Game history debugging system and method based on game log analysis

Abstract

The application provides a game history debugging system and method based on game log analysis, aiming to enable developers to comprehensively understand user behavior data at each level and each day, including user attributes and battle ability, and the acquisition and usage amount of all resources, by analyzing game logs. Based on these data, developers can accurately adjust resource output in the game and optimize the battle difficulty of game levels, thereby realizing efficient debugging of the game history. The application builds a dynamic debugging system by analyzing game logs, starting from the actual experience of users. The system can not only fine-tune the actual values of "battle ability-resource amount-gameplay difficulty", but also verify the actual effect in the game through data. This method significantly reduces the cost of game history debugging, while improving the accuracy and efficiency of debugging, providing developers with a more scientific and efficient debugging tool.

Description

Technical Field

[0001] This invention relates to the field of game development technology, and more specifically, to a game process debugging system and method based on game log analysis. Background Technology

[0002] Against the backdrop of the booming digital entertainment industry, game development has evolved into a highly complex and systematic engineering project. The game journey, as the complete process from entering the game to its end, encompasses multiple dynamic processes such as plot progression, character growth, level challenges, mechanism unlocking, and difficulty changes. Its core components mainly include four aspects: the storyline, the difficulty curve, mechanism unlocking, and the reward cycle. The design quality of these elements directly determines the game's playability and commercial value. Therefore, during game development, developers need to systematically construct the game journey and continuously iterate and refine every aspect of the player experience to create a "fun" gaming experience. This process is known as "game journey debugging."

[0003] In game progression debugging, three key elements must be repeatedly adjusted by developers: 1) the amount of resources a player needs to possess at any given time; 2) the player's attributes and combat abilities at any given time; and 3) the attributes and combat abilities of the monsters the player faces at any given time. These three elements are interconnected, and a change in one affects the entire system. However, relying solely on manual experience for debugging often results in a limited and inflexible approach, failing to fully cover the complexities of the game system. Therefore, improving debugging efficiency and facilitating convenient game progression debugging through tools is the core objective of this invention.

[0004] A patent search revealed an invention patent with publication number CN109876448A, which discloses a method, device, apparatus, and system for real-time debugging of game skills. The method includes establishing a communication connection with a game engine editor; generating a skill status information request and sending it to the game engine editor; acquiring skill status data from the game engine editor, parsing the skill status data into a set of visual elements, and rendering the visual elements; responding to a skill update command, acquiring the editing results of the visual elements, generating skill update data based on the editing results; and transmitting the skill update data to the game engine editor to enable real-time skill updates. This patent primarily focuses on real-time debugging of game skills, without addressing overall game process debugging, the relationship between player resources, attributes, and gameplay difficulty, or utilizing game log analysis, thus lacking a systematic optimization of the overall player experience.

[0005] In summary, given the numerous limitations of existing technologies in game process debugging, which make it difficult to meet the demands of modern game development for efficient and accurate debugging, researching a game process debugging system and method based on game log analysis has become a critical task that urgently needs to be addressed. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a game history debugging system and method based on game log analysis.

[0007] A game history debugging system based on game log analysis provided by the present invention includes:

[0008] The data acquisition module is used to generate structured behavior logs through the data collection unit within the game program;

[0009] The data analysis module is used to parse behavior logs, integrate the parsed behavior logs according to time series, construct a user game journey model, and generate analysis results based on the user game journey model, including user growth path, event rationality, and item supply and demand relationship.

[0010] The data debugging module is used to adjust gameplay output and difficulty based on analysis results, and to establish a dynamic mapping relationship between "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at specific times.

[0011] Preferably, the data collection unit sets trigger conditions according to the business scenario to record user behavior data. The behavior log includes timestamp, user ID, event type and event parameters.

[0012] Preferably, the data analysis module includes:

[0013] The log parsing unit is used to perform regular expression matching and parsing on the behavior log to obtain the parsed behavior log.

[0014] The process reconstruction unit is used to integrate and analyze the behavior logs in chronological order to build a user game process model, so as to clarify the user's attributes, combat ability, resource amount, dwell time and event participation at any time.

[0015] The data summarization unit is used to perform user analysis, event analysis, and item analysis based on the user's game journey model, and to generate deviation assessments of the user's growth ladder, indicators of the rationality of event design, and the balance between supply and demand of items.

[0016] Preferably, user analysis includes: extracting user level, number of days, and event participation information; calculating changes in dwell time, resource changes, and combat power growth rate within each level and number of days based on statistical analysis; presenting the growth path by user level or number of days; presenting the user's strength changes by level challenge order; determining whether the user growth ladder and growth at different times meet design expectations; comparing behavioral differences between different users based on cluster analysis; determining whether the game's freedom meets design expectations; and generating a deviation assessment of the user growth ladder.

[0017] Preferably, event analysis includes: extracting the participation rate, completion rate, and completion time of the event; analyzing the participation rate and completion rate of the gameplay through a funnel model, quantifying the changes in the user's state before and after the event is completed, judging the rationality of the event design and its conformity with expectations, and generating event design rationality indicators.

[0018] Preferably, the item analysis includes: extracting the acquisition and consumption paths of the item; using a supply and demand balance model, comparing the acquisition and consumption of the item to determine the supply and demand balance; then using regression analysis to verify the correlation between the acquisition and consumption paths of the item; plotting the change curves of the acquisition and consumption of the item; determining whether it meets the design expectations; and generating the item supply and demand balance status.

[0019] Preferably, the data debugging module includes an output debugging unit and an enemy debugging unit. The output debugging unit adjusts the gameplay output according to the user's combat ability growth path, and the enemy debugging unit adjusts the gameplay difficulty based on the adjusted gameplay output, establishing a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty".

[0020] Preferably, the process of adjusting gameplay output by the output debugging unit includes: based on the growth path of the user's combat ability, obtaining the user's combat ability at each node by analyzing logs, and calculating the total amount of resources required to develop to a specific combat ability, since all resources are produced through gameplay, thereby adjusting the output of gameplay at each node.

[0021] Preferably, the process of adjusting the gameplay difficulty by the enemy debugging unit includes: based on the adjusted gameplay output, combined with the user's current combat ability and resource quantity, dynamically matching the enemy's combat ability through a difficulty mapping relationship module. The difficulty mapping relationship module is based on a preset user combat ability and enemy combat ability mapping table, and corrects the mapping relationship in real time in combination with the difficulty measurement indicators in the analysis results. The difficulty measurement indicators include the completion rate, battle time and the user's remaining health.

[0022] If the success rate is less than the preset success threshold, or the battle duration is greater than the preset duration threshold, or the user's remaining health is less than the preset health threshold, then the enemy's combat ability will be reduced to lower the game difficulty.

[0023] If the success rate is greater than the preset success threshold, or the battle duration is less than the preset duration threshold, or the user's remaining health is greater than the preset health threshold, then the enemy's combat ability will be increased to raise the game difficulty.

[0024] This invention also provides a game history debugging method based on game log analysis. Based on the above-mentioned game history debugging system based on game log analysis, the method includes the following steps:

[0025] Step S1: During the user experience game, generate behavior logs based on the user's behavior. The format of each behavior log is: timestamp|user ID|event type|event parameters;

[0026] Step S2: Summarize all behavior logs to form a game experience log. Analyze each behavior log and use regular expressions to obtain the timestamp, user ID, event type, and event parameters. Using the user ID as the core, create or update the user's behavior information.

[0027] Step S3: Based on the parsed behavior logs, construct a user game journey model, and generate analysis results including user growth path, event rationality, and item supply and demand relationship based on the user game journey model;

[0028] Step S4: Based on the analysis results, adjust the gameplay output and difficulty in the game, and establish a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at specific times.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. This invention constructs a dynamic debugging system based on user experience by analyzing game logs. This system can not only fine-tune the actual values ​​of "combat ability, resource availability, and gameplay difficulty," but also verify their actual effects in the game through data. This method significantly reduces the cost of debugging the game process while improving the accuracy and efficiency of debugging, providing developers with a more scientific and efficient debugging tool.

[0031] 2. This invention solves the problem of miscalculation that may occur under the planning approach by dynamically adjusting the values ​​and gameplay in the game through real-time collection and analysis of user behavior logs. Attached Figure Description

[0032] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0033] Figure 1 This is a schematic diagram of a game history debugging system based on game log analysis in an embodiment of the present invention;

[0034] Figure 2 This is a flowchart of a game process debugging method based on game log analysis in an embodiment of the present invention. Detailed Implementation

[0035] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0036] This invention provides a game progress debugging system and method based on game log analysis. By analyzing game logs, developers can comprehensively understand user behavior data at each level and each day, including user attributes and combat abilities, as well as the acquisition and usage of all resources. Based on this data, developers can precisely adjust resource output within the game and optimize the combat difficulty of game levels, thereby achieving efficient game progress debugging. This invention, by analyzing game logs and starting from the user's actual experience, constructs a dynamic debugging system. This system can not only fine-tune the actual values ​​of "combat ability, resource quantity, and gameplay difficulty," but also verify their actual effects in the game through data. This method significantly reduces the cost of game progress debugging while improving the accuracy and efficiency of debugging, providing developers with a more scientific and efficient debugging tool.

[0037] Example 1:

[0038] Figure 1 This is a schematic diagram of a game history debugging system based on game log analysis in an embodiment of the present invention.

[0039] like Figure 1 As shown, this embodiment provides a game history debugging system based on game log analysis, including:

[0040] The data acquisition module is used to record all user behaviors through the embedded data collection unit in the game program and generate structured behavior logs. Each user behavior corresponds to a behavior log, and the number of behavior logs ranges from several thousand to tens of thousands.

[0041] Specifically, the data collection unit sets trigger conditions according to business scenarios to record user behavior data. Each behavior log includes a timestamp, user ID, event type, and event parameters.

[0042] In this embodiment, the triggering conditions include character leveling up, improvement of the character development system's capabilities, participation in gameplay, resource acquisition and consumption, and task completion, basically covering all scenarios of changes in the user's strength and resource quantity. The event parameters that need to be recorded vary depending on the event type. Specifically, the event parameters for improving the character development system's capabilities include the development system name, the developed body part and the amount of change, and combat capabilities; the event parameters for participating in gameplay include the gameplay system name, gameplay ID, gameplay result and rewards, and if there is combat, the comparison of the strength of the opposing side and the battle result are additionally recorded.

[0043] The data analysis module is used to parse behavior logs, integrate the parsed behavior logs by time series, construct a user game journey model, and generate analysis results based on the user game journey model, including user growth path, event rationality, and item supply and demand relationship.

[0044] Specifically, the data analysis module includes:

[0045] The log parsing unit is used to perform regular expression matching and parsing on the behavior logs to obtain the parsed behavior logs.

[0046] In this embodiment, the parsed behavior log includes the user's behavior at a specific time, the amount of resources obtained, and attribute improvements. Specifically, the log parsing unit extracts user level, number of days, level challenge order, and event participation information from the event type and event parameters in the behavior log. Further, the log parsing unit calculates the event participation rate, completion rate, completion time, and user state changes before and after event completion, and compares the acquisition and consumption methods of items with the planning in the game design phase.

[0047] The process reconstruction unit is used to integrate and analyze the behavior logs in chronological order to build a user game process model, so as to clarify the user's attributes (including level, combat ability, resource amount, time spent, and event participation at any given moment.

[0048] In this embodiment, the parsed behavior logs of the same user are sorted by time to form the user's game experience history. Specifically, the history reconstruction unit calculates the current amount of resources (the amount of resources the user actually possesses at a certain moment), the cumulative acquisition amount (the total amount of resources the user has accumulated from the start of the game to a certain moment), and the cumulative consumption amount (the total amount of resources the user has consumed from the start of the game to a certain moment) by accumulating the resource amounts in the parsed behavior logs in chronological order. The history reconstruction unit also calculates the specific values ​​of the user's attributes and combat abilities at any given time based on the parsed behavior logs to completely reconstruct the user's game experience history.

[0049] The data summarization unit is used to perform user analysis, event analysis, and item analysis based on the user's game journey model, and to generate deviation assessments of the user's growth ladder, indicators of the rationality of event design, and the balance between supply and demand of items.

[0050] User analysis includes: analyzing growth paths and strength changes based on user attributes, combat abilities, and resource availability. Specifically, it extracts user level, number of days, and event participation information; calculates changes in dwell time, resource changes, and combat power growth rate within each level and number of days based on statistical analysis; presents growth paths by user level or number of days; presents user strength changes by level challenge order; and determines whether the user growth ladder and growth at different times meet design expectations. It also compares behavioral differences between different users based on cluster analysis to determine whether the game's freedom meets design expectations and generates a deviation assessment of the user growth ladder.

[0051] Specifically, by recording user levels and timestamps in behavior logs, logs showing each change in level or number of days are obtained, thus creating a log range for a specific level or number of days. By comparing the first and last log entries of the range, the difference in timestamps yields the dwell time, and the difference in combat power yields the combat power growth rate. Furthermore, by statistically analyzing all logs within the range, resource logs are filtered to obtain the range's resource changes, and event IDs and participation results in event parameters reveal the range's event participation status.

[0052] Furthermore, user level is extracted from logs with event type "level upgrade", and the event parameters include the upgraded level value; number of days is extracted from timestamps, calculating the time span from the user's first login to the current log record; event participation information is extracted from logs with event type "event participation", and the event parameters include the event ID and participation result; dwell time is obtained by calculating the difference in timestamps between two consecutive logs under the same level; resource change is extracted from logs with event type "resource acquisition" or "resource consumption", and the event parameters include the resource type and quantity.

[0053] Event analysis includes: judging the rationality of event design based on event participation. Specifically, it involves extracting the event's participation rate, completion rate, and completion time; analyzing the participation and completion rates of gameplay using a funnel model; quantifying the changes in users' states before and after event completion; judging the rationality of the event design and its alignment with expectations; and generating event design rationality indicators.

[0054] Item analysis includes assessing the acquisition and consumption pathways of items and the economic balance based on changes in resource quantity. Specifically, it involves extracting the acquisition and consumption pathways of items, comparing acquisition and consumption using a supply and demand balance model to determine supply and demand equilibrium, and then using regression analysis to verify the correlation between acquisition and consumption pathways, plotting the curves of item acquisition and consumption changes, and determining whether it meets design expectations. This quantifies the user's experience with game resources, enabling the guidance of user behavior through reasonable resource allocation and generating a state of item supply and demand equilibrium.

[0055] The data debugging module is used to adjust gameplay output and difficulty based on analysis results, and to establish a dynamic mapping relationship between "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at specific times.

[0056] In this embodiment, "combat ability - resource quantity - gameplay difficulty" constitute the basic cycle of the game, and the three factors influence each other. Adjusting "combat ability - resource quantity - gameplay difficulty" allows users to have a good gaming experience. The improvement of a user's combat ability depends on the amount of resources in the game, which is improved by consuming resources in the development module. Resources are obtained by participating in gameplay, and challenging higher difficulty gameplay can improve the efficiency of resource acquisition. Challenging higher difficulty gameplay requires users to have higher combat abilities.

[0057] The process of adjusting gameplay output by the output debugging unit includes: based on the user's combat ability growth path, analyzing logs to obtain the user's combat ability at each node, and combining this with the amount of resources required to develop to a specific combat ability (a known basic setting), calculating the user's total resources at each node. All resources are produced through gameplay, and then adjusting the gameplay output at each node. If the actual combat ability of a node does not reach the set combat ability, it indicates that the resource output of that node is insufficient, and gameplay output needs to be increased; if the actual combat ability of a node exceeds the set combat ability by a certain margin, it indicates that the resource output of that node is excessive, and gameplay output needs to be reduced.

[0058] The process of adjusting the difficulty of gameplay by the enemy debugging unit includes: based on the adjusted gameplay output, combined with the user's current combat ability and resource quantity, dynamically matching the enemy's combat ability through the difficulty mapping relationship module. The difficulty mapping relationship module is based on a preset user combat ability and enemy combat ability mapping table, and corrects the mapping relationship in real time in combination with the difficulty measurement indicators in the analysis results. The difficulty measurement indicators include the completion rate, battle time and user's remaining health.

[0059] If the success rate is less than the preset success threshold, or the battle duration is greater than the preset duration threshold, or the user's remaining health is less than the preset health threshold, then the enemy's combat ability will be reduced to lower the game difficulty.

[0060] If the success rate is greater than the preset success threshold, or the battle duration is less than the preset duration threshold, or the user's remaining health is greater than the preset health threshold, then the enemy's combat ability will be increased to raise the game difficulty.

[0061] This enables a dynamic mapping relationship between "combat ability - resource quantity - gameplay difficulty", ensuring that users achieve the expected attributes and combat ability at a specific time.

[0062] In this embodiment, the preset level completion threshold, preset time threshold, and preset health threshold are values ​​pre-calibrated based on game balance test data.

[0063] In the early stages of game design, to avoid the cyclical influence between "combat ability, resource availability, and gameplay difficulty" and further reduce debugging costs, developers can temporarily ignore the elements of "resource availability" and "gameplay difficulty." Specifically, developers can assume they have unlimited resources and invincibility, while simultaneously simulating the user's experience path during gameplay. This allows developers to quickly verify the rationality of the combat ability growth path and initially determine the target combat ability. The target combat ability is the combat ability that the user should achieve at a specific time, used to guide the design of gameplay output and development consumption. The development module is a system where users improve their combat ability by consuming resources, specifically including functions such as character attribute enhancement and equipment strengthening.

[0064] In the middle of the game development process, the game was further debugged by arranging for multiple users to experience the game repeatedly. Specifically, the developers used data analysis and data debugging modules, combined with the behavior logs of multiple users, to determine the corresponding resource amounts and gameplay difficulty, thereby improving the stability and adaptability of the game and ensuring that different users can have a "fun" gaming experience when they play the game repeatedly.

[0065] Example 2:

[0066] Figure 2 This is a flowchart of a game process debugging method based on game log analysis in an embodiment of the present invention.

[0067] like Figure 2 As shown, this embodiment provides a game history debugging method based on game log analysis, using a game history debugging system based on game log analysis from Embodiment 1 above, including the following steps:

[0068] Step S1: During the user experience of the game, generate behavior logs based on the user's behavior. The format of each behavior log is: timestamp|user ID|event type|event parameters.

[0069] Step S2: Summarize all behavior logs to form a game experience log. Analyze each behavior log and use regular expressions to obtain the timestamp, user ID, event type, and event parameters. Using the user ID as the core, if the user ID in the log does not exist in the current user set, create the corresponding user; if the user ID already exists, update the user's behavior information according to the event type and event parameters in the log.

[0070] Step S3: Based on the parsed behavior logs, construct a user game journey model, and generate analysis results including user growth path, event rationality, and item supply and demand relationship based on the user game journey model.

[0071] Step S4: Based on the analysis results, adjust the gameplay output and difficulty in the game, and establish a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at specific times.

[0072] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, enabling the system and its various devices, modules, and units to function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0073] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A game history debugging system based on game log analysis, characterized in that, include: The data acquisition module is used to generate structured behavior logs through the data collection unit within the game program; The data analysis module is used to parse the behavior logs, integrate the parsed behavior logs according to the time series, construct a user game journey model, and generate analysis results based on the user game journey model, including user growth path, event rationality, and item supply and demand relationship. The data debugging module is used to adjust gameplay output and difficulty based on the analysis results, and establish a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at a specific time.

2. The game history debugging system based on game log analysis according to claim 1, characterized in that, The data collection unit sets trigger conditions according to the business scenario to record user behavior data. The behavior log includes timestamp, user ID, event type and event parameters.

3. The game history debugging system based on game log analysis according to claim 2, characterized in that, The data analysis module includes: The log parsing unit is used to perform regular expression matching and parsing on the behavior log to obtain the parsed behavior log; The process reconstruction unit is used to integrate the parsed behavior logs in chronological order to construct a user game process model, so as to clarify the user's attributes, combat ability, resource amount, dwell time and event participation at any time. The data summarization unit is used to perform user analysis, event analysis, and item analysis based on the user game journey model, and generate deviation assessments of the user growth ladder, event design rationality indicators, and item supply and demand balance status.

4. The game history debugging system based on game log analysis according to claim 3, characterized in that, The user analysis includes: extracting user level, number of days, and event participation information; calculating changes in dwell time, resource changes, and combat power growth rate within each level and number of days based on statistical analysis; presenting growth paths by user level or number of days; presenting changes in user strength by level challenge order; determining whether the user growth ladder and growth at different times meet design expectations; comparing behavioral differences between different users based on cluster analysis; determining whether the game's freedom meets design expectations; and generating a deviation assessment of the user growth ladder.

5. A game history debugging system based on game log analysis according to claim 3, characterized in that, The event analysis includes: extracting the participation rate, completion rate, and completion time of the event; analyzing the participation rate and completion rate of the gameplay through a funnel model, quantifying the changes in the user's state before and after the event is completed, judging the rationality of the event design and its conformity with expectations, and generating event design rationality indicators.

6. The game process debugging system based on game log analysis according to claim 3, characterized in that, The item analysis includes: extracting the acquisition and consumption paths of the item; using a supply and demand balance model, comparing the acquisition and consumption of the item to determine the supply and demand balance; then using regression analysis to verify the correlation between the acquisition and consumption paths of the item; plotting the change curves of the acquisition and consumption of the item; determining whether it meets the design expectations; and generating the item supply and demand balance status.

7. A game history debugging system based on game log analysis according to claim 3, characterized in that, The data debugging module includes an output debugging unit and an enemy debugging unit. The output debugging unit adjusts the gameplay output according to the user's combat ability growth path, and the enemy debugging unit adjusts the gameplay difficulty based on the adjusted gameplay output, establishing a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty".

8. A game history debugging system based on game log analysis according to claim 7, characterized in that, The process of adjusting gameplay output by the output debugging unit includes: based on the user's combat ability growth path, obtaining the user's combat ability at each node by analyzing logs, and calculating the total amount of resources required to develop to a specific combat ability, since all resources are produced through gameplay, thereby adjusting the output of gameplay at each node.

9. A game history debugging system based on game log analysis according to claim 7, characterized in that, The process of adjusting the gameplay difficulty by the enemy debugging unit includes: based on the adjusted gameplay output, combined with the user's current combat ability and resource quantity, dynamically matching the enemy's combat ability through the difficulty mapping relationship module. The difficulty mapping relationship module is based on a preset user combat ability and enemy combat ability mapping table, and corrects the mapping relationship in real time in combination with the difficulty measurement indicators in the analysis results. The difficulty measurement indicators include the completion rate, battle time and user's remaining health. If the success rate is less than the preset success threshold, or the battle duration is greater than the preset duration threshold, or the user's remaining health is less than the preset health threshold, then the enemy's combat ability will be reduced to lower the game difficulty. If the success rate is greater than the preset success threshold, or the battle duration is less than the preset duration threshold, or the user's remaining health is greater than the preset health threshold, then the enemy's combat ability will be increased to raise the game difficulty.

10. A game process debugging method based on game log analysis, based on the game process debugging system based on game log analysis as described in claims 1 to 9, characterized in that, Includes the following steps: Step S1: During the user experience game, generate behavior logs based on the user's behavior. The format of each behavior log is: timestamp|user ID|event type|event parameters; Step S2: Summarize all behavior logs to form a game experience log, parse each behavior log, and use regular expressions to obtain the timestamp, user ID, event type, and event parameters in the behavior log; using the user ID as the core, create a user or update the user's behavior information; Step S3: Based on the parsed behavior logs, construct a user game journey model, and generate analysis results including user growth path, event rationality, and item supply and demand relationship based on the user game journey model; Step S4: Based on the analysis results, adjust the gameplay output and difficulty in the game, and establish a dynamic mapping relationship of "combat ability - resource quantity - gameplay difficulty" to ensure that users achieve the expected attributes and combat ability at a specific time.

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