Semi-automatic game server pressure test system

Abstract

The invention discloses a semi-automatic game server pressure test system, which can automatically generate batch test accounts and simulate real player behaviors through a robot control module, greatly improves the test efficiency, reduces manual configuration work, more accurately evaluates the performance and stability of a server, and at the same time, reduces the labor intensity of a user. The robot login / exit interval is controlled to support the cyclic pressure test, the test comprehensiveness and reliability are enhanced, the server parameter dynamic configuration module can modify key parameters in real time, dynamically adjust the maximum number of online people of the server and the branching switching rule, simulate various scenes and load changes, help to evaluate the performance under high load, and improve the performance of the server. Branch configuration and load states are displayed in real time, visual data and feedback are provided, problems can be found and optimized in time, a test rule engine supports multi-stage pressure test parameter configuration, collapse critical points are automatically recognized, key indexes are recorded, test flexibility and configurability are improved, and a powerful basis is provided for optimization and improvement.

Description

Technical Field

[0001] The present invention relates to the technical field of game server stress testing, and in particular to a semi-automatic game server stress testing system. Background Art

[0002] Current game server stress testing technology has several significant limitations and shortcomings. Traditional stress testing tools usually require testers to manually configure test accounts and operation scripts. This process is cumbersome and inefficient, making it difficult to meet the needs of large-scale, high-efficiency testing.

[0003] In addition, existing testing solutions are often unable to dynamically adjust server parameters for extreme testing. In actual game operations, the server needs to adjust its performance parameters in real time according to changes in the number of players to ensure the smoothness and stability of the game. However, current testing technologies mostly use static testing methods, which cannot truly simulate this dynamically changing environment, thereby limiting the accuracy and effectiveness of the test.

[0004] Furthermore, existing testing methods lack targeted testing methods for the line-dividing mechanism of game scenarios. In games such as multiplayer online role-playing games (MMORPGs), the line-dividing mechanism is an important means to ensure player experience and server performance. However, due to the complexity and diversity of the line-dividing mechanism, current testing technology makes it difficult to conduct comprehensive and in-depth testing on it, thereby increasing the risk of game operations. Summary of the Invention

[0005] In view of this, the present invention proposes a semi-automated game server stress testing system, which can effectively solve the defects of the existing technology, such as the difficulty in meeting large-scale and high-efficiency testing requirements, the inability to truly simulate a dynamically changing environment, and the lack of targeted testing methods for the line division mechanism of the game scene.

[0006] The technical solution of the present invention is achieved as follows:

[0007] A semi-automatic game server stress testing system, comprising:

[0008] The robot control module is used to automatically generate batch test accounts according to preset rules, simulate player behavior through operation command recording / playback, control the robot login / logout interval, and support cyclic stress testing;

[0009] The server parameter dynamic configuration module is used to modify the number of scene branches, branch mode, and maximum number of people threshold in real time, dynamically adjust the maximum number of online users of the server, branch switching rules, and display the current branch configuration and load status in real time;

[0010] The test rule engine is used to support multi-stage stress test parameter configuration, automatically identify the critical point of server crash, and record key indicators of server response time and error rate.

[0011] As a further optional solution to the semi-automatic game server stress testing system, the robot control module automatically generates batch test accounts according to preset rules, specifically:

[0012] Automatically generate batches of test accounts based on the preset rules of the account generation algorithm. The account generation algorithm is as follows:

[0013] AccountID=Prefix+(SerialNumber),

[0014] Where AccountID is the unique identifier of the test account, Prefix is the account prefix, and SerialNumber is the serial number, which increases incrementally starting from 1 and is used to uniquely identify each test account.

[0015] The imitation of player behavior is achieved through the operation instruction recording / playback technology, specifically:

[0016] Record a series of operation instructions of the player in the game to form an operation instruction library;

[0017] During the test, commands are selected from the operation command library and replayed as needed to simulate the player's real behavior;

[0018] The control robot login / logout interval supports cyclic stress testing, specifically:

[0019] The robot's login / logout intervals are controlled according to the login / logout control algorithm to support cyclic stress testing. The login / logout control algorithm is:

[0020] Login / LogoutInterval=BaseInterval+(RandomValue),

[0021] Among them, Login / LogoutInterval is the time interval for robot login / logout, BaseInterval is the basic interval time, and RandomValue is a random value used to add a random time deviation on the basis of the basic interval time to achieve randomness of robot login / logout, thereby better simulating the online behavior of real players.

[0022] As a further optional solution of the semi-automatic game server stress testing system, the algorithm for modifying the number of scene lines in real time is:

[0023] NewLine=CurrentLine+ΔLine,

[0024] Among them, NewLine is the new branch line dynamically created during the test, CurrentLine is the number or identifier of the game scene branch line currently in use, and ΔLine is the number of branches added or reduced dynamically calculated based on the current server load and game scene requirements;

[0025] The line splitting mode includes single line mode, multi-line parallel mode, and load balancing mode;

[0026] The adjustment of the maximum number of people threshold is dynamically set based on server performance and test requirements;

[0027] The algorithm for dynamically adjusting the maximum number of online users on the server is:

[0028] MaxOnlinePlayers=BaseMaxPlayers×(1+LoadFactor),

[0029] Among them, MaxOnlinePlayers is the maximum number of online players allowed by the server, BaseMaxPlayers is the basic maximum number of online players, and LoadFactor is the load factor, which is dynamically adjusted according to the current server load;

[0030] The line switching rules are adjusted based on the current load conditions of each line and the game scene requirements to achieve load balancing and optimize the player experience.

[0031] As a further optional solution of the semi-automatic game server stress testing system, the multi-stage stress testing parameter configuration includes an initial stress stage, a pressure increasing stage, and a pressure maintaining or decreasing stage, and the stress parameters of each stage are customized according to the test requirements;

[0032] The algorithm for automatically identifying the critical point of server crash is:

[0033] CrashPoint=MaxLoad-SafetyMargin,

[0034] Among them, CrashPoint is the critical point of server crash, MaxLoad is the maximum load reached by the server during the test, and SafetyMargin is the safety threshold used to provide a certain buffer space when identifying the critical point of crash.

[0035] The key indicators of recording server response time and error rate are realized by a test report generation unit. The test report generation unit collects and records various performance indicators of the server in real time during the test process, and generates a detailed test report after the test is completed.

[0036] As a further optional solution of the semi-automatic game server stress testing system, the robot control module also includes a dynamic scheduling unit for adjusting the robot's login and exit strategies according to test requirements.

[0037] A semi-automated game server stress testing method, specifically comprising:

[0038] Generate batch test accounts through the robot control module and set the robot's behavior mode;

[0039] Set the initial server parameters and line configuration through the server parameter dynamic configuration module;

[0040] Start the test rule engine, begin stress testing, and dynamically adjust server parameters and robot behavior according to the instructions of the test rule engine;

[0041] Monitor and record server performance data during the test, including key indicators such as response time and error rate;

[0042] Analyze test data to determine the performance boundaries and potential problem points of the server.

[0043] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned semi-automatic game server stress testing method are implemented.

[0044] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned semi-automatic game server stress testing method.

[0045] The beneficial effects of the present invention are: through the robot control module, the system can automatically generate batch test accounts according to preset rules and simulate the behavior patterns of real players. This function not only greatly improves the test efficiency and reduces the manual configuration work of testers, but also can more realistically simulate the player's operations and behaviors in the game, thereby more accurately evaluating the performance and stability of the server. At the same time, by controlling the login / logout interval of the robot, the system can support cyclic stress testing, further enhancing the comprehensiveness and reliability of the test. The server parameter dynamic configuration module enables the system to modify key parameters such as the number of scene lines, line mode, and maximum number of people threshold in real time, and dynamically adjust the server's maximum number of online people and line switching rules according to test requirements. This dynamic adjustment capability can realistically simulate the game operation process Various scenarios and load changes in the server can help testers more accurately evaluate the performance of the server under high load. In addition, the real-time display of the current branch configuration and load status provides testers with intuitive test data and feedback, which helps them to find problems and optimize them in time. The test rule engine supports multi-stage stress test parameter configuration, and can automatically identify the server's critical point of collapse, and record key indicators such as the server's response time and error rate. This function not only improves the flexibility and configurability of the test, but also can accurately identify the server's performance bottlenecks and potential problem points, providing testers with strong data support and analysis basis. In addition, through the generated detailed test report, testers can fully understand the performance of the server and provide targeted suggestions and directions for subsequent optimization and improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 This is a schematic diagram of the composition of a semi-automatic game server stress testing system of the present invention;

[0048] Figure 2 This is a flow chart of a semi-automatic game server stress testing method of the present invention;

[0049] Figure 3 A schematic diagram of the composition of a computing device according to the present invention. DETAILED DESCRIPTION

[0050] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] refer to Figure 1-Figure 3 , a semi-automatic game server stress testing system, comprising:

[0052] The robot control module is used to automatically generate batch test accounts according to preset rules, simulate player behavior through operation command recording / playback, control the robot login / logout interval, and support cyclic stress testing;

[0053] The server parameter dynamic configuration module is used to modify the number of scene branches, branch mode, and maximum number of people threshold in real time, dynamically adjust the maximum number of online users of the server, branch switching rules, and display the current branch configuration and load status in real time;

[0054] The test rule engine is used to support multi-stage stress test parameter configuration, automatically identify the critical point of server crash, and record key indicators of server response time and error rate.

[0055] In this embodiment, through the robot control module, the system can automatically generate batch test accounts according to preset rules and simulate the behavior patterns of real players. This function not only greatly improves the test efficiency and reduces the manual configuration work of testers, but also can more realistically simulate the player's operations and behaviors in the game, thereby more accurately evaluating the performance and stability of the server. At the same time, by controlling the login / logout interval of the robot, the system can support cyclic stress testing, further enhancing the comprehensiveness and reliability of the test. The server parameter dynamic configuration module enables the system to modify key parameters such as the number of scene lines, line mode, and maximum number of people in real time, and dynamically adjust the server's maximum number of online people and line switching rules according to test requirements. This dynamic adjustment capability can truly simulate the game operation process. various scenarios and load changes, thereby helping testers to more accurately evaluate the performance of the server under high load. In addition, the real-time display of the current branch configuration and load status provides testers with intuitive test data and feedback, allowing them to promptly identify problems and optimize them. The test rule engine supports multi-stage stress test parameter configuration, and can automatically identify the server's critical point of collapse, and record key indicators such as the server's response time and error rate. This function not only improves the flexibility and configurability of the test, but also can accurately identify the server's performance bottlenecks and potential problem points, providing testers with strong data support and analysis basis. In addition, through the generated detailed test report, testers can fully understand the performance of the server and provide targeted suggestions and directions for subsequent optimization and improvement.

[0056] Preferably, the robot control module automatically generates batch test accounts according to preset rules, specifically:

[0057] Automatically generate batches of test accounts based on the preset rules of the account generation algorithm. The account generation algorithm is as follows:

[0058] AccountID=Prefix+(SerialNumber),

[0059] Where AccountID is the unique identifier of the test account, Prefix is the account prefix, and SerialNumber is the serial number, which increases incrementally starting from 1 and is used to uniquely identify each test account.

[0060] The imitation of player behavior is achieved through the operation instruction recording / playback technology, specifically:

[0061] Record a series of operation instructions of the player in the game to form an operation instruction library;

[0062] During the test, commands are selected from the operation command library and replayed as needed to simulate the player's real behavior;

[0063] The control robot login / logout interval supports cyclic stress testing, specifically:

[0064] The robot's login / logout intervals are controlled according to the login / logout control algorithm to support cyclic stress testing. The login / logout control algorithm is:

[0065] Login / LogoutInterval=BaseInterval+(RandomValue),

[0066] Among them, Login / LogoutInterval is the time interval for robot login / logout, BaseInterval is the basic interval time, and RandomValue is a random value used to add a random time deviation on the basis of the basic interval time to achieve randomness of robot login / logout, thereby better simulating the online behavior of real players.

[0067] In this embodiment, through the account generation algorithm, the system can efficiently and accurately generate batch test accounts. Each account is unique and easy to manage and track. This automatic generation method greatly reduces the workload of testers in manually creating accounts and improves testing efficiency; through operation instruction recording / playback technology, the system can record the operation instructions of real players and play back these instructions during the test process, thereby simulating the real behavior of the players. This imitation method makes the test closer to the actual game scene and can more accurately evaluate the performance of the server under real player behavior; through the login / logout control algorithm, the system can control the login / logout interval of the robot to realize cyclic stress testing. The introduction of random values increases the randomness of the robot login / logout, making the test closer to the online behavior pattern of real players. This control method can more comprehensively test the performance of the server under different load conditions, especially when the number of players changes dynamically.

[0068] Preferably, the algorithm for modifying the number of scene lines in real time is:

[0069] NewLine=CurrentLine+ΔLine,

[0070] Among them, NewLine is the new branch line dynamically created during the test, CurrentLine is the number or identifier of the game scene branch line currently in use, and ΔLine is the number of branches added or reduced dynamically calculated based on the current server load and game scene requirements;

[0071] The line splitting mode includes single line mode, multi-line parallel mode, and load balancing mode;

[0072] The adjustment of the maximum number of people threshold is dynamically set based on server performance and test requirements;

[0073] The algorithm for dynamically adjusting the maximum number of online users on the server is:

[0074] MaxOnlinePlayers=BaseMaxPlayers×(1+LoadFactor),

[0075] Among them, MaxOnlinePlayers is the maximum number of online players allowed by the server, BaseMaxPlayers is the basic maximum number of online players, and LoadFactor is the load factor, which is dynamically adjusted according to the current server load;

[0076] The line switching rules are adjusted based on the current load conditions of each line and the game scene requirements to achieve load balancing and optimize the player experience.

[0077] In this embodiment, through the algorithm NewLine=CurrentLine+ΔLine, the system can dynamically create or delete branches according to the current server load and game scene requirements. This dynamic adjustment of the number of branches enables the server to respond more flexibly to changes in the number of players and maintain the smoothness and stability of the game. Real-time adjustment of the number of branches also helps to optimize the use of server resources and avoid resource waste or shortage. It provides multiple branching modes such as single-line mode, multi-line parallel mode and load balancing mode, so that the system can select appropriate branching strategies according to different game scenes and test requirements. The diversified branching modes help to improve the scalability and flexibility of the game and meet the needs of players of different sizes. The dynamic setting of the maximum number of people threshold enables the system to adjust the number of branches according to the game scene. The maximum number of players in each lane can be flexibly adjusted based on server performance and testing requirements. This dynamic adjustment helps maintain the balance and stability of the game, avoiding server overload due to too many players or waste of resources due to too few players. By dynamically adjusting the algorithm for the maximum number of online players on the server, the system can dynamically adjust the maximum number of online players allowed by the server based on the current server load. This dynamic adjustment method enables the server to allocate resources more reasonably, ensuring stable performance under high load conditions. The lane switching rules are adjusted based on the current load conditions of each lane and the requirements of the game scenario to achieve load balancing and optimize the player experience. This optimization method helps reduce player waiting time and lag when switching lanes, thereby improving the player's gaming experience.

[0078] Preferably, the multi-stage pressure test parameter configuration includes an initial pressure stage, a pressure increasing stage, and a pressure maintaining or decreasing stage, and the pressure parameters of each stage are customized according to the test requirements;

[0079] The algorithm for automatically identifying the critical point of server crash is:

[0080] CrashPoint=MaxLoad-SafetyMargin,

[0081] Among them, CrashPoint is the critical point of server crash, MaxLoad is the maximum load reached by the server during the test, and SafetyMargin is the safety threshold used to provide a certain buffer space when identifying the critical point of crash.

[0082] The key indicators of recording server response time and error rate are realized by a test report generation unit. The test report generation unit collects and records various performance indicators of the server in real time during the test process, and generates a detailed test report after the test is completed.

[0083] In this embodiment, through a multi-stage configuration including an initial stress stage, a stress increasing stage, and a stress maintaining or decreasing stage, the system can simulate the performance of the server under different load conditions. The stress parameters of each stage can be customized according to the test requirements, making the test more flexible and close to the actual scenario. The multi-stage test can comprehensively evaluate the performance bottlenecks and potential problem points of the server under different load stages, and provide comprehensive data support for optimizing server performance. Through the algorithm CrashPoint=MaxLoad-SafetyMargin, the system can automatically identify the critical point of the server's crash. The algorithm takes into account the maximum load (MaxLoad) and safety threshold (SafetyMargin) reached by the server during the test. fetyMargin), which provides an accurate basis for identifying the critical point of collapse. The setting of the safety threshold provides the system with a certain buffer space when identifying the critical point of collapse, which helps to prevent the server from suddenly crashing due to excessive load in actual operation, and improves the stability and reliability of the system. Through the test report generation unit, the system can collect and record various performance indicators of the server in real time during the test, including key indicators such as response time and error rate. This real-time performance enables testers to understand the performance of the server in a timely manner and discover potential problems. After the test, the system can generate a detailed test report to provide testers with a comprehensive data analysis basis. These reports help testers to gain an in-depth understanding of the performance bottlenecks and potential problem points of the server.

[0084] Preferably, the robot control module further includes a dynamic scheduling unit for adjusting the robot's login and exit strategies according to test requirements.

[0085] In this embodiment, the dynamic scheduling unit can adjust the robot's login and logout strategies according to real-time testing needs, so that the test system can flexibly respond to load changes in different scenarios. For example, when simulating peak player behavior, the dynamic scheduling unit can quickly increase the login frequency and online time. When testing server stability, the player loss scenario can be simulated by adjusting the logout strategy. This flexibility makes the test closer to the real business scenario and improves the reference value of the test results. By dynamically adjusting the login and logout strategies, the system can control the time distribution of the robot's behavior and avoid instantaneous high loads caused by concentrated logins. For example, adopting a time-segmented login strategy or a dynamic adjustment mechanism based on load feedback can make the server pressure curve smoother and help discover potential performance bottlenecks or resource competition problems. Player behavior in a real game environment is dynamic and uncertain. The dynamic scheduling unit introduces Random variables (such as failed login retries and fluctuations in online time) and conditional triggering mechanisms (such as load thresholds triggering exit waves) can simulate more complex player behavior patterns and help verify the server's fault tolerance and recovery mechanism under extreme conditions; in phased stress testing, the dynamic scheduling unit can cooperate with the test rule engine to adjust the stress intensity in real time according to the server status. For example, the login interval can be gradually shortened during the increasing pressure stage, and the strategy can be fine-tuned near the critical point of collapse to accurately locate the threshold, thereby improving the accuracy and controllability of the test; the dynamic scheduling unit supports custom strategy configuration, such as simulating player groups in different regions and with different behavior patterns. By combining multiple strategies (such as random login intervals and step-by-step exits), more test scenarios can be covered and repeated testing time can be reduced. At the same time, automated strategy adjustments reduce the cost of manual intervention, allowing test resources to focus more on key issue analysis.

[0086] A semi-automated game server stress testing method, specifically comprising:

[0087] Generate batch test accounts through the robot control module and set the robot's behavior mode;

[0088] Set the initial server parameters and line configuration through the server parameter dynamic configuration module;

[0089] Start the test rule engine, begin stress testing, and dynamically adjust server parameters and robot behavior according to the instructions of the test rule engine;

[0090] Monitor and record server performance data during the test, including key indicators such as response time and error rate;

[0091] Analyze test data to determine the performance boundaries and potential problem points of the server.

[0092] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned semi-automatic game server stress testing method are implemented.

[0093] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned semi-automatic game server stress testing method.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A semi-automatic game server stress testing system, characterized in that: include: The robot control module is used to automatically generate batch test accounts according to preset rules, simulate player behavior through operation command recording / playback, control the robot login / logout interval, and support cyclic stress testing; The server parameter dynamic configuration module is used to modify the number of scene branches, branch mode, and maximum number of people threshold in real time, dynamically adjust the maximum number of online users of the server, branch switching rules, and display the current branch configuration and load status in real time; The test rule engine is used to support multi-stage stress test parameter configuration, automatically identify the critical point of server crash, and record key indicators of server response time and error rate.

2. A semi-automatic game server stress testing system according to claim 1, characterized in that: The robot control module automatically generates batch test accounts according to preset rules, specifically: Automatically generate batches of test accounts based on the preset rules of the account generation algorithm. The account generation algorithm is as follows: AccountID=Prefix+(SerialNumber), Where AccountID is the unique identifier of the test account, Prefix is the account prefix, and SerialNumber is the serial number, which increases incrementally starting from 1 and is used to uniquely identify each test account. The imitation of player behavior is achieved through the operation instruction recording / playback technology, specifically: Record a series of operation instructions of the player in the game to form an operation instruction library; During the test, commands are selected from the operation command library and replayed as needed to simulate the player's real behavior; The control robot login / logout interval supports cyclic stress testing, specifically: The robot's login / logout intervals are controlled according to the login / logout control algorithm to support cyclic stress testing. The login / logout control algorithm is: Login / LogoutInterval=BaseInterval+(RandomValue), Among them, Login / LogoutInterval is the time interval for robot login / logout, BaseInterval is the basic interval time, and RandomValue is a random value used to add a random time deviation on the basis of the basic interval time to achieve randomness of robot login / logout, thereby better simulating the online behavior of real players.

3. A semi-automatic game server stress testing system according to claim 2, characterized in that: The algorithm for modifying the number of scene lines in real time is: NewLine=CurrentLine+ΔLine, Among them, NewLine is the new branch line dynamically created during the test, CurrentLine is the number or identifier of the game scene branch line currently in use, and ΔLine is the number of branches added or reduced dynamically calculated based on the current server load and game scene requirements; The line splitting mode includes single line mode, multi-line parallel mode, and load balancing mode; The adjustment of the maximum number of people threshold is dynamically set based on server performance and test requirements; The algorithm for dynamically adjusting the maximum number of online users on the server is: MaxOnlinePlayers=BaseMaxPlayers×(1+LoadFactor), Among them, MaxOnlinePlayers is the maximum number of online players allowed by the server, BaseMaxPlayers is the basic maximum number of online players, and LoadFactor is the load factor, which is dynamically adjusted according to the current server load; The line switching rules are adjusted based on the current load conditions of each line and the game scene requirements to achieve load balancing and optimize the player experience.

4. A semi-automatic game server stress testing system according to claim 3, characterized in that: The multi-stage pressure test parameter configuration includes an initial pressure stage, a pressure increase stage, and a pressure hold or decrease stage. The pressure parameters of each stage are customized according to the test requirements. The algorithm for automatically identifying the critical point of server crash is: CrashPoint=MaxLoad-SafetyMargin, Among them, CrashPoint is the critical point of server crash, MaxLoad is the maximum load reached by the server during the test, and SafetyMargin is the safety threshold used to provide a certain buffer space when identifying the critical point of crash. The key indicators of recording server response time and error rate are realized by a test report generation unit. The test report generation unit collects and records various performance indicators of the server in real time during the test process, and generates a detailed test report after the test is completed.

5. A semi-automatic game server stress testing system according to claim 4, characterized in that: The robot control module also includes a dynamic scheduling unit for adjusting the robot's login and exit strategies according to test requirements.

6. A semi-automatic game server stress testing method, characterized in that: Specifically include: Generate batch test accounts through the robot control module and set the robot's behavior mode; Set the initial server parameters and line configuration through the server parameter dynamic configuration module; Start the test rule engine, begin stress testing, and dynamically adjust server parameters and robot behavior according to the instructions of the test rule engine; Monitor and record server performance data during the test, including key indicators such as response time and error rate; Analyze test data to determine the performance boundaries and potential problem points of the server.

7. A computing device, characterized in that The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the semi-automatic game server stress testing method according to claim 6 when executing the computer program.

8. A computer-readable storage medium, characterized in that The storage medium stores a computer program, which, when executed by a processor, implements the steps of the semi-automatic game server stress testing method according to claim 6.

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