RU128741U1 - SYSTEM FOR FORMING SOLVING PROBLEMS OF FUNCTIONING COMPUTER SYSTEMS - Google Patents

Abstract

1. A system for generating a solution to problems in the functioning of computer systems, including a server, which at the same time contains: (a) a means for generating solutions stored in memory and executed on the server processor, designed to: - obtain a solution for the category of problems recorded in a given format on the computer a user connected to the server and writing the resulting solution to the database; - finding solutions for the mentioned category of problems in the database; - comparing the resulting solution in terms of quality with those found in the process of said search in the database for solutions; and at the same time, the mentioned decision making tool is associated with the solution testing tool and the database; (b) the solution testing tool stored in memory and executed on the server processor, designed to execute decisions received and stored in the database in various hardware and software configurations in order to determine the quality indicators of the mentioned solutions and record the quality indicators in the database, while the mentioned solution testing tool is associated with Zoe data; (c) a database stored in the server's memory, designed for the orderly storage of categories of problems, decisions, rules by which a decision is associated with a category of problems and solutions of quality indicators; 2. The system according to claim 1, which additionally contains decision-making means stored in memory and executed on the server processor, designed to: - collect system information from at least one user connected to the server computer, which determines the category of problems and configuration

Description

Technical field

This utility model relates to systems for technical support of users and more specifically to systems for generating solutions to functioning problems and correcting errors that occur in computer systems of users.

State of the art

The level of quality and convenience of technical user support is an important indicator in the characterization of a technological product. One type of technical support is finding solutions in the knowledge base without the intervention of a technical support specialist or expert. In such services implemented to date, solutions to the problems encountered are documents in electronic format (texts and / or graphic images), often combined into knowledge bases. These documents can be articles, help files, user instructions, and more.

To find the necessary information to identify and fix problems, the user has to spend a lot of time studying documents that may not be related to the product or its version that interests the user. Often, the user may not be aware of the reasons that caused this or that malfunction, or he may not have enough qualifications to determine the appearance of deterioration in the operation of the system.

There are systems that analyze the state of a computer system and detect problems or errors. Such systems are described, for example, in patents US6845474, US5740354 and applications JP2006350955A2, JP2000322267A2. However, they are not able to automatically fix the existing problem.

Another type of system, for example, which is described in US5058113, allows you to detect an error in a remote computer system and correct it using known rules. However, these rules are signals, and to determine the presence of an error requires a period of time during which the system is monitored. Moreover, some of the problems may not be accompanied by error reports, which significantly narrows the scope of this system.

At the moment, there are no systems that can determine the presence of problems, classify a problem, offer the most effective options for achieving a positive result and, if possible, apply this option. Existing systems also lack the functions of creating rules and decisions that users can add.

This utility model eliminates the described disadvantages and allows you to quickly and efficiently solve the problem of restoring the correct functioning of user computer systems.

Utility Model Essence

This utility model is intended to formulate solutions to functioning problems and correct errors that occur in users' computer systems.

The technical result of this utility model is to automatically generate solutions to functioning problems and correct errors. The application of the utility model in practice makes it possible to increase the reliability of computer systems on which they are installed and which are connected to a system for generating solutions to problems in the functioning of computer systems. The technical result is achieved by automatically generating and adding users new solutions that can fix the problem on the computer systems of other users. The utility model described below allows you to detect a problem, potential problem or error, choose the most optimal set of solutions, apply them automatically taking into account the rating of solutions and the user profile, as well as fix new problems, their solutions and create new rules and solutions.

The system for generating solutions to problems in the functioning of computer systems consists of: (a) means for generating new solutions designed to obtain a new solution for a category of problems recorded in a given format on a user’s computer connected to a server, searching for solutions for the mentioned category of problems in a database, comparison according to the quality indicators of the new solution with the solutions found in the process of the said search in the database; (b) means for testing solutions designed to execute new and stored in the database solutions in various hardware and software configurations with the aim of determining the quality indicators of the solutions and recording the quality indicators in the database; (c) a database intended for the orderly storage of categories of problems, solutions, rules by which a solution is put in line with the categories of problems, and indicators of the quality of solutions.

In an embodiment, the system for generating a solution to problems in the functioning of computer systems comprises a decision making tool for collecting system information from a user computer connected to the server, by which the category of problems and the configuration of the user computer are determined, and a list of solutions is created from the database corresponding to the mentioned category of problems and applicable to the aforementioned configuration of the user's computer, while the list of solutions is sorted by rating of solutions and transfer solutions from the generated list of solutions to said computer of the user in an ordered manner.

The implementation option also contains a database, which additionally contains tables for orderly storage of user profiles, including at least system information of the user's personal computer, information about problems encountered, decisions made on the user's personal computer and solutions added by the user;

There is an implementation option in which the decision maker downloads the user profile from the database to account for it in the formation of the decision list.

An example implementation of the system processes system information, which includes the software and hardware configurations of the user's computer, event logs, application report files, error information, the status of the central processor, the status of the random access memory, the status of network devices.

In one implementation option, the rating of solutions is calculated by the number of applications of the solution, and the more the number of solutions to problems in users' computer systems using this solution, the higher its rating.

The solution testing tools in various implementations are a set of virtual machines with various hardware and software configurations and user computers designed to test the application of the solution in the hardware and software configuration of the said virtual machines and said user computer, respectively.

Various implementation options use quality indicators to evaluate decisions, including rating decisions, decision effectiveness.

Brief description of the attached drawings

The accompanying drawings, which are included to provide an additional understanding of the utility model and form part of this description, show embodiments of the utility model and, together with the description, serve to explain the principles of the utility model.

The claimed utility model is illustrated by the following drawings, in which:

Figa, 1b and 1c show possible installation options for the system on the technical support server and the client computer system.

Figure 2 shows the separation of components when installing the system on a technical support server and when installing on a client computer system.

Figa shows a structural diagram of a system for forming a solution to the problems of functioning of computer systems.

Fig. 3b shows a general diagram of a server in which a utility model is implemented.

Figure 4 shows a block diagram of a problem solving algorithm.

5 shows a block diagram of a private decision adding algorithm.

5a includes sets of particular solutions with general system parameters and general solutions to problems.

Fig.5b shows a block diagram of a decision search algorithm using fuzzy logic.

6 shows a selection scheme from a database of rules and decisions taking into account the user profile.

7 shows the relationship of problems and solutions using logical rules.

Fig. 8a shows a solution search scheme for a new problem in a given subcategory.

Fig. 8b shows a rule generation diagram for new solutions related to a specific error category of problems.

Figure 9 shows the sequence of solving complex problems using nested decision chains.

10 shows an example of a general purpose computer system, personal computer, or server.

Description of Preferred Embodiments

The objects and features of the present utility model, methods for achieving these objects and features will become apparent by reference to exemplary embodiments. However, the present utility model is not limited to the exemplary embodiments disclosed below, it can be embodied in various forms. The essence described in the description is nothing more than specific details for helping a specialist in the field of technology in a comprehensive understanding of a utility model, and the present utility model is determined only in the scope of the attached formula.

The tool for solving system problems is a complex structured system consisting of several tools. This system is necessary to provide user support. In various embodiments, the described tool can be installed on a client system, on a remote server, or distributed between a client system and a remote technical support server.

On figa, 1b, 1c shows three examples of services with different architectures. Fig. 1a describes an example when a problem solving tool is installed in a client system. This option allows you to support and fix problems without connecting to the Internet, but it has a drawback - the solutions may be outdated, because they can only be updated by installing a new system that includes this service. With such an implementation, client 100 is called a “thick” client, and the service is implemented as a quick user support module 110. The implementation may be a help file (for example, in .chm format) for the installed application. Fig. 1b describes a more complex implementation structure in which service functions are distributed between the client 100 and the server 130. A quick user support module 110 is installed in the user system, which has the necessary functions to find and fix the problem encountered in this system. In this form, the client system is identical to the system shown in Fig.1A. A number of functions, such as updating solutions, user profiles, adding new solutions, an expanded knowledge base is available thanks to server 130 with the installed quick support database 120. The service can be used in this example, either using a connection to the server via the Internet or without it . A third possible way of executing the support tool of FIG. 1c is to install on the server 130 quick support for users 140, accessed through web applications such as a browser. Using the server of fast support of users is possible only when connected to the Internet. At the same time, there are positive aspects, which include the lack of the need to install a support module in the client system, reducing the cost of computing resources, saving all the functions that the service provides, shown in Fig.1b. An example of a system with the architecture shown in FIG. 1B is a technical support web page. The modules shown in FIGS. 1a-c may have their own databases (not displayed). Data can also be stored in files of various formats.

Depending on the type of installation of the problem-solving system, the configuration of the client and server tools may vary. Figure 2 shows the structural separation of the problem-solving system between the client 100 and the server 130. When the service is fully installed in the client system 100, it contains the following components: a local decision database 201, data collection tool 202, decision-making tool 203, decision-making tool 204, solution adding tool 205, solution checking tool 206 and a database of decision checking rules 207. In the case when the system architecture involves the inclusion of a server, some functions are supplemented and / or supported in the server 130 quick support LCDs and are implemented in the following tools: decision database 211, data collection tool 212, decision tool 213, decision execution tool 214, new solution generation tool 215, decision verification tool 216, decision verification rule database 217, decision statistics database 218 , user profile database 219, solution testing tool 220. Some of the tools described in FIG. 2 are duplicated in the client and server, but their function may vary. The server has a large supply of computing resources, respectively, is able to store more information and process it with more complex algorithms. As an example, consider the database of solutions 211 and the local database of solutions 201. Both databases are not functionally different and are designed to store problems, solutions and rules by which one or another solution is selected. At the same time, the database installed on the server is capable of storing a much larger amount of data and process it, while the local database contains only information for a specific version of the user system. The statistics database is designed to store all the characteristics of the solutions obtained by taking into account the application of each solution. For example, the number of applications of the solution, the number of effective applications, the breakdown of the number of applications according to the user's geolocation, etc. Next, the function of the service and the relationship of its components will be described in more detail.

The structural diagram of the problem-solving formation system is shown in FIG. 3. If system failures or other problems occur, the data collector 300 scans the user system. This process includes the collection of internal reports, magazines, program settings, as well as analysis of installed programs and tools in the system. For example, a data collection tool may obtain the following system information:

- Error codes

- program version

- License Information

- Date updated anti-virus databases

- Program reports

- User action log

- System configuration (software and hardware)

One of the most important reasons for automatic categorization of a problem is the error value returned by the program (explicit categorization). The list of errors contains information about the type of problem in advance, and can serve as one of the components of the final categorization. The following are some types of errors specific to anti-virus protection tools (for example, Kaspersky Internet Security 2011) that users encounter while using programs.

[Licensing] - unknown error

[Licensing] - key in the black list

[Licensing] - databases are out of date

[Activation] - the number of legal users has been exceeded

[Activation] - server name not found

[Activation] - the key file is locked

[Activation] - activation code does not match this application

[Licensing] - license is invalid

[Activation] - the key has expired

[Licensing] - invalid activation date

[Activation] - proxy server is unavailable

[Detection] - cannot cure file

[Conflict] - application crashed

[Conflict] - conflict with the application

Errors can occur not only in applications and services, such as anti-virus, but also in operating systems (system services, drivers, etc.). Information about them can also be used to categorize problems.

An important fact for determining the category of a problem is the place where the described system is launched. For many products, it is possible to embed a function call point in the product dialog box. For example, for an antivirus in the Create Crash Copy dialog box, you can embed a service call point. If the service was called from this point, then with a high degree of probability we can assume that the user had a problem with creating an emergency backup task.

Further, the collected data goes to the decision-making tool 310. The main task of the decision-making tool is to choose the most useful and productive solution for the user system. To do this, it classifies the problem - defines the category of the problem according to certain parameters. Suppose the user has a problem with updating the anti-virus databases, in this case there are two possible reasons: the end of the license agreement and the lack of access to the update north. Each of these conditions will indicate at least a category of problems related to updating the databases. In case of difficulties with file treatment, data about this will be recorded in the antivirus log, which determines the category of "file treatment problems".

Next, a query is created in the database of rules and decisions 320, where, from all records, a selection is made for a given problem and / or category of problems. Solutions have a certain rating. After applying this or that decision, it is determined whether it helped or not. Depending on the result of the re-examination or survey, the rating increases or decreases, respectively. The ratings of the solutions are stored in the statistics database 218. Sorting the decisions by rating allows you to apply the most effective troubleshooting suggestions, which are also specialized for this particular user system.

The application of the solution provides a means of execution of decisions 350, which is an interpreter of machine instructions, if the decision is enclosed in a script file. Application of the solution may also consist in playing media files (flash, audio or video) or text information or in downloading an executable file, depending on the format in which the solution is specified. A solution may also be a link to a software update, a link to a patch program, or a link to a media file that demonstrates how to restore functionality.

As noted earlier, there is also the possibility of replenishing the decision database with users or third-party experts called experts. To do this, the system provides a means of adding solutions 340, which creates a solution in a standardized way. Decision Checker 350 prevents false decisions or, moreover, decisions that could harm users' computers from entering the system. There are two options for this tool - checking the solution file and emulating the behavior of the solution. 360 decision verification rules are a separate structure in the system. For each user, a profile is created that contains a set of identification data and system parameters, a log that stores a history of problems encountered, applied solutions and resolved problems. Profiles allow you to individualize the work of the support tool and optimize it. The database of profiles 219 stores data of users using this service.

The following categories of problems can be distinguished as the main ones (for anti-virus protection tools):

- the product activation process ended with an error;

- a malicious object has been detected and cannot be deleted;

- antivirus databases are outdated, and there is a problem with updating them;

- not the last assembly of the product is installed on the user's computer;

- there were problems with installing / uninstalling the product;

- Vulnerabilities of installed software were detected;

- other similar problems that occur when using the product.

Consider the mechanism for finding and applying the solution, which is shown in Figure 4. The process is initiated by a request to solve the problem 400. The request is compiled and sent automatically in case of deviation of the system performance from the norm or is initiated by the user.

There are two possible options for the development of events: with the use of intelligent search for solutions and without its application. The service can also be configured for a consistent solution to the problem - with the use of intelligent search for solutions, and then without it. In the case of the use of intelligent search, the system data is collected, analyzed, and the standard problem 420 is identified. The standard problem is understood as the already known and classified problem, which is stored in the service’s memory. Automatic search may be unsuccessful, in this case the system allows you to search for problems on the list of categories. It also collects 410 data for a more accurate search. The next step after choosing a problem category, taking into account the data obtained, is to search for suitable solutions 425. Each solution has its own rating, which is calculated by statistical indicators, which allows you to sort 430 solutions found by statistics (by rating). Next, at step 435, the sequential application of the solutions occurs. If the decision with the highest rating does not correct the adverse situation, the following decision is applied in descending order. A similar cycle 435-450, consisting of checking the effectiveness of the solution, changing the statistics of the solution and applying the next solution, if one exists, is repeated until a positive result is achieved or until all solutions corresponding to this problem are applied. After applying each solution, the statistics of this solution are updated: the rating rises when the solution helps and the rating decreases otherwise. If after going through the search for solutions by selecting the category of the problem and using the intelligent search, the problem remains unresolved, a request is made to the expert 455, consisting of the collected data about the system and the measures taken. The request is recorded in the database as a problem that needs to be resolved. The process ends with the exit from the system 465 after sending the request to the expert or after a satisfactory result of applying the solution.

Fig. 7 shows an example of rules that relate conditions (parameters of a user's computer system and solutions. The presented flowcharts allow a more detailed description of the decision-making process for a particular problem. A database of rules and solutions stores records of problems 700, divided into classes ( categories) 710 and solutions 720, as well as rules 740, according to which each category of problems is assigned several solutions 730. Moreover, the number of solutions for one category of problems can be zero, one, two and ogre The solution can be attributed to several problems, that is, several problems can be solved in one way. For example, in Fig. 7, the rule determined that the solution "a" can help to fix problems "1" and "6" But the rule did not find solutions for problem category “2,” while three possible solutions were defined for category “5.” The rules for determining solutions are created by the expert in the process of training the system — it indicates the correct and incorrect solutions, exposes causal relationships and control pairs meters characterizing the sample and an appropriate decision. Creating a rule by an expert for each particular problem and each particular solution will lead to the appearance of a fair amount of such rules and, as a result, to overflow of memory and lack of resources to search and store these rules. One implementation option in which this drawback is absent is a decision-making tool with an algorithm based on fuzzy logic rules and the ability to generate new rules and decisions due to private decisions received from users.

To increase the speed of data exchange between users and quickly supplement the database of solutions, the described system allows users to add solutions in an automatic mode. In the event that the user has detected deviations from the norm in the system operation or the system has signaled to him and the user knows how to eliminate them, he is invited to create a solution to this problem on his own and upload it to the database of rules and solutions. The user who performs this procedure is called an expert. The process of adding solutions is depicted in the form of a flowchart in FIG. 5. The beginning of this process is the request to add a solution at step 500. In order to standardize the format of the rules, it is worth identifying the problem at step 505 - assign it to a certain category using the information received from the data collection tool 300. At step 510, the decision generator starts - the tools included in the solution adding means 340, which at step 515 records the actions of the expert in a machine-readable language. This process is called macro recording. In order to prevent the recording of a malicious, erroneous, unqualified solution, two stages of verifying the solution code are proposed: directly during recording at step 520 and based on the results of testing the solution (steps 530, 535). If the decision does not meet the safety rules and / or quality standards, the decision is corrected or not saved (step 525). Security rules are access rights to files, processes, etc., and the quality standard refers to performance indicators, compatibility of programs and devices, etc. For verification, you can use various methods for testing solutions, for example, using user computers. When decisions successfully pass both stages of verification, they are stored in the decision database in the table for added decisions at step 540, the user rating is changed in the user profile database at step 545, and the process ends at step 550. As a result, the number of useful decisions increases and increases probability and speed of achieving a positive outcome. The procedure for adding solutions involves saving information received from the user in the following format:

User System Information Set of recorded troubleshooting instructions

The added solution contains the state of the system and instructions for fixing the problem created by the solution generator, and is a private solution. The state of the system is represented by a set of system parameters with their values. The value of the parameter may or may not be set. The value is absent if this parameter cannot characterize this system configuration, for example, when a connection to the network is not established in the user's computer and network port status parameters cannot be obtained. The probability of absolute coincidence of the source data for several users is very small, which makes this record practically inapplicable. In order to transform a particular solution into a solution that will be effectively used in many user systems (hereinafter referred to as a general solution), the algorithm shown in FIG. 5a is applied. Private decisions of users 561, 571, 581 are accumulated in the database. They consist of a set of system parameters X 562, 572, 582 and a set of instructions A and B, which are indicated in FIG. 5a by numbers 563, 573, 583. The accumulated private decisions are compared they are combined with each other, forming a common solution and the rule by which it is put in correspondence with the problem. Comparison can be carried out by all known methods, for example, by checksums. The result of the comparison is a quantitative measure characterizing the degree of coincidence of two sets of parameters or two sets of instructions. Thresholds for the values of these degrees, above which the sets are considered similar, are set by experts.

We consider two cases of correspondence of particular solutions. The first case occurs when the instruction sets of two particular solutions are considered similar. In this case, the installed system parameters corresponding to these solutions are compared. Missing (undefined) parameters are ignored during comparison. As a result, a rule is formed that defines the investigative relationship between the general set of system parameters, which is the intersection of two initial sets of parameters, and sets of instructions in particular solutions. This rule is stored in the database of rules and decisions.

For example, X1 = {x1, x2, x3, x4} and X2 = (x1, x2, x3, x4, x5}, where x1-x5 are the installed system parameters, and A1 = A2, where A1 and A2 are matching sets of instructions solving problems enclosed in X1 and X2, respectively, then the rule will look like this:

IF [X = {x1, x2, x3, x4}] THEN [A1, A2],

where [A1, A2] is a list of solutions consisting of solutions A1 and A2.

The similarity of the system parameter sets is the second special case, which involves the creation of a rule that defines the relationship between the augmented set of system parameters and each set of instructions in particular solutions. An augmented set of parameters is understood as one in which the differing values of the parameter complement each other. This parameter has two or more values, depending on the number of parameter values in the source sets.

For example, X1 = {x1, x2, x3, x4} and X2 = {x1, x2, x3, x4 '}, where x1-x4, x4' are the set parameters of the system, and A1 ≠ A2, where A1 and A2 are different sets of instructions that solve the problems contained in X1 and X2, respectively. Then the rule will look like this:

IF [X = {x1, x2, x3, x4 or x4 '}] THEN [A1, A2],

where [A1, A2] is a list consisting of solutions A1 and A2.

When the number of system parameter values in the rule reaches a relatively large value, the set can be extrapolated to the function. This step can help predict potential problems, reduce the number of rules, and simplify data storage. An example of such forecasting can be the case in which the antivirus conflict occurs with several versions of the application, for example, with versions 1.0, 1.1, 1.2. In this case, X1 = 1.0, X2 = 1.1, X3 = 1.2. It can be assumed that the conflict can be encountered with version 1.3.

Fig. 5b shows an example implementation of a decision determination algorithm based on fuzzy logic. The algorithm is to determine the rules for fixing problems in the user's computer system. At step 591, the data collection tool 300 collects information about the user system: operating system, software and hardware configuration, application reports, etc. At step 592, there is a transition from particular system parameters to fuzzy problems - linguistic variables (terms). This process is a classification of problems and thereby dividing them into categories. For example, the following terms correspond to a set of parameters with values:

Parameter and its value Term Class of problems App Last Updated Date = The application was updated: 3 days ago Recently - 1 week ago Long Problems with updating CPU utilization = Loading: 10% Weak - fifty% Average - 90% Strong Application conflict; Virus treatment

At step 593, the fuzzy rules from the rules and decisions database 320 are mapped to fuzzy variables. As a result, after matching, a rule will be found that matches a particular fuzzy variable. The rule contains a link to a set of solutions or to a parameter that characterizes each solution and is saved as metadata, thereby at step 593 a type of solutions will be established that is able to correct an existing problem according to a given rule. For transition to clear variables, there is step 594, at which decisions of this type are located in the base of melon rules and decisions. Next, at step 595, the found solutions are transferred for execution. The application of the solution is made on the client side, by reproducing the solution. Decisions can be transferred via the http protocol or any other data transfer protocol, using a specially installed software agent, etc.

Another example of adaptive decision-making is shown in Fig. 8a. The drawing shows a database of rules and decisions 320, in which problems 700 are divided into categories, subcategories, and sections. Each problem corresponds to a set of solutions 710. If a problem is found for which there are no solutions in the database, it is assumed that for similar problems there may be the same solutions. Problem “B” is given as an example, which is in the same subcategory as problems 700 “A” and “B”. The relevant rules defined the solution sets 710: {X1, X2, X3} for the problem "A", {Y1, Y2, Y3} for the problem "B" and an empty solution set for "B". In this case, an adaptive set of solutions 720 is constructed, which contains solutions to the problems of its subcategory. The result of this algorithm will be the rule:

IF ["B"] THEN [X1, Y1, X2, Y2, X3, Y3]

In this example, the solutions to problems “A” and “B” alternate, however, the sequence can be selected depending on the rating of the solution, its simplicity, etc.

The user may have complex problems that cannot be unambiguously classified. They are divided into several simpler problems and are solved sequentially. The following situations can be examples of complex problems:

- when solving the problem of treating the virus, it may turn out that it is necessary to solve the problem of updating the anti-virus databases;

- if a situation arises when the application is an antivirus and the anti-virus signature database is damaged, it may be necessary to restore the antivirus program, scan for viruses, update the program to the latest version, depending on current conditions. All of these nested solutions - solutions to problems discovered during the correction of the original task, can be offered both in parallel and sequentially, one after another.

- in a situation where an application, such as an antivirus, does not start, there may be a need to proceed with the removal of incompatible software, perform a virus scan, update the program to the latest version.

The progress of solving complex problems is shown in Fig.9. There is a chain of solutions to Problem “A” 900, which consists of individual rated solutions. In the course of applying solutions, it becomes necessary to solve another problem “B”, which is called embedded in this case. Chains of embedded solutions 910, 920, 930, 940 are also sorted by rating. After fixing the nested problems, the process returns to the next step in order to solve the problem “A”. The number of attachments is limited by the number of subcategories of problems currently known and stored in the database of rules and solutions. The process ends when the positive result is achieved or all proposed solutions are tried. In this example, to solve problem "A", four nested problems had to be solved. In total, the example shows the use of fifteen different solutions. Each decision chain is sorted by feature and contains decisions that take into account the user's computer parameters and data from his profile: the history of the application of decisions, the level of knowledge of the user, etc.

A solution in the general case is a set of data, guided by which it is possible to prevent or correct a malfunction in a computer system. There are many different options for presenting solutions for computer systems, which include text documents, media files (audio, video, animation), a program patch (patch), configuration files, scripts. Each type of solution can complement or replace the others, for example, to solve a problem, you need to run a script, but so that the problem does not occur again, it is recommended to install a fix for the product or for the operating system. The use of each type of solution is not always possible due to differences in user operating systems and other circumstances. The most common way is to support using text documents. The positive side of this method is accessibility for all users, ease of editing and ease of use. With the development of technology, richer ways to support users with the use of video, audio and other media formats appear. However, documents in this format, as well as text documents, cannot be applied automatically. Let us consider the solution options, the implementation of which does not require user action - these are updates, additions or corrections to the program or system as a whole using special patch tools. These tools can be installed in the user's system and thereby eliminate system problems. Corrections are created by experts and added to the solution database. Another variety of solutions may be a scenario - a sequence of instructions in machine language that can be executed by the system without any user intervention. The difficulty in implementing the scenarios is that not all components have key functionality - there is no control interface. Configuration files allow you to apply system settings, but there is a problem similar to the problem of using scripts.

Taking into account the user's computer settings can significantly improve the quality of the provided support service. In some ways, individualization is a necessary factor for effective problem solving. Rules that allow us to identify useful solutions, i.e. the use of which is possible in this system and with a certain degree of probability will lead to a positive effect, use the parameters obtained from the user's computer. Consideration of parameters is the main function of individualization. The functionality is complemented by features such as:

- Keeping a user's history (saving emerging problems, solutions that turned out to be useful, added solutions, program settings, etc.);

- Choice of the level of knowledge (presentation of solutions in accordance with the level of knowledge of the user: beginner, advanced and expert levels);

- User rating (ranking users by the quality and number of added solutions, the frequency of use of the service), etc.

The user's knowledge level is set, for example, by the user himself, by default as an entry-level or is based on other settings. If the application settings are different from the standard, the user is considered an expert. A detailed description of the categorization of users is reflected in the application under the number RU 2009142890.

Table number 1 User type Presentation level Decision First level plain Detailed description of the sequence of actions Advanced level average Indication of system settings and description of the sequence of actions Expert level complicated Specifying specific system settings

Table 1 shows an example of the correspondence between knowledge levels and data presentation levels. For users with an initial level of knowledge, a description of the solution will be accompanied by a detailed description of the sequence of actions. An advanced user will have access to more compact comments indicating the system settings and a description of the sequence of actions. It is usually enough for an expert to provide the most necessary information that he understands and knows how to apply it.

Figure 6 shows the structural diagram of the individualization of the service. The data collection tool scans the system and determines its parameters: name, version and serial number of the application 610; type, license key and expiration date of license 620; country and language of localization 630; the date and number of the anti-virus database update is 640. The decision-making tool 600 takes into account the data collected and selects rules and decisions from the database of 320 — filters only those that correspond to these parameters from the entire list of decisions. As a result, if the user has the antivirus application of the N-th version with the latest anti-virus databases and a valid license key, the decision-maker will offer a solution specifically for this N-th version of the product and exclude from the list of solutions problems associated with unlicensed use and outdated anti-virus databases .

In the general case, the actions of the system can be arranged in the following sequence: (a) an event is detected (if the event can be identified, an error code, a problem class, etc.) are determined; (b) actions on the system are recorded in the log, which is analyzed to determine the error, system failure, preceding application conflict, application malfunction, user actions (incorrect settings, incorrect actions, such as allowing the execution of malicious code, disabling the protection program, etc. .d.); (c) application of fuzzy logic rules for system parameters and determination of possible solutions; (d) application of solutions taking into account sorting by rating and personalization; (e) adding a new private solution and checking it.

On figb shows a diagram of the formation of the decision and the rules for this decision. The figure shows the solutions correcting error No. 12345 890: “solution 1” 850, “solution 2” 860, “solution 3” 870. As described above, the error number categorizes the problem. By the error number, you can determine what happened to the user - it is impossible to cure the file or it is impossible to write / read memory, an error in the program and more. At the same time, sets of system parameters were fixed at which this problem was fixed - parameters X1-X4 (820-823). On figb displays the relationship of the parameters and solutions that allow you to determine the effective correction of the problem for this set of parameters.

Dotted arrows set the rules: the relationship between parameters and errors can be ambiguous. There are cases when for a particular case there is no solution. For example, error No. 12345 890 that occurred in a computer system with parameters X4 823 at the moment cannot be corrected using these connections, while an error in system X2 821 can be solved immediately in two ways. In the set of rules presented as an example, there is redundancy - an error in the system X1-X3 (820-822) can be corrected using two of the three known solutions. Accordingly, comparing the ratings of the solutions, one of them can be deleted, for example, “Solution 3” 870. FIG. 8b also shows the “New Solution” 880. It can be added to the database by an expert or generated using the algorithms described in this document. The “New Solution” 880 may be the union, addition, or intersection of several well-known solutions in order to increase its effectiveness and applicability. It is known that it allows to fix the Error No. 12345 890, but in order to determine the rating of a solution, the efficiency of its work on computer systems with various system parameters, testing of the solution is necessary. The testing process can take place automatically on user computer systems or in a virtual space in which various sets of parameters are modeled - for example, various versions of the OS, processors, user applications, network interfaces, etc. After the test results are obtained, the new solution is compared with other known solutions and their metadata on the effectiveness and applicability of the solution. For example, if the “New Solution” 880 corrects error No. 12345 890 in all private systems X1-X4 (820-823) and is less resource intensive than others, its rating will be the highest and it will be applied first turn.

The general server diagram in which the utility model is implemented is shown in Fig. 3b. Database 380 stores solutions; their meta data; rules by which decisions are made to correct the corresponding errors and functioning problems. The server allows you to replenish this database by generating new rules (optimization of existing rules); test solutions to determine the compatibility of solutions with system parameters: software and hardware components of the user's computer system and determine the rating for new solutions; as well as for the formation of a sequence of decisions, sorted by rating and personalized according to the user's profile, in response to the collected system information. Solution Generator 365 processes the solution created by the expert, searches for similar solutions and solutions for this category of problems (for a given error), and then compares these solutions by rating, compatibility and analyzes the redundancy of solutions. Based on these indicators, the primary rating level for new solutions is affixed. New solutions go through a testing phase in the 370 Solution Testing Tool to determine compatibility and performance level on computers with different settings and characteristics. Compatibility, level of effectiveness, rating and other possible characteristics of solutions together constitute indicators of the quality of decisions. This tool 370 can be implemented in various ways, for example, as a set of virtual machines with different characteristics. If the error is fixed in a particular virtual machine, the solution is considered compatible with these parameters. The greater the number of compatible computer systems, the greater the efficiency. As an extension of the functionality, the resource-intensiveness of the solutions is estimated: time, memory, computing resources necessary for the execution of the solution. Test results affect the rating of solutions: the greater the efficiency and less resource consumption, the higher the rating. There is an implementation option in which testing the solution is transferred to the side of users. In the event of a problem, a new solution is sent, after which the results are returned, which are processed and entered into the database. The search for solutions for users is carried out by decision making tool 375, described in detail earlier.

10 is an example of a general purpose computer system, personal computer, or server 20 comprising a central processor 21, a system memory 22, and a system bus 23 that contains various system components, including memory associated with the central processor 21. The system bus 23 is implemented like any bus structure known in the art, which in turn contains a bus memory or a bus memory controller, a peripheral bus and a local bus that is capable of interacting with any other bus architecture d. The system memory contains read-only memory (ROM) 24, random access memory (RAM) 25. The main input / output system (BIOS), contains the basic procedures that ensure the transfer of information between the elements of the personal computer 20, for example, at the time of loading the operating system using ROM 24.

The personal computer 20 in turn contains a hard disk 27 for reading and writing data, a magnetic disk drive 28 for reading and writing to removable magnetic disks 29, and an optical drive 30 for reading and writing to removable optical disks 31, such as a CD-ROM, DVD -ROM and other optical information carriers. The hard disk 27, the magnetic disk drive 28, the optical drive 30 are connected to the system bus 23 through the interface of the hard disk 32, the magnetic disk drive interface 33 and the optical drive interface 34, respectively. Drives and associated computer storage media are non-volatile means of storing computer instructions, data structures, software modules and other data of a personal computer 20.

The present description discloses an implementation of a system that uses a hard disk, a removable magnetic disk 29 and a removable optical disk 31, but it should be understood that other types of computer storage media are possible that can store data in a form readable by a computer (solid state drives, flash cards memory, digital disks, random access memory (RAM), etc.).

Computer 20 has a file system 36 where the recorded operating system 35 and additional software applications 37, other software modules 38 and program data 39 are stored. The user is able to enter commands and information into the personal computer 20 via input devices (keyboard 40, mouse pad) 42). Other input devices (not displayed) can be used: microphone, joystick, game console, scanner, etc. Such input devices are, as usual, connected to the computer system 20 via a serial port 46, which in turn is connected to the system bus, but can be connected in another way, for example, using a parallel port, a game port, or a universal serial bus (USB). A monitor 47 or other type of display device is also connected to the system bus 23 via an interface such as a video adapter 48. In addition to the monitor 47, the personal computer can be equipped with other peripheral output devices (not displayed), for example, speakers, a printer, etc. .

The personal computer 20 is capable of operating in a networked environment, using a network connection with another or more remote computers 49. The remote computer (or computers) 49 are the same personal computers or servers that have most or all of the elements mentioned earlier in the description of the creature personal computer 20 shown in Fig.10. Other devices, such as routers, network stations, peer-to-peer devices, or other network nodes may also be present on the computer network.

Network connections can form a local area network (LAN) 51 and wide area network (WAN) 52. Such networks are used in corporate computer networks, internal networks of companies and, as a rule, have access to the Internet. In LAN or WAN networks, the personal computer 20 is connected to the local area network 51 via a network adapter or network interface 53. When using the networks, the personal computer 20 may use a modem 54 or other means of providing communication with a global computer network 52, such as the Internet. The modem 54, which is an internal or external device, is connected to the system bus 23 via the serial port 46. It should be clarified that the network connections are only exemplary and are not required to display the exact network configuration, i.e. in reality, there are other ways to establish a technical connection between one computer and another.

In conclusion, it should be noted that the information provided in the description are only examples that do not limit the scope of the present utility model described by the formula. The person skilled in the art will understand that there may be other options for implementing this utility model that are consistent with the nature and scope of this utility model.

Claims (18)

1. The system for forming a solution to the problems of functioning of computer systems, including a server, which at the same time contains: (a) a decision-making tool stored in memory and executed on a server processor, designed to: - obtaining a solution for the category of problems recorded in the specified format on the user's computer connected to the server, and recording the resulting solution in the database; - finding solutions for the mentioned category of problems in the database; - Comparison of the obtained solution in terms of quality with the solutions found in the process of the said search in the database; and wherein said decision making means is associated with a decision testing means and a database; (b) a solution testing tool, stored in memory and executed on the server processor, designed to execute solutions received and stored in the database in various hardware and software configurations with the aim of determining the quality indicators of the solutions and recording the quality indicators in the database, while solution testing tool is connected to the database; (c) a database stored in the server’s memory, intended for the orderly storage of categories of problems, solutions, rules by which a solution is put in accordance with the categories of problems, and indicators of the quality of solutions; 2. The system according to claim 1, which further comprises a decision-making tool stored in memory and executed on the server processor, designed to: - collection of system information from at least one user computer connected to the server, which determines the category of problems and the configuration of the user computer; - forming a list of solutions from the database corresponding to the mentioned category of problems and applicable to the mentioned configuration of the user's computer, while the list of solutions is ordered by rating of solutions; and - transferring decisions from the generated list of decisions to the user's computer in an ordered manner. 3. The system according to claim 1, in which the database further comprises tables for orderly storage of user profiles, including at least system information of the user's personal computer, information about problems encountered, decisions made on the user's personal computer and solutions added by the user. 4. The system according to claims 2 and 3, in which the decision-making tool is also designed to load the user profile from the database and create a list of decisions based on the downloaded data. 5. The system according to claim 1, in which the system information includes at least the software and hardware configurations of the user's computer, event logs, application report files, error information, the state of the central processor, the state of the random access memory, the status of network devices. 6. The system according to claim 1, in which the rating of solutions is calculated by the number of applications of the solution, and the more the number of troubleshooting in computer systems of users using this solution, the higher its rating. 7. The system according to claim 1, in which the solution testing tool is a set of virtual machines with various hardware and software configurations designed to test the application of solutions. 8. The system according to claim 1, in which the solution testing means is stored and executed on at least one user computer and is intended to test the application of the solution in the software and hardware configuration of said user computer. 9. The system according to claim 1, in which the quality indicators contain at least a rating of decisions, the effectiveness of decisions. 10. The system for forming a solution to the problems of functioning of computer systems, including a server, which at the same time contains: (a) a decision-making tool stored in memory and executed on a server processor, designed to: - finding solutions for the category of problems in the database; - forming a solution for the mentioned category of problems by modifying the solutions found in the database during the search, and writing the generated solution to the database; - comparisons in terms of quality of the formed solution with the solutions found in the search process in the database; and wherein said decision making means is associated with a database and a decision testing means; (b) a solution testing tool, stored in memory and executed on the server processor, designed to execute the solutions generated and stored in the database in various hardware and software configurations in order to determine the quality indicators of the solutions and write the quality indicators to the database, while solution testing tool is connected to the database; (c) a database stored in memory and executed on the server processor, designed for orderly storage of categories of problems, solutions, rules by which a solution is put into correspondence with the categories of problems, and quality indicators of solutions. 11. The system of claim 10, which further comprises a decision-making tool stored in memory and executed on a server processor, designed to: - collection of system information from at least one user computer connected to the server, which determines the category of problems and the configuration of the user computer; - forming a list of solutions from the database corresponding to the mentioned category of problems and applicable to the mentioned configuration of the user's computer, while the list of solutions is ordered by rating of solutions; and - transferring decisions from the generated list of decisions to the user's computer in an ordered manner. 12. The system of claim 10, wherein the database further comprises tables for orderly storage of user profiles, including at least system information of a user's personal computer, information about problems encountered, decisions made on the user's personal computer, and solutions added by the user. 13. The system according to paragraphs 11 and 12, in which the decision-making tool is also designed to load the user profile from the database and generate a list of decisions based on the downloaded data. 14. The system of claim 10, in which the system information includes at least the software and hardware configurations of the user's computer, event logs, application report files, error information, the state of the central processor, the status of the random access memory, the status of network devices. 15. The system of claim 10, in which the rating of solutions is calculated according to the number of applications of the solution, and the more the number of solutions to problems in computer systems of users using this solution, the higher its rating. 16. The system of claim 10, in which the solution testing tool is a set of virtual machines with various hardware and software configurations designed to test the application of solutions. 17. The system of claim 10, in which the solution testing means is stored and executed on at least one user computer and is intended to test the application of the solution in the hardware-software configuration of said user computer. 18. The system of claim 10, in which the quality indicators contain at least a rating of decisions, the effectiveness of decisions.

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