 The flowchart for step S1212.

[0050] Figure 5 yes Figure 2 The flowchart for step S123.

[0051] Figure 6 is Figure 2 the flowchart of step S124 in

[0052] Figure 7 is a structural schematic diagram of the flash memory problem positioning device provided by the embodiment of the present application.

[0053] Figure 8 is a structural schematic diagram of the computer device provided by the embodiment of the present application.

[0054] Figure 9 is a structural schematic diagram of the computer readable storage medium in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0056] In order to make the description of the present disclosure more detailed and complete, the following describes the embodiments and specific embodiments of the present application; but this is not the only form of implementation or use of the specific embodiments of the present application. The embodiments include the features of the specific embodiments and the method steps and their order used to construct and operate these specific embodiments. However, other specific embodiments can also be used to achieve the same or equivalent functions and step sequences. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0057] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein.

[0058] In addition, in the description of the embodiments of the present application, "a plurality of" means two or more than two, and other quantifiers similar thereto should be understood. The preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application, and the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0059] Figure 1 is a flowchart of a flash memory problem positioning method provided by the embodiment of the present application. As shown in Figure 1 the flash memory problem positioning method can include the following steps.

[0060] In step S110, threshold distribution data of the key indicators of the faulty flash memory is collected.

[0061] The key indicators include preset flash extension function parameters.

[0062] Specifically, in step S110, the faulty flash memory is a flash memory that has failed. The key indicators of the faulty flash memory are indicator parameters that affect the working state of the flash memory, for example, the key indicators can be flash read / write speed, voltage, or error rate, etc. The number of key indicators can be one or more, which can be set according to the specific needs at the time of application, and is not limited in detail here.

[0063] Specifically, the flash extension function parameters are parameters for optimizing the function of the flash memory, which can be set according to the specific needs at the time of application. For example, when it is necessary to improve the read / write performance of the flash memory, the flash extension function parameter can be set as a cache strategy parameter, and then the cache capacity, cache algorithm, and write strategy, etc. can be set reasonably by setting the cache strategy parameter, so as to improve the read / write performance of the flash memory. When it is necessary to reduce the read waiting time of sequential access data, the flash extension function parameter can be set as a data pre-reading parameter, and then the data pre-reading function can be used to predict the data access demand in advance, and possible data can be loaded into the cache or memory in advance. When it is necessary to ensure the reliability of the data stored in the flash memory, the flash extension function parameter can be set as an error correction algorithm strength parameter, and then the error correction algorithm strength parameter value (such as using a higher level error correction code or a suitable error correction algorithm type) can be adjusted to effectively detect and correct errors in the data during storage and transmission.

[0064] Specifically, the threshold distribution data of the key indicators of the faulty flash memory is the value range of one or more key indicators of the flash memory when the flash memory fails.

[0065] In step S130, the threshold distribution data of the key indicators is input into the abnormal threshold distribution graph database, and a first abnormal threshold distribution graph corresponding to the key indicators in the abnormal threshold distribution graph database is obtained.

[0066] It should be noted that in step S130, the first abnormal threshold distribution graph is part or all of the abnormal threshold distribution graph pre-stored in the abnormal threshold distribution graph database. The abnormal threshold distribution graph can be a distribution graph formed by the abnormal value range of one or more key indicators of the flash memory when the flash memory fails in various types of failure problems. In this way, in step S130, after the threshold distribution data of the key indicators is input into the abnormal threshold distribution graph database, the first abnormal threshold distribution graph corresponding to the key indicators can be obtained.

[0067] As a specific example, the abnormal threshold distribution graph database can pre-store abnormal value range distribution graphs (i.e., abnormal threshold distribution graphs) of key indicators such as read-write speed, voltage, error rate, and cache strategy of the flash memory when the flash memory occurs various failure problems, and the key indicators of the current failure flash memory collected in step S110 are read-write speed and cache strategy. Then, after the threshold distribution data of the read-write speed and cache strategy is input into the abnormal threshold distribution graph database in step S130, the abnormal value range distribution of the read-write speed and cache strategy can be selected from the abnormal value range distribution graphs of the key indicators such as the read-write speed, voltage, error rate, and cache strategy of the flash memory as the first abnormal threshold distribution graph.

[0068] Step S140, determining a second abnormal threshold distribution graph with the strongest similarity to the threshold distribution data of the key indicators in the first abnormal threshold distribution graph.

[0069] In step S140, after the first abnormal threshold distribution graph corresponding to the key indicators of the failure flash memory is screened, a second abnormal threshold distribution graph with the closest (i.e., the strongest similarity) value range of the key indicators of the failure flash memory can be further screened.

[0070] Step S150, determining the problem corresponding to the second abnormal threshold distribution graph as the problem of the failure flash memory.

[0071] It should be noted that the abnormal threshold distribution graph database pre-stores abnormal threshold distribution graphs of various problems of the flash memory and key indicators corresponding to the various problems. Specifically, one problem of the flash memory can correspond to abnormal value ranges of multiple key indicators, and different value ranges of one key indicator can also correspond to different problems of the flash memory. The specific situation can be determined according to the actual scene of the various problems of the flash memory, which is not limited here.

[0072] In the scheme provided by the embodiment of the application, when determining the problem of the faulty flash memory, the second abnormal threshold value distribution graph corresponding to the threshold value distribution data of the key indicators of the faulty flash memory is searched, and then the problem corresponding to the second abnormal threshold value distribution graph stored in the abnormal threshold value distribution graph database is taken as the problem occurred by the faulty flash memory. Since the abnormal threshold value distribution graph stored in the abnormal threshold value distribution graph database and the problem corresponding thereto are fixed, when determining the problem of the faulty flash memory, a unified determination standard is provided, and the problem determination deviation caused by the inconsistent determination standards of different technicians is avoided, thereby improving the accuracy of the problem positioning of the faulty flash memory. In addition, when considering the key indicators, the flash memory extension function parameters are considered, so that when determining the problem of the faulty flash memory, the influencing factors causing the problem are as comprehensive as possible, and the accuracy of the problem obtained based on these influencing factors is higher. In addition, since the problem has been set in the abnormal threshold value distribution graph database, when the flash memory fails, technicians are not required to analyze the problem step by step, thereby avoiding the problem of low efficiency of the manual determination of the flash memory problem. Furthermore, when determining the problem of the faulty flash memory, even if the technicians need to determine the problem, the technicians can find the second abnormal threshold value distribution graph corresponding to the threshold value distribution data of the key indicators of the faulty flash memory, and do not need to master the professional knowledge of the system, thereby avoiding the problem of low positioning efficiency and high cost of the flash memory problem in the related art caused by the need for technicians to master the professional knowledge of the system.

[0073] In some embodiments of the application, as shown in Figure 2 Before step S130, the following steps are further included.

[0074] Step S121, collecting third threshold value distribution data of key indicators when the flash memory works normally, and collecting fourth threshold value distribution data of key indicators when the flash memory occurs a problem;

[0075] Step S122, generating an abnormal threshold value distribution graph of the key indicators of the problem according to the third threshold value distribution data and the fourth threshold value distribution data;

[0076] Step S123, generating an association relationship by associating the problem and the abnormal threshold value distribution graph of the key indicators of the problem;

[0077] Step S124, storing the problem, the abnormal threshold value distribution graph of the key indicators of the problem and the association relationship into the abnormal threshold value distribution graph database.

[0078] Specifically, in step S121, the flash memory works normally, which means that the flash memory works without failure. The problem occurred by the flash memory collected in step S121 can be one or multiple.

[0079] Specifically, in step S122, since the third threshold distribution data is the value range distribution of the key indicator when the flash memory works normally, and the fourth threshold distribution data is the value range distribution of the key indicator when the flash memory has a problem, by comparing the third threshold distribution data and the fourth threshold distribution data, the value range distribution of the key indicator that is different from the third threshold distribution data in the fourth threshold distribution data can be naturally determined as the abnormal threshold distribution graph of the problem key indicator.

[0080] Further, based on step S122, one or more abnormal threshold distribution graphs of the problem can be obtained, and then in step S123, the problem of the flash memory and the abnormal threshold distribution graph corresponding to the problem can be associated.

[0081] In this way, based on steps S121-S124, a comprehensive abnormal threshold distribution graph database can be established.

[0082] In some embodiments of the present application, as shown in Figure 3 Step S121 includes the following steps.

[0083] Step S1211, collecting third threshold distribution data of a first key indicator when the flash memory works normally, and collecting fifth threshold distribution data of the first key indicator when historical problems of the flash memory occur;

[0084] Step 1212, generating sixth threshold distribution data of a second key indicator related to the historical problems, wherein the second key indicator is a flash memory extended function parameter, and the fourth threshold distribution data includes the fifth threshold distribution data and the sixth threshold distribution data.

[0085] Specifically, in step S1212, since the flash memory extended function parameter is an extended function parameter formed for optimizing the performance of the flash memory, compared with other key indicators, the flash memory extended function parameter does not have more historical failure scenarios, so other key indicators corresponding to historical problems can be collected in step S1211, and then based on the scenarios of the historical problems, the sixth threshold distribution data of the corresponding extended function parameter can be generated.

[0086] In some embodiments of the present application, as shown in Figure 4 Step S1212 includes the following steps.

[0087] Step S12121, determining a flash memory extended function parameter related to the performance of the flash memory and the problem of the flash memory;

[0088] Step S12122, changing the threshold of the flash memory extended function parameter, and observing the working state of the flash memory;

[0089] Step S12123, when the flash memory fails and the failure is a historical problem, confirming that the threshold of the flash memory extended function parameter at the current time is the sixth threshold distribution data related to the historical problem.

[0090] Specifically, in step S12121, the flash memory extended function parameter related to the flash memory performance and the flash memory problem is determined, that is, the flash memory extended function parameter that can affect the flash memory performance and cause the flash memory to have a problem is determined, and the determination manner is any implementable manner, which is not limited in detail here.

[0091] Further specifically, in step S12122, by changing the threshold of the flash memory extended function parameter, the value range of the flash memory extended function parameter can be changed, and with the change of the value range of the flash memory extended function parameter, the working state of the flash memory can change or can not change, that is, the flash memory can always be in a normal working state or can change from a normal state to a failure state.

[0092] Further specifically, in step S12123, when the flash memory fails and the failure is a historical problem, the threshold of the flash memory extended function parameter when the flash memory fails is determined as the sixth threshold distribution data of the flash memory extended function corresponding to the historical problem.

[0093] In this way, based on steps S12121-S12123, the abnormal threshold distribution data of the flash memory extended function parameter that can cause the historical problem can be generated, so that the flash memory extended function parameter can be comprehensively considered when determining the problem of the failed flash memory.

[0094] In some embodiments of the present application, step S12121 includes:

[0095] observing the change of the value of the preset flash memory extended function parameter, the change of the performance parameter value of the flash memory, and the working state of the flash memory;

[0096] determining the preset flash memory extended function parameter that causes the performance parameter value of the flash memory to change and / or causes the working state of the flash memory to change as the flash memory extended function parameter related to the flash memory performance and the flash memory problem.

[0097] In this way, in the above-mentioned embodiments of the application, the flash memory extended function parameter that can cause the flash memory to have a problem can be accurately determined, so that when the problem of the failed flash memory is determined based on the threshold of the flash memory extended function parameter, the determined problem is more accurate.

[0098] In some embodiments of the present application, as shown in FIG. 12, step S123 includes the following steps. Figure 5

[0099] ​Step S1231, based on the hierarchical relationship between the key indicators, the key indicators are divided into levels;

[0100] Step S1232, set the higher level of the key indicators have higher problem finding order;

[0101] Step S1233, based on the problem, the abnormal threshold distribution of the key indicators corresponding to the problem and the problem finding order, the association is generated.

[0102] Among them, the high-level key indicators include low-level key indicators.

[0103] Specifically, in step S1231, when the key indicators are divided into levels, it is required that the high-level key indicators include the low-level key indicators, that is, the low-level key indicators are the sub-level indicators of the high-level key indicators. For example, the key indicators are read-write speed and sequential read-write speed. Since the read-write speed includes the sequential read-write speed and the random read-write speed, etc., the read-write speed can be set as the high-level key indicator, and the sequential read-write speed and the random read-write speed can be set as the low-level key indicators.

[0104] Further specifically, in step S1232, having higher problem finding order means that when the threshold distribution data of the key indicators of the faulty flash memory is input into the abnormal threshold distribution graph database to obtain the final problem of the faulty flash memory, the higher level key indicators corresponding to the collected key indicators of the faulty flash memory are preferentially searched in the abnormal threshold distribution graph database. For example, if the key indicators of the collected faulty flash memory are random read-write speed, when searching for the key indicators corresponding to the random read-write speed in the abnormal threshold distribution graph database, the read-write speed is preferentially searched, and further the threshold distribution graph corresponding to the random read-write speed is searched in the read-write speed threshold distribution graph.

[0105] It can be understood that based on steps S1231-S1233, when confirming the problem corresponding to the faulty flash memory, the abnormal threshold distribution graph corresponding to the problem is searched step by step, and the problem is finally determined, which avoids searching all abnormal threshold distribution graphs in the abnormal threshold distribution graph database to compare the similarity between the threshold distribution data of the key indicators of the faulty flash memory and the threshold distribution data, thereby effectively improving the problem finding efficiency of the faulty flash memory.

[0106] In some embodiments of the present application, the abnormal threshold distribution graph corresponding to the flash memory device type and the environment parameter value can also be set in the abnormal threshold distribution graph database, wherein the abnormal threshold distribution graph corresponding to the flash memory device type is the device type of the flash memory when the problem occurs, and the abnormal threshold distribution graph corresponding to the environment parameter is the parameter value of the related environment of the flash memory when the problem occurs.

[0107] Further, the device type and the environment parameter can be set to have a higher level than the key indicator, that is, have a higher problem searching order, so that in searching the abnormal threshold distribution graph of the faulty flash memory, the device type and the environment parameter can be searched first, avoiding the need to search all the key indicators of the highest level in the process of searching the problem, thereby effectively improving the problem searching efficiency of the faulty flash memory.

[0108] In some embodiments of the present application, as shown in Figure 6 Step S124 includes the following steps.

[0109] Step S1241, tracing the key indicator corresponding to the problem;

[0110] Step S1242, generating the specific solution corresponding to the problem in stages according to the tracing order of the key indicator;

[0111] Step S1243, storing the problem, the abnormal threshold distribution graph of the key indicator corresponding to the problem, the correlation, and the specific solution corresponding to the problem into the abnormal threshold distribution graph database.

[0112] The tracing order is from high to low in the level of the key indicator. Each key indicator corresponds to a solution.

[0113] Specifically, in step S1242, when the specific solution corresponding to the problem is generated in stages according to the tracing order of the key indicator, more specific solutions can be generated in stages based on the solutions of the key indicators of each level, so that the generated solutions are more reliable.

[0114] Based on the above flash memory problem positioning method, an embodiment of the present application provides a flash memory problem positioning device, as shown in Figure 7 The flash memory problem positioning device includes:

[0115] The acquisition module 710 is configured to acquire threshold distribution data of the key indicator of the faulty flash memory, wherein the key indicator includes a preset flash memory extension function parameter.

[0116] The distribution graph acquisition module 720 is configured to input the threshold distribution data of the key indicator into the abnormal threshold distribution graph database to obtain a first abnormal threshold distribution graph corresponding to the key indicator in the abnormal threshold distribution graph database.

[0117] The similarity comparison module 730 is configured to determine a second abnormal threshold distribution graph having the strongest similarity with the threshold distribution data of the key indicator in the first abnormal threshold distribution graph.

[0118] The problem determination module 740 is configured to determine the problem corresponding to the second abnormal threshold distribution graph as the problem of the faulty flash memory.

[0119] Other details of the modules in the flash problem positioning apparatus for implementing the above technical solutions can refer to the description of the flash problem positioning method provided in the above embodiments, which will not be repeated here. The modules in the flash problem positioning apparatus can be implemented by software, hardware, or a combination thereof, in whole or in part. The modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a memory in the computer device in software form, so as to be called and executed by a processor to perform the operations corresponding to the modules.

[0120] Please refer to Figure 8 A structural schematic diagram of a computer device provided by an embodiment of the present application is shown in FIG. 8. The device includes a processor 801, which can be implemented in a general-purpose central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application. The device also includes a memory 802, which can be implemented in a read only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 802 and executed by the processor 801 to implement the flash problem positioning method of the embodiments of the present application. The device also includes an input / output interface 803, which is used to implement information input and output. The device also includes a communication interface 804, which is used to implement communication and interaction between the device and other devices. The communication can be implemented by a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.). A bus 805 is used to transmit information between various components (for example, the processor 801, the memory 802, the input / output interface 803, and the communication interface 804) of the device. The processor 801, the memory 802, the input / output interface 803, and the communication interface 804 are connected to each other by the bus 805 to implement communication and connection within the device.

[0121] As Figure 9As shown, the embodiment of the present application also provides a structural diagram of a computer readable storage medium, and the storage medium stores a readable computer program 91; wherein the computer program 91 can be stored in the above storage medium in the form of a software product, and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor execute all or part of the steps of the method of each embodiment of the present application. And the foregoing storage medium includes: a U disk, a mobile hard disk, a magnetic or optical disk, a ROM (Read-Only Memory), a RAM (Random Access Memory), and various storage program codes or terminal devices such as computers, servers, mobile phones, and tablets.

[0122] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented by other manners. For example, the above-described device embodiments are only schematic, for example, the division of modules is only a logical function division, and actual implementation can have another division manner, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed modules can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or other forms.

[0123] The modules illustrated as separate components can or can not be physically separate, and the components illustrated as modules can or can not be physical modules, that is, can be located in one place, or can be distributed to a plurality of network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0124] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically, or two or more modules can be integrated in one module. The above integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can be stored in a computer readable storage medium.

[0125] In the above embodiments, all or part of them can be realized by software, hardware, firmware or any combination thereof. When realized by software, all or part of them can be realized in the form of a computer program product.

[0126] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the flow or function according to the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that the computer can store or be integrated into a data storage device such as a server, data center, etc. containing one or more available media. The available media can be magnetic media (for example, floppy disk, hard disk, magnetic tape), optical media, or semiconductor media (for example, solid state disk (SSD)) and the like.

[0127] The above describes the technical solutions provided by the present application in detail. The principles and implementation modes of the present application are described by applying specific examples. The above examples are only used to help understand the method and core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed; in summary, the content of the specification should not be understood as a limitation of the present application.

[0128] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, optical storage, etc.) containing computer usable program code.

[0129] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system) and computer program product of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of the flows and / or blocks in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a machine that implements the flowchart and / or block diagram. Figure 1 one flow or multiple flows and / or blocks Figure 1means for performing the function specified by the block or blocks.

[0130] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 flow or flows and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow Figure 1 flow or flows and / or blocks Figure 1 steps of means for performing the function specified by the block or blocks.

[0132] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for locating a flash problem, the method comprising: The method comprises: collecting threshold distribution data of key indicators of a faulty flash memory, wherein the key indicators include preset flash extension function parameters; inputting the threshold distribution data of the key indicators into an abnormal threshold distribution graph database to obtain a first abnormal threshold distribution graph corresponding to the key indicators in the abnormal threshold distribution graph database; before the inputting, the method further comprises: collecting third threshold distribution data of the key indicators when the flash memory is working normally, and collecting fourth threshold distribution data of the key indicators when the flash memory has a problem and the flash memory has the problem; generating an abnormal threshold distribution graph of the key indicators of the problem according to the third threshold distribution data and the fourth threshold distribution data; associating the problem with the abnormal threshold distribution graph of the key indicators corresponding to the problem to generate an association relationship; storing the problem, the abnormal threshold distribution graph of the key indicators corresponding to the problem, and the association relationship into the abnormal threshold distribution graph database; the associating comprises: dividing the key indicators into levels based on a hierarchical relationship between the key indicators, wherein a higher-level key indicator includes a lower-level key indicator; setting a higher-level key indicator to have a higher problem finding order; generating the association relationship based on the problem, the abnormal threshold distribution graph of the key indicators corresponding to the problem, and the problem finding order; determining a second abnormal threshold distribution graph in the first abnormal threshold distribution graph that has the strongest similarity to the threshold distribution data of the key indicators; and determining a problem of the faulty flash memory as a problem corresponding to the second abnormal threshold distribution graph.

2. The method of claim 1, wherein, The collecting comprises: collecting the third threshold distribution data of a first key indicator when the flash memory is working normally, and collecting fifth threshold distribution data of the first key indicator when the flash memory has a historical problem and the flash memory has the historical problem; generating sixth threshold distribution data of a second key indicator related to the historical problem, wherein the second key indicator is a flash extension function parameter, and the fourth threshold distribution data includes the fifth threshold distribution data and the sixth threshold distribution data.

3. The method of claim 2, wherein, The generating the sixth threshold distribution data of the second key indicator related to the historical problem comprises: determining the flash extension function parameter related to flash performance and a flash problem; changing a threshold value of the flash extension function parameter and observing a working state of the flash memory; when the flash memory has a fault and the fault is the historical problem, confirming that a threshold value of the flash extension function parameter at a current time is the sixth threshold distribution data related to the historical problem.

4. The method of claim 3, wherein, The determining the flash extended function parameters related to the flash performance and the flash problem comprises: observing the change of the performance parameter value of the flash and the working state of the flash when the value of the preset flash extended function parameter changes; determining the preset flash extended function parameter that will cause the change of the performance parameter value of the flash and / or will cause the change of the working state of the flash as the flash extended function parameter related to the flash performance and the flash problem.

5. The method of claim 1, wherein, The storing the problem, the abnormal threshold distribution graph of the key indicator corresponding to the problem and the association relationship into the abnormal threshold distribution graph database comprises: tracing the key indicator corresponding to the problem, wherein the tracing order is from high to low according to the level of the key indicator; generating the specific solution corresponding to the problem according to the tracing order of the key indicator, wherein each key indicator corresponds to a solution; storing the problem, the abnormal threshold distribution graph of the key indicator corresponding to the problem, the association relationship and the specific solution corresponding to the problem into the abnormal threshold distribution graph database.

6. An apparatus for locating a flash memory problem, the apparatus being configured to implement the steps of the method for locating a flash memory problem according to any one of claims 1-5, characterized in that, Comprise: The acquisition module is used for collecting the threshold distribution data of the key indicator of the fault flash memory, wherein the key indicator comprises a preset flash extended function parameter; The distribution graph acquisition module is used for inputting the threshold distribution data of the key indicator into the abnormal threshold distribution graph database to obtain a first abnormal threshold distribution graph corresponding to the key indicator in the abnormal threshold distribution graph database; The similarity comparison module is used for determining a second abnormal threshold distribution graph with the strongest similarity to the threshold distribution data of the key indicator in the first abnormal threshold distribution graph; The problem determination module is used for determining the problem corresponding to the second abnormal threshold distribution graph as the problem of the fault flash memory.

7. A computer device, comprising: The device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete the communication among each other through the communication bus; The memory is used for storing a computer program; The processor is used for executing the program stored on the memory to realize the steps of the flash problem positioning method in any one of claims 1-5.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the flash problem positioning method in any one of claims 1-5.

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