Multi-mode game balance testing method and device

Abstract

The invention relates to the technical field of game testing, and discloses a multi-mode game balance testing method and device.The method is applied to a balance testing platform and comprises the steps that a testing requirement corresponding to a current game item is determined; the test requirements comprise a test game mode, test mode setting parameters and a test object; generating multiple groups of test data meeting the test requirements according to the test requirements; when multiple test game modes exist, the test data comprises test data of each test game mode; generating antagonism data corresponding to each group of test data according to test requirements based on a set data generation algorithm; based on a test simulation algorithm, performing a balance test on each test task to obtain a test result; each test task comprises one group of test data and antagonism data corresponding to the test data. According to the game balance testing method and device, the game balance testing efficiency can be improved, and meanwhile the accuracy of the game balance testing result is improved.

Description

Technical Field

[0001] The present invention relates to the field of game testing technology, and in particular to a multi-mode game balance testing method and device. Background Art

[0002] Game balance is a key factor that affects the player's gaming experience. Through game balance testing, developers can discover and solve imbalances in gameplay such as characters, skills or game mechanisms in the game, so that all players are in a relatively fair competitive environment in the game, which is conducive to improving the playability of the game and thus increasing player satisfaction with the game.

[0003] In the prior art, balance testing is usually done manually by testers or by using an exhaustive method to traverse all test combinations. However, in the above existing testing methods, manual testing is prone to missing test combinations, and the test levels of testers vary, which can easily lead to inaccurate test results; the exhaustive method requires too many computing resources and is costly; and both testing methods consume a long test time, resulting in low efficiency in game testing.

[0004] Therefore, it is particularly important to propose a technical solution that can improve the efficiency of game balance testing while improving the accuracy of game balance testing results. Summary of the invention

[0005] The present invention provides a multi-mode game balance testing method and device, which can be beneficial.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a multi-mode game balance testing method, which is applied to a balance testing platform, and the method includes:

[0007] Determine the test requirements corresponding to the current game project; the test requirements include test game mode, test mode setting parameters and test objects;

[0008] According to the test requirements, multiple groups of test data that meet the test requirements are generated; wherein, when the test requirements include at least two of the test game modes, all of the test data include at least one group of test data for each of the test game modes;

[0009] Based on the data generation algorithm set by the balance test platform, according to the test requirements, generate adversarial data corresponding to each group of the test data;

[0010] Based on the test simulation algorithm set by the balance test platform, a balance test is performed for each test task to obtain a test result; each of the test tasks includes a set of the test data and adversarial data corresponding to the test data.

[0011] As an optional implementation, in the first aspect of the present invention, the test game mode includes a PVP mode and / or a PVE mode; when the test game mode includes the PVP mode, the test mode setting parameters include test battle parameters, and the test battle parameters include a test battle map and / or a test battle duration; when the test game mode includes the PVE mode, the test mode setting parameters include test level parameters, and the test level parameters include a test level type and / or a test level difficulty; the test object includes a combination of one or more of a target character, a target lineup, a target value, a target level, and a target difficulty;

[0012] Each group of the test data includes a test lineup; the test lineup includes at least one test character; each group of the test data also includes test character parameters corresponding to each of the test characters in the test lineup; the test character parameters include a combination of one or more of the test character level, test character equipment and test character skills;

[0013] For each group of test data, when the test game mode corresponding to the test data is the PVP mode, the adversarial data corresponding to the test data include the adversarial lineup and the adversarial character parameters corresponding to each adversarial character in the adversarial lineup; when the test game mode corresponding to the test data is the PVE mode, the adversarial data corresponding to the test data include the level enemy lineup and the enemy parameters corresponding to each level enemy in the level enemy lineup.

[0014] As an optional implementation, in the first aspect of the present invention, before generating multiple groups of test data that meet the test requirements according to the test requirements, the method further includes:

[0015] Receive custom account parameters input by the tester; or, generate custom account parameters according to the test requirements; the custom account parameters include one or more combinations of account basic parameters, account role parameters, account resource parameters and account mode parameters; the account basic parameters include one or more combinations of account quantity, account type, account level and account resources; the account role parameters include one or more combinations of character quantity, character type, character level, character equipment and character skills; the account mode parameters include the game mode type applicable to the test account to be generated;

[0016] Generate multiple test accounts according to the custom account parameters, and import all the test accounts into the balance testing platform;

[0017] And, generating multiple groups of test data that meet the test requirements according to the test requirements, including:

[0018] According to the test requirement, at least one set of test data is generated for each test account so that the test account meets the test requirement.

[0019] As an optional implementation, in the first aspect of the present invention, the test simulation algorithm set based on the balance test platform performs a balance test for each test task to obtain a test result, including:

[0020] Based on the distributed computing technology corresponding to the balance test platform, each test task is allocated to a target server that meets the preset allocation conditions; the target server is one of the multiple test servers corresponding to the balance test platform;

[0021] Based on all the target servers, balance tests are performed in parallel for multiple test tasks until the balance tests are completed for all the test tasks to obtain test results; wherein the test results include test task results corresponding to each of the test tasks; the test task results include a combination of one or more of battle results, character performance results, and test resource consumption results; the battle results include win-loss results and / or battle duration;

[0022] Wherein, in the process of performing the balance test on multiple test tasks in parallel based on all the target servers until the balance test is completed for all the test tasks and the test results are obtained, the method further includes:

[0023] Based on the cache technology corresponding to the balance test platform, the calculation results corresponding to each of the test tasks are cached to obtain cached calculation results; the calculation results include the test task results corresponding to the test task and / or the intermediate calculation results in the process of executing the balance test corresponding to the test task;

[0024] After detecting that the cache calculation result is not empty, before executing the balance test for each of the test tasks, detecting whether the balance test platform has cached the cache calculation result related to the test task;

[0025] For each of the test tasks, when it is detected that the balance test platform caches a cache calculation result related to the test task, the cache calculation result related to the test task is read, and based on the read cache calculation result, the test task result corresponding to the test task is determined;

[0026] For each of the test tasks, when it is detected that the balance test platform does not cache the cache calculation results related to the test task, a balance test is performed on the test task based on the target server corresponding to the test task to obtain the test task result corresponding to the test task.

[0027] As an optional implementation, in the first aspect of the present invention, after performing a balance test for each test task based on the test simulation algorithm set by the balance test platform and obtaining the test result, the method further includes:

[0028] Analyze the test results to obtain a balance analysis result corresponding to the current game project;

[0029] According to the balance analysis result, determining whether the current game item meets a preset balance condition;

[0030] When it is determined that the current game item does not meet the balance condition, determining a key balance factor corresponding to the current game item according to the balance analysis result;

[0031] Generate an optimization suggestion according to the key balance factor; the optimization suggestion includes a first optimization suggestion and / or a second optimization suggestion;

[0032] According to the optimization suggestion, the optimization object corresponding to the optimization suggestion is optimized; the optimization object includes the current game project and / or the balance testing platform.

[0033] As an optional implementation manner, in the first aspect of the present invention, generating optimization suggestions according to the key balance factors includes:

[0034] Determine the factor type of the key balance factor; the factor type includes a game design factor type and / or a test design factor type;

[0035] When the factor type of the key balance factor includes the game design factor type, generating a first optimization suggestion for the current game project according to the key balance factor; the first optimization suggestion is used to optimize the game design corresponding to the current game project;

[0036] When the factor type of the key balance factor includes the test design factor type, a second optimization suggestion for the balance test platform is generated according to the key balance factor; the second optimization suggestion is used to optimize the data generation algorithm corresponding to the balance test platform; the data generation algorithm includes a combination of one or more of a test data generation algorithm, an adversarial data generation algorithm and a battle matching algorithm.

[0037] As an optional implementation, in the first aspect of the present invention, generating a first optimization suggestion for the current game project according to the key balance factor includes:

[0038] Determine the combat power difference corresponding to each group of the test tasks according to the key balance factors;

[0039] Filter out the test tasks whose combat power difference is greater than or equal to the preset combat power difference from the combat power difference values ​​corresponding to all the test tasks as the first reference task;

[0040] Analyze the test data included in all the first reference tasks to obtain design defect information corresponding to the current game project; the design defect information includes one or more combinations of character design defect information, team design defect information, equipment design defect information, enemy design defect information and level design defect information;

[0041] A first optimization suggestion for the current game project is generated based on the design defect information.

[0042] A second aspect of the present invention discloses a multi-mode game balance testing device, which is applied to a balance testing platform, and comprises:

[0043] A determination module is used to determine the test requirements corresponding to the current game project; the test requirements include a test game mode, test mode setting parameters and a test object;

[0044] A generating module, configured to generate, according to the testing requirement, a plurality of groups of testing data satisfying the testing requirement; wherein, when the testing requirement includes at least two of the testing game modes, all of the testing data include at least one group of testing data for each of the testing game modes;

[0045] The generating module is further configured to generate adversarial data corresponding to each group of the test data based on the data generating algorithm set by the balance testing platform and according to the test requirements;

[0046] A test module is used to perform a balance test on each test task based on a test simulation algorithm set by the balance test platform to obtain a test result; each of the test tasks includes a set of the test data and adversarial data corresponding to the test data.

[0047] As an optional implementation, in the second aspect of the present invention, the test game mode includes a PVP mode and / or a PVE mode; when the test game mode includes the PVP mode, the test mode setting parameters include test battle parameters, and the test battle parameters include a test battle map and / or a test battle duration; when the test game mode includes the PVE mode, the test mode setting parameters include test level parameters, and the test level parameters include a test level type and / or a test level difficulty; the test object includes a combination of one or more of a target character, a target lineup, a target value, a target level, and a target difficulty;

[0048] Each group of the test data includes a test lineup; the test lineup includes at least one test character; each group of the test data also includes test character parameters corresponding to each of the test characters in the test lineup; the test character parameters include a combination of one or more of the test character level, test character equipment and test character skills;

[0049] For each group of test data, when the test game mode corresponding to the test data is the PVP mode, the adversarial data corresponding to the test data include the adversarial lineup and the adversarial character parameters corresponding to each adversarial character in the adversarial lineup; when the test game mode corresponding to the test data is the PVE mode, the adversarial data corresponding to the test data include the level enemy lineup and the enemy parameters corresponding to each level enemy in the level enemy lineup.

[0050] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0051] A receiving module, used for receiving the custom account parameters input by the tester before the generating module generates multiple groups of test data satisfying the test requirements according to the test requirements; or generating the custom account parameters according to the test requirements; the custom account parameters include one or more combinations of account basic parameters, account role parameters, account resource parameters and account mode parameters; the account basic parameters include one or more combinations of the number of accounts, account types, account levels and account resources; the account role parameters include one or more combinations of the number of roles, role types, role levels, role equipment and role skills; the account mode parameters include the game mode type applicable to the test account to be generated;

[0052] The generating module is further used to generate a plurality of test accounts according to the custom account parameters, and import all the test accounts into the balance testing platform;

[0053] And, the specific manner in which the generating module generates multiple groups of test data that meet the test requirements according to the test requirements includes:

[0054] According to the test requirement, at least one set of test data is generated for each test account so that the test account meets the test requirement.

[0055] As an optional implementation, in the second aspect of the present invention, the test module performs a balance test for each test task based on the test simulation algorithm set by the balance test platform, and the specific manner of obtaining the test result includes:

[0056] Based on the distributed computing technology corresponding to the balance test platform, each test task is allocated to a target server that meets the preset allocation conditions; the target server is one of the multiple test servers corresponding to the balance test platform;

[0057] Based on all the target servers, balance tests are performed in parallel for multiple test tasks until the balance tests are completed for all the test tasks to obtain test results; wherein the test results include test task results corresponding to each of the test tasks; the test task results include a combination of one or more of battle results, character performance results, and test resource consumption results; the battle results include win-loss results and / or battle duration;

[0058] Wherein, the device further comprises:

[0059] A cache module is used for, in the process of executing the balance test for multiple test tasks in parallel based on all the target servers in the test module until the balance test is completed for all the test tasks and the test results are obtained, caching the calculation results corresponding to each of the test tasks based on the cache technology corresponding to the balance test platform to obtain cached calculation results; the calculation results include the test task results corresponding to the test task and / or the intermediate calculation results in the process of executing the balance test corresponding to the test task;

[0060] A detection module, configured to detect whether the balancing test platform has cached cached calculation results related to the test task before executing the balancing test for each test task after detecting that the cached calculation results are not empty;

[0061] A reading module, for each of the test tasks, when the detection module detects that the balance test platform caches the cache calculation results related to the test task, reading the cache calculation results related to the test task, and determining the test task result corresponding to the test task based on the read cache calculation results;

[0062] The test module is also used to, for each of the test tasks, when the detection module detects that the balance test platform does not cache the cache calculation results related to the test task, perform a balance test on the test task based on the target server corresponding to the test task to obtain the test task result corresponding to the test task.

[0063] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0064] An analysis module, configured to perform a balance test on each test task based on the test simulation algorithm set by the test module and the balance test platform, and after obtaining the test result, analyze the test result to obtain a balance analysis result corresponding to the current game project;

[0065] A judgment module, used to judge whether the current game project meets a preset balance condition according to the balance analysis result;

[0066] The determination module is further configured to determine a key balance factor corresponding to the current game item according to the balance analysis result when the judgment module determines that the current game item does not meet the balance condition;

[0067] The generating module is further used to generate an optimization suggestion according to the key balance factor; the optimization suggestion includes a first optimization suggestion and / or a second optimization suggestion;

[0068] An optimization module is used to optimize the optimization object corresponding to the optimization suggestion according to the optimization suggestion; the optimization object includes the current game project and / or the balance testing platform.

[0069] As an optional implementation, in the second aspect of the present invention, the specific manner in which the generation module generates the optimization suggestion according to the key balance factor includes:

[0070] Determine the factor type of the key balance factor; the factor type includes a game design factor type and / or a test design factor type;

[0071] When the factor type of the key balance factor includes the game design factor type, generating a first optimization suggestion for the current game project according to the key balance factor; the first optimization suggestion is used to optimize the game design corresponding to the current game project;

[0072] When the factor type of the key balance factor includes the test design factor type, a second optimization suggestion for the balance test platform is generated according to the key balance factor; the second optimization suggestion is used to optimize the data generation algorithm corresponding to the balance test platform; the data generation algorithm includes a combination of one or more of a test data generation algorithm, an adversarial data generation algorithm and a battle matching algorithm.

[0073] As an optional implementation, in the second aspect of the present invention, the specific manner in which the generation module generates the first optimization suggestion for the current game project according to the key balance factor includes:

[0074] Determine the combat power difference corresponding to each group of the test tasks according to the key balance factors;

[0075] Filter out the test tasks whose combat power difference is greater than or equal to the preset combat power difference from the combat power difference values ​​corresponding to all the test tasks as the first reference task;

[0076] Analyze the test data included in all the first reference tasks to obtain design defect information corresponding to the current game project; the design defect information includes one or more combinations of character design defect information, team design defect information, equipment design defect information, enemy design defect information and level design defect information;

[0077] A first optimization suggestion for the current game project is generated based on the design defect information.

[0078] A third aspect of the present invention discloses another multi-mode game balance testing device, the device comprising:

[0079] A memory storing executable program code;

[0080] a processor coupled to the memory;

[0081] The processor calls the executable program code stored in the memory to execute part or all of the steps of the multi-mode game balance testing method disclosed in the first aspect of the present invention.

[0082] A fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all steps of the multi-mode game balance testing method disclosed in the first aspect of the present invention.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] In the present invention, the test requirements corresponding to the current game project are determined; the test requirements include test game modes, test mode setting parameters and test objects; according to the test requirements, multiple groups of test data that meet the test requirements are generated; wherein, when the test requirements include at least two test game modes, all test data include at least one group of test data for each test game mode; based on the data generation algorithm set by the balance test platform, adversarial data corresponding to each group of test data is generated according to the test requirements; based on the test simulation algorithm set by the balance test platform, a balance test is performed for each test task to obtain a test result; each test task includes one group of test data and adversarial data corresponding to the test data. It can be seen that the implementation of the present invention can generate multiple groups of test data that meet the test requirements according to the determined test requirements of the current game project, and generate corresponding adversarial data for each group of test data, so as to perform a balance test on each group of test data and the corresponding adversarial data based on the test simulation algorithm to obtain the test results. It can realize the balance test based on the intelligent generation of test tasks that meet the test requirements, improve the generation efficiency and generation accuracy of the test data, thereby improving the generation accuracy of the corresponding adversarial data, which is beneficial to improve the efficiency of the game balance test while improving the accuracy of the game balance test results, which is beneficial to improve the optimization accuracy of the game content and the balance test process, which is beneficial to improve the playability of the game and the reliability of the test process, and is beneficial to provide players with better game content. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0086] Figure 1 It is a flowchart of a multi-mode game balance testing method disclosed in an embodiment of the present invention;

[0087] Figure 2 is a flowchart of another multi-mode game balance testing method disclosed in an embodiment of the present invention;

[0088] Figure 3 is a flowchart of another multi-mode game balance testing method disclosed in an embodiment of the present invention;

[0089] Figure 4 It is a structural schematic diagram of a multi-mode game balance testing device disclosed in an embodiment of the present invention;

[0090] Figure 5 is a structural schematic diagram of another multi-mode game balance testing device disclosed in an embodiment of the present invention;

[0091] Figure 6 It is a structural schematic diagram of another multi-mode game balance testing device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0092] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 creative work are within the scope of protection of the present invention.

[0093] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0094] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0095] The present invention discloses a multi-mode game balance test method and device, which can generate multiple groups of test data that meet the test requirements according to the test requirements of the current game project determined, and generate corresponding adversarial data for each group of test data, so as to perform balance test on each group of test data and corresponding adversarial data based on the test simulation algorithm, and obtain test results, and can realize balance test based on intelligent generation of test tasks that meet the test requirements, improve the generation efficiency and generation accuracy of test data, thereby improving the generation accuracy of corresponding adversarial data, and thus help to improve the efficiency of game balance test while improving the accuracy of game balance test results, and thus help to improve the optimization accuracy of game content and balance test process, and thus help to improve the playability of the game and the reliability of the test process, and thus help to provide players with better game content. The following are detailed descriptions.

[0096] Embodiment 1

[0097] See also Figure 1 , Figure 1 : is a flowchart of a multi-mode game balance testing method disclosed in an embodiment of the present invention. Figure 1 The described multi-mode game balance test method can be applied to a multi-mode game balance test device, which may include one of a test device, a test terminal, a test system, and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiment of the present invention; the method can also be applied to a balance test platform, which is not limited in the embodiment of the present invention. Figure 1 As shown, the multi-mode game balance testing method may include the following operations:

[0098] 101. Determine the testing requirements corresponding to the current game project.

[0099] In the embodiment of the present invention, the test requirements may include a test game mode, test mode setting parameters and a test object.

[0100] 102. According to the test requirements, generate multiple groups of test data that meet the test requirements.

[0101] In the embodiment of the present invention, when the test requirements include at least two test game modes, all test data include at least one set of test data for each test game mode.

[0102] 103. Based on the data generation algorithm set by the balance test platform, generate adversarial data corresponding to each set of test data according to test requirements.

[0103] In an embodiment of the present invention, optionally, step 103 may be specifically as follows: based on the data generation algorithm set by the balance test platform, according to the test requirements, generating adversarial data with a matching degree greater than or equal to a preset matching degree with each set of test data, which is not limited in the embodiment of the present invention.

[0104] 104. Based on the test simulation algorithm set by the balance test platform, a balance test is performed for each test task to obtain a test result.

[0105] In the embodiment of the present invention, each test task includes a set of test data and adversarial data corresponding to the test data.

[0106] In an embodiment of the present invention, specifically, for each test task, when the test game mode corresponding to the test task is the PVP (Player Versus Player) mode, based on the above-mentioned test simulation algorithm and the test data and corresponding adversarial data included in the test task, a PVP battle is simulated to obtain a battle test result corresponding to the test task; when the test game mode corresponding to the test task is the PVE (Player Versus Environment) mode, based on the above-mentioned test simulation algorithm and the test data and corresponding adversarial data included in the test task, a PVE battle is simulated to obtain a level test result corresponding to the test task.

[0107] It can be seen that the implementation of the method described in the embodiment of the present invention can generate multiple groups of test data that meet the test requirements according to the determined test requirements of the current game project, and generate corresponding adversarial data for each group of test data, so as to perform a balance test on each group of test data and the corresponding adversarial data based on the test simulation algorithm to obtain the test results. It can realize the balance test based on the intelligent generation of test tasks that meet the test requirements, improve the generation efficiency and generation accuracy of the test data, thereby improving the generation accuracy of the corresponding adversarial data, which is beneficial to improve the efficiency of the game balance test while improving the accuracy of the game balance test results, which is beneficial to improve the optimization accuracy of the game content and the balance test process, which is beneficial to improve the playability of the game and the reliability of the test process, and is beneficial to provide players with better game content.

[0108] In an optional embodiment, the balance test platform may be provided with an automated testing tool, a fault tolerance mechanism, a load balancing mechanism, and a high-performance computing cluster.

[0109] It can be seen that this optional embodiment can use automated testing tools to reduce manual intervention and improve testing efficiency; and, by adopting a fault-tolerant mechanism, the system can still run stably when some servers fail, thereby improving testing stability; and, by adopting load balancing technology, it can ensure that computing tasks are evenly distributed and avoid single-point bottlenecks; and, by using a high-performance computing cluster to support highly complex computing-intensive tasks, it is conducive to testing more diverse battle / level situations and improving testing comprehensiveness.

[0110] In an optional embodiment, the test game mode includes a PVP mode and / or a PVE mode; when the test game mode includes a PVP mode, the test mode setting parameters include test battle parameters, and the test battle parameters include a test battle map and / or a test battle duration; when the test game mode includes a PVE mode, the test mode setting parameters include test level parameters, and the test level parameters include a test level type and / or a test level difficulty; the test object includes a combination of one or more of a target character, a target lineup, a target value, a target level, and a target difficulty;

[0111] Each set of test data includes a test lineup; the test lineup includes at least one test character; each set of test data also includes test character parameters corresponding to each test character in the test lineup; the test character parameters include a combination of one or more of the test character level, test character equipment and test character skills;

[0112] For each set of test data, when the test game mode corresponding to the test data is the PVP mode, the adversarial data corresponding to the test data include the adversarial lineup and the adversarial character parameters corresponding to each adversarial character in the adversarial lineup; when the test game mode corresponding to the test data is the PVE mode, the adversarial data corresponding to the test data include the level enemy lineup and the enemy parameters corresponding to each level enemy in the level enemy lineup.

[0113] Among them, the antagonist character parameters corresponding to each antagonist character may include a combination of one or more of the antagonist character level, antagonist character equipment and antagonist character skills; the enemy parameters corresponding to each level enemy may include a combination of one or more of the enemy level, enemy equipment and enemy skills, which is not limited in the embodiment of the present invention.

[0114] It can be seen that this optional embodiment can determine more specific and comprehensive test requirements, which is conducive to improving the comprehensiveness and accuracy of subsequently generated test data; and, it records more specific and comprehensive test data types, which can improve the accuracy and comprehensiveness of test data generation; and, based on the test data and the test game mode, it determines the corresponding adversarial data type, which is conducive to improving the degree of matching between adversarial data and test data, thereby improving the accuracy of adversarial data generation.

[0115] In another optional embodiment, before generating multiple groups of test data that meet the test requirements according to the test requirements, the method may further include the following operations:

[0116] Receive custom account parameters input by the tester; or, generate custom account parameters according to the test requirements; custom account parameters include one or more combinations of account basic parameters, account role parameters, account resource parameters and account mode parameters; account basic parameters include one or more combinations of account quantity, account type, account level and account resources; account role parameters include one or more combinations of character quantity, character type, character level, character equipment and character skills; account mode parameters include the game mode type applicable to the test account to be generated;

[0117] Generate multiple test accounts based on custom account parameters, and import all test accounts into the balance testing platform.

[0118] Among them, the number of accounts is the number of test accounts that need to be generated; the account type includes the account type of each test account that needs to be generated. Exemplarily, the account type can be an ordinary player type or a VIP player type, which is not limited in the embodiment of the present invention; the account level includes the account level range of each test account that needs to be generated; the number of roles in the account role parameter includes the number of roles owned by each test account that needs to be generated, and the role type in the account role parameter includes the role type of each role owned by each test account that needs to be generated. Exemplarily, the role type can be a warrior, a mage, a shooter, etc., or other role types, which are not limited in the embodiment of the present invention; the account resource parameter includes the account resources owned by each test account that needs to be generated. Exemplarily, the account resources can include gold coins, diamonds, props, etc., and can also be game resources that other players can use in the account, which are not limited in the embodiment of the present invention.

[0119] It can be seen that this optional embodiment can generate multiple test accounts according to the custom account parameters by receiving the custom account parameters input by the tester or generating custom account parameters according to the test requirements, so as to import the test accounts into the balance testing platform, which can improve the flexibility and accuracy of determining the custom account parameters, thereby realizing the intelligent generation of test accounts, improving the accuracy of test account generation, and further facilitating improving the accuracy of importing test accounts.

[0120] In this optional embodiment, optionally, according to the test requirements, multiple groups of test data that meet the test requirements are generated, including:

[0121] According to the test requirements, at least one set of test data is generated for each test account so that the test account meets the test requirements.

[0122] It can be seen that this optional embodiment can also generate test data that meets the test requirements for each test account. Generating test data in combination with account information can further improve the accuracy of test data generation, and is conducive to improving the accuracy and comprehensiveness of subsequent analysis of test results.

[0123] In yet another optional embodiment, based on the test simulation algorithm set by the balance test platform, performing a balance test for each test task to obtain a test result may include the following operations:

[0124] Based on the distributed computing technology corresponding to the balance test platform, each test task is assigned to a target server that meets the preset assignment conditions; the target server is one of the multiple test servers corresponding to the balance test platform;

[0125] Based on all target servers, balance tests are performed in parallel for multiple test tasks until the balance tests are completed for all test tasks to obtain test results; wherein the test results include test task results corresponding to each test task; the test task results include a combination of one or more of battle results, character performance results, and test resource consumption results; the battle results include win-loss results and / or battle duration.

[0126] Optionally, based on the distributed computing technology corresponding to the balance test platform, each test task is assigned to a target server that meets preset allocation conditions. Specifically, based on the distributed computing technology corresponding to the balance test platform, each test task is assigned in turn to the target server with the least number of connections, which is not limited in the embodiments of the present invention.

[0127] Among them, the victory and defeat results in the battle results include the victory and defeat results of each battle or level, and the battle duration in the battle results includes the duration of each battle or level; the character performance results include the performance data of each character. Exemplarily, the performance data may include one or more combinations of the character's damage output data, the character's treatment data, and the character's damage-bearing data, and may also include character performance data in other tests, which is not limited in the embodiments of the present invention; the test resource consumption results may include the resource consumption in each battle or level. Exemplarily, the resource consumption may include one or more combinations of the number of skill uses, the type of consumable props, and the number of consumable props, and may also include other resources that can be used in the game, which is not limited in the embodiments of the present invention.

[0128] It can be seen that this optional embodiment can allocate each test task to a target server that meets preset allocation conditions based on distributed computing technology, and then based on the target server, perform balance tests in parallel for multiple test tasks until the balance tests of all test tasks are completed and the test results are obtained. By using distributed technology, the test tasks can be allocated to multiple servers for parallel processing, thereby improving computing efficiency, thereby improving the processing efficiency of test tasks, which is conducive to further improving the efficiency of balance testing.

[0129] In this optional embodiment, in the process of performing the balance test on multiple test tasks in parallel based on all target servers until the balance test on all test tasks is completed and the test results are obtained, the method may further include the following operations:

[0130] Based on the caching technology corresponding to the balance test platform, the calculation results corresponding to each test task are cached to obtain cached calculation results; the calculation results include the test task results corresponding to the test task and / or the intermediate calculation results in the process of executing the balance test corresponding to the test task;

[0131] After detecting that the cached calculation result is not empty, before executing the balance test for each test task, detecting whether the balance test platform has cached the cached calculation result related to the test task;

[0132] For each test task, when it is detected that the balance test platform caches a cache calculation result related to the test task, the cache calculation result related to the test task is read, and based on the read cache calculation result, the test task result corresponding to the test task is determined;

[0133] For each test task, when it is detected that the balance test platform does not cache the cache calculation results related to the test task, a balance test is performed on the test task based on the target server corresponding to the test task to obtain the test task result corresponding to the test task.

[0134] Optionally, for each test task, determining the test task result corresponding to the test task based on the read cache calculation result may include the following operations:

[0135] When the cache calculation result read includes the intermediate calculation result required by the test task, based on the target server corresponding to the test task and on the basis of the intermediate calculation result, a balance test is performed on the test task to obtain the test task result corresponding to the test task;

[0136] When the cache calculation result read includes the test task result required by the test task, the read test task result is used as the test task result corresponding to the test task.

[0137] It can be seen that this optional embodiment can also cache the calculation results based on the caching technology during the parallel processing of test tasks, and if the existence of related calculation results is detected before processing the test task again, the test task results can be determined based on the calculation results, which can reduce repeated calculations and save computing resources, thereby helping to improve the efficiency of balance testing.

[0138] Embodiment 2

[0139] See also Figure 2 , Figure 2 : is a flowchart of a multi-mode game balance testing method disclosed in an embodiment of the present invention. Figure 2 The described multi-mode game balance test method can be applied to a multi-mode game balance test device, which may include one of a test device, a test terminal, a test system, and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiment of the present invention; the method can also be applied to a balance test platform, which is not limited in the embodiment of the present invention. Figure 2 As shown, the multi-mode game balance testing method may include the following operations:

[0140] 201. Determine the testing requirements corresponding to the current game project.

[0141] In the embodiment of the present invention, the test requirements include a test game mode, test mode setting parameters and a test object.

[0142] 202. According to the test requirements, generate multiple groups of test data that meet the test requirements.

[0143] In the embodiment of the present invention, when the test requirements include at least two test game modes, all test data include at least one set of test data for each test game mode.

[0144] 203. Based on the data generation algorithm set by the balance test platform, adversarial data corresponding to each set of test data is generated according to test requirements.

[0145] 204. Based on the test simulation algorithm set by the balance test platform, a balance test is performed for each test task to obtain a test result.

[0146] In the embodiment of the present invention, each test task includes a set of test data and adversarial data corresponding to the test data.

[0147] 205. Analyze the test results to obtain the balance analysis results corresponding to the current game project.

[0148] In an embodiment of the present invention, the balance analysis result is used to indicate the numerical balance degree of the battle / level design of the current game project; wherein, optionally, the balance analysis result may include lineup information of the attacker / defender, character information of the attacker / defender, battle win rate, average injuries per game, average treatment per game, average damage per game, average treatment received per game, and one or more combinations of rounds survived per game, which are not limited in the embodiment of the present invention.

[0149] 206. Based on the balance analysis results, determine whether the current game project meets the pre-set balance conditions.

[0150] In an embodiment of the present invention, when step 206 determines that the current game project does not meet the balance condition, that is, when the judgment result of step 206 is no, the operation of step 207 is executed; optionally, when the judgment result of step 206 is yes, the process is terminated, or, based on the above test results, a test report on the current game project regarding the above test requirements is generated, which is not limited in the embodiment of the present invention.

[0151] 207. Based on the balance analysis results, determine the key balance factors corresponding to the current game project.

[0152] 208. Generate optimization suggestions based on key balance factors.

[0153] In an embodiment of the present invention, the optimization suggestion includes a first optimization suggestion and / or a second optimization suggestion; optionally, the optimization object corresponding to the first optimization suggestion may be the current game project, and the optimization object corresponding to the second optimization suggestion may be a balance testing platform, which is not limited in the embodiment of the present invention.

[0154] 209. According to the optimization suggestion, optimize the optimization object corresponding to the optimization suggestion.

[0155] In the embodiment of the present invention, the optimization object includes the current game project and / or the balance test platform.

[0156] In the embodiment of the present invention, for other detailed descriptions of steps 201 to 204, please refer to the detailed description of steps 101 to 104 in the first embodiment, which will not be described in detail in the embodiment of the present invention.

[0157] It can be seen that the implementation of the method described in the embodiment of the present invention can generate multiple groups of test data that meet the test requirements according to the determined test requirements of the current game project, and generate corresponding adversarial data for each group of test data, so as to perform a balance test on each group of test data and the corresponding adversarial data based on the test simulation algorithm to obtain the test results. It can realize the balance test based on the intelligent generation of test tasks that meet the test requirements, improve the generation efficiency and generation accuracy of the test data, thereby improving the generation accuracy of the corresponding adversarial data, which is beneficial to improve the efficiency of the game balance test while improving the accuracy of the game balance test results, which is beneficial to improve the optimization accuracy of the game content and the balance test process, which is beneficial to improve the playability of the game and the reliability of the test process, and is beneficial to provide players with better game content. In addition, by analyzing the test results, the balance analysis results can be obtained. If it is judged based on the balance analysis results that the current game project does not meet the balance conditions, the key balance factors corresponding to the current game project are first determined, and then optimization suggestions are generated based on the key balance factors to optimize the corresponding optimization objects. This can improve the comprehensiveness and accuracy of the analysis of the test results, which is conducive to improving the accuracy of determining the key balance factors, so as to more accurately generate optimization suggestions for game content or testing platforms, which in turn is conducive to improving the optimization accuracy of game content and testing processes.

[0158] In an optional embodiment, generating optimization suggestions according to key balance factors may include the following operations:

[0159] Determine the factor type of the key factor of balance; the factor type includes the game design factor type and / or the test design factor type;

[0160] When the factor type of the key balance factor includes a game design factor type, generating a first optimization suggestion for the current game project according to the key balance factor; the first optimization suggestion is used to optimize the game design corresponding to the current game project;

[0161] When the factor type of the key balance factor includes a test design factor type, a second optimization suggestion for the balance test platform is generated based on the key balance factor; the second optimization suggestion is used to optimize the data generation algorithm corresponding to the balance test platform; the data generation algorithm includes a combination of one or more of a test data generation algorithm, an adversarial data generation algorithm and a battle matching algorithm.

[0162] Among them, exemplarily, the key balance factors may include one or more combinations of account level differences, character level differences, character equipment differences, character skill differences, card star differences, and data matching differences between test data and adversarial data, which are not limited in the embodiments of the present invention.

[0163] It can be seen that this optional embodiment can generate optimization suggestions corresponding to different types according to the factor types of the key balance factors, which can improve the accuracy of the analysis of the key balance factors, thereby facilitating targeted optimization of game design and / or test data generation logic, and further facilitating more accurate iterative optimization of game content and test processes.

[0164] In this optional embodiment, optionally, generating a first optimization suggestion for the current game project according to the key balance factor may include the following operations:

[0165] Determine the combat power difference corresponding to each set of test tasks based on key balance factors;

[0166] Filter out the test tasks whose combat power difference is greater than or equal to the preset combat power difference from the combat power difference values ​​corresponding to all the test tasks as the first reference tasks;

[0167] Analyze the test data included in all the first reference tasks to obtain design defect information corresponding to the current game project; the design defect information includes one or more combinations of character design defect information, team design defect information, equipment design defect information, enemy design defect information and level design defect information;

[0168] Based on the design defect information, generate the first optimization suggestion for the current game project.

[0169] Among them, the combat power difference corresponding to each group of test tasks is used to represent the combat power difference between the two parties in each group of test tasks or the combat power difference between the test character and the level enemy, which is not limited in the embodiment of the present invention.

[0170] It can be seen that this optional embodiment can also screen out the first reference task with a larger combat power gap from all test tasks, and analyze the design defects of the game based on the first reference task, so as to accurately generate the first optimization suggestion for the current game project, and can accurately analyze the defects in the game design based on the test results, which is conducive to improving the accuracy of generating optimization suggestions for game content, thereby further improving the optimization accuracy of game content.

[0171] In this optional embodiment, optionally, generating a second optimization suggestion for the balance test platform according to the key balance factor may include the following operations:

[0172] According to the key factors of balance, target test data whose numerical settings do not satisfy a preset first numerical condition are screened out from all test data; and / or, according to the key factors of balance, target adversarial data whose numerical settings do not satisfy a preset second numerical condition are screened out from all adversarial data; and / or, according to the key factors of balance, second reference tasks whose data difference between the test data and the adversarial data does not satisfy a preset third numerical condition are screened out from all test tasks;

[0173] Based on all target test data and / or all target adversarial data and / or all second reference tasks, analyzing data generation defect information existing in the balance test platform; the data generation defect information may include at least one of a test data generation logic defect, an adversarial data generation logic defect, and a data pairing logic defect;

[0174] Defect information is generated based on the data, and a second optimization suggestion for the balance test platform is generated.

[0175] It can be seen that this optional embodiment can also filter out target data or second reference tasks that do not meet the preset numerical conditions from the test data, adversarial data, and test tasks, and analyze the data generation defects existing in the balance test platform based on the above-mentioned data that do not meet the numerical conditions, so as to generate targeted optimization suggestions corresponding to the data generation process of the balance test platform, thereby improving the accuracy of the generation of optimization suggestions, and further improving the optimization accuracy of the test process.

[0176] In another optional embodiment, the method may further include the following operations:

[0177] Based on the optimized optimization object, the next batch of test data and corresponding adversarial data are generated to conduct the next batch of balance tests, thereby iteratively optimizing the game content of the current detailed project and the test process of the balance test platform.

[0178] It can be seen that this optional embodiment can perform iterative testing and optimization based on the optimized content, which can be helpful in verifying whether the optimization results meet expectations, thereby helping to improve the optimization accuracy of game content and testing processes.

[0179] In the embodiment of the present invention, illustratively, the process of the multi-mode game balance testing method can also be as follows: Figure 3 As shown, Figure 3 is a flowchart of another multi-mode game balance testing method disclosed in an embodiment of the present invention. Specifically, the method may include the following operations:

[0180] First, determine the game testing requirements, then generate custom parameters, then import multiple test accounts and select test data that meets the requirements, or directly generate test data without generating test accounts; then generate adversarial data corresponding to the test data, and then perform a balance test based on the generated data, and generate a balance analysis result based on the test results, so as to adjust the next batch of test data based on the balance analysis result, thereby iteratively optimizing the test process and game content, which is not limited in the embodiments of the present invention.

[0181] Embodiment 3

[0182] See also Figure 4 , Figure 4 1 is a schematic diagram of the structure of a multi-mode game balance testing device disclosed in an embodiment of the present invention. Figure 4 The described multi-mode game balance test device may include one of a test device, a test terminal, a test system and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiment of the present invention; the device may be applied to a balance test platform, which is not limited in the embodiment of the present invention. Figure 4 As shown, the multi-mode game balance testing device may include:

[0183] Determination module 301, used to determine the test requirements corresponding to the current game project; the test requirements include test game mode, test mode setting parameters and test objects;

[0184] A generating module 302, configured to generate multiple groups of test data satisfying the test requirements according to the test requirements; wherein, when the test requirements include at least two test game modes, all the test data include at least one group of test data for each test game mode;

[0185] The generation module 302 is further used to generate adversarial data corresponding to each set of test data according to the test requirements based on the data generation algorithm set by the balance test platform;

[0186] The test module 303 is used to perform a balance test on each test task based on the test simulation algorithm set by the balance test platform to obtain a test result; each test task includes a set of test data and adversarial data corresponding to the test data.

[0187] It can be seen that the device described in the embodiment of the present invention can generate multiple groups of test data that meet the test requirements according to the determined test requirements of the current game project, and generate corresponding adversarial data for each group of test data, so as to perform a balance test on each group of test data and the corresponding adversarial data based on the test simulation algorithm to obtain the test results. It can realize the balance test based on the intelligent generation of test tasks that meet the test requirements, improve the generation efficiency and generation accuracy of the test data, thereby improving the generation accuracy of the corresponding adversarial data, which is beneficial to improve the efficiency of the game balance test while improving the accuracy of the game balance test results, which is beneficial to improve the optimization accuracy of the game content and the balance test process, which is beneficial to improve the playability of the game and the reliability of the test process, which is beneficial to provide players with better game content.

[0188] In an optional embodiment, the test game mode includes a PVP mode and / or a PVE mode; when the test game mode includes a PVP mode, the test mode setting parameters include test battle parameters, and the test battle parameters include a test battle map and / or a test battle duration; when the test game mode includes a PVE mode, the test mode setting parameters include test level parameters, and the test level parameters include a test level type and / or a test level difficulty; the test object includes a combination of one or more of a target character, a target lineup, a target value, a target level, and a target difficulty;

[0189] Each set of test data includes a test lineup; the test lineup includes at least one test character; each set of test data also includes test character parameters corresponding to each test character in the test lineup; the test character parameters include a combination of one or more of the test character level, test character equipment and test character skills;

[0190] For each set of test data, when the test game mode corresponding to the test data is the PVP mode, the adversarial data corresponding to the test data include the adversarial lineup and the adversarial character parameters corresponding to each adversarial character in the adversarial lineup; when the test game mode corresponding to the test data is the PVE mode, the adversarial data corresponding to the test data include the level enemy lineup and the enemy parameters corresponding to each level enemy in the level enemy lineup.

[0191] It can be seen that the device described in the implementation of this optional embodiment can determine more specific and comprehensive test requirements, which is conducive to improving the comprehensiveness and accuracy of subsequently generated test data; and, the data type of more specific and comprehensive test data is recorded, which can improve the accuracy and comprehensiveness of test data generation; and, based on the test data and the test game mode, the corresponding adversarial data type is determined, which is conducive to improving the degree of matching between adversarial data and test data, thereby improving the accuracy of adversarial data generation.

[0192] In another optional embodiment, Figure 5 As shown, the device may also include:

[0193] The receiving module 304 is used to receive the custom account parameters input by the tester before the generating module 302 generates multiple groups of test data that meet the test requirements according to the test requirements; or, generate the custom account parameters according to the test requirements; the custom account parameters include one or more combinations of account basic parameters, account role parameters, account resource parameters and account mode parameters; the account basic parameters include one or more combinations of the number of accounts, account types, account levels and account resources; the account role parameters include one or more combinations of the number of roles, role types, role levels, role equipment and role skills; the account mode parameters include the game mode type applicable to the test account to be generated;

[0194] The generation module 302 is further used to generate multiple test accounts according to the custom account parameters, and import all the test accounts into the balance test platform;

[0195] Furthermore, the specific manner in which the generating module 302 generates multiple groups of test data that meet the test requirements according to the test requirements may include:

[0196] According to the test requirements, at least one set of test data is generated for each test account so that the test account meets the test requirements.

[0197] It can be seen that the device described in the implementation of this optional embodiment can generate multiple test accounts according to the custom account parameters by receiving the custom account parameters input by the tester or generating custom account parameters according to the test requirements, so as to import the test accounts into the balance testing platform, which can improve the flexibility and accuracy of determining the custom account parameters, thereby realizing the intelligent generation of test accounts, improving the accuracy of test account generation, and further facilitating the improvement of the accuracy of importing test accounts; and, it can also generate test data that meets the test requirements for each test account, and generating test data in combination with account information can further improve the accuracy of test data generation, and is conducive to improving the accuracy and comprehensiveness of subsequent analysis of test results.

[0198] In another optional embodiment, the test module 303 performs a balance test for each test task based on a test simulation algorithm set by the balance test platform. The specific method of obtaining the test result may include:

[0199] Based on the distributed computing technology corresponding to the balance test platform, each test task is assigned to a target server that meets the preset assignment conditions; the target server is one of the multiple test servers corresponding to the balance test platform;

[0200] Based on all target servers, balance tests are performed in parallel for multiple test tasks until the balance tests are completed for all test tasks to obtain test results; wherein the test results include test task results corresponding to each test task; the test task results include a combination of one or more of battle results, character performance results, and test resource consumption results; the battle results include win-loss results and / or battle duration;

[0201] Among them, Figure 5 As shown, the device may also include:

[0202] The cache module 305 is used to perform the balance test for multiple test tasks in parallel based on all target servers in the test module 303 until the balance test is completed for all test tasks. In the process of obtaining the test results, based on the cache technology corresponding to the balance test platform, cache the calculation results corresponding to each test task to obtain the cached calculation results; the calculation results include the test task results corresponding to the test task and / or the intermediate calculation results in the process of executing the balance test corresponding to the test task;

[0203] A detection module 306 is used to detect whether the balance test platform has cached calculation results related to the test task before performing the balance test for each test task after detecting that the cached calculation results are not empty;

[0204] The reading module 307 is used for, for each test task, when the detection module 306 detects that the balance test platform caches the cache calculation result related to the test task, reading the cache calculation result related to the test task, and determining the test task result corresponding to the test task based on the read cache calculation result;

[0205] The test module 303 is also used to perform a balance test on each test task based on the target server corresponding to the test task to obtain the test task result corresponding to the test task when the detection module 306 detects that the balance test platform does not cache the cache calculation results related to the test task.

[0206] It can be seen that the device described in the implementation of this optional embodiment can, based on distributed computing technology, allocate each test task to a target server that meets preset allocation conditions, and then, based on the target server, perform balance tests in parallel for multiple test tasks until the balance tests of all test tasks are completed and the test results are obtained. By using distributed technology, the test tasks can be allocated to multiple servers for parallel processing, thereby improving computing efficiency, thereby improving the processing efficiency of the test tasks, and further facilitating the improvement of the balance test efficiency; and, in the process of parallel processing of test tasks, the calculation results can be cached based on the caching technology, and if the existence of related calculation results is detected before processing the test task, the test task results can be determined based on the calculation results, which can reduce repeated calculations and save computing resources, thereby facilitating the improvement of the balance test efficiency.

[0207] In yet another optional embodiment, Figure 5 As shown, the device may also include:

[0208] The analysis module 308 is used to perform a balance test on each test task based on the test simulation algorithm set by the balance test platform in the test module 303, and after obtaining the test result, analyze the test result to obtain the balance analysis result corresponding to the current game project;

[0209] The judgment module 309 is used to judge whether the current game project meets the preset balance condition according to the balance analysis result;

[0210] The determination module 301 is further used to determine the key balance factors corresponding to the current game project according to the balance analysis result when the judgment module 309 determines that the current game project does not meet the balance condition;

[0211] The generating module 302 is further used to generate optimization suggestions according to the key balance factors; the optimization suggestions include the first optimization suggestions and / or the second optimization suggestions;

[0212] The optimization module 310 is used to optimize the optimization object corresponding to the optimization suggestion according to the optimization suggestion; the optimization object includes the current game project and / or the balance test platform.

[0213] It can be seen that the device described in the implementation of this optional embodiment can obtain a balance analysis result by analyzing the test results. If it is judged based on the balance analysis result that the current game project does not meet the balance conditions, the key balance factors corresponding to the current game project are first determined, and then optimization suggestions are generated based on the key balance factors to optimize the corresponding optimization objects. This can improve the comprehensiveness and accuracy of the analysis of the test results, thereby helping to improve the accuracy of determining the key balance factors, so as to more accurately generate optimization suggestions for the game content or test platform, which in turn helps to improve the optimization accuracy of the game content and the test process.

[0214] In this optional embodiment, the specific manner in which the generation module 302 generates optimization suggestions according to the key balance factors may include:

[0215] Determine the factor type of the key factor of balance; the factor type includes the game design factor type and / or the test design factor type;

[0216] When the factor type of the key balance factor includes a game design factor type, generating a first optimization suggestion for the current game project according to the key balance factor; the first optimization suggestion is used to optimize the game design corresponding to the current game project;

[0217] When the factor type of the key balance factor includes a test design factor type, a second optimization suggestion for the balance test platform is generated based on the key balance factor; the second optimization suggestion is used to optimize the data generation algorithm corresponding to the balance test platform; the data generation algorithm includes a combination of one or more of a test data generation algorithm, an adversarial data generation algorithm and a battle matching algorithm.

[0218] It can be seen that the device described in the implementation of this optional embodiment can also generate optimization suggestions corresponding to different types according to the factor type of the key balance factor, which can improve the accuracy of the analysis of the key balance factors, thereby facilitating targeted optimization of game design and / or test data generation logic, and further facilitating more accurate iterative optimization of game content and test processes.

[0219] In this optional embodiment, the specific manner in which the generation module 302 generates the first optimization suggestion for the current game project according to the key balance factor may include:

[0220] Determine the combat power difference corresponding to each set of test tasks based on key balance factors;

[0221] Filter out the test tasks whose combat power difference is greater than or equal to the preset combat power difference from the combat power difference values ​​corresponding to all the test tasks as the first reference tasks;

[0222] Analyze the test data included in all the first reference tasks to obtain design defect information corresponding to the current game project; the design defect information includes one or more combinations of character design defect information, team design defect information, equipment design defect information, enemy design defect information and level design defect information;

[0223] Based on the design defect information, generate the first optimization suggestion for the current game project.

[0224] It can be seen that the device described in the implementation of this optional embodiment can also screen out the first reference task with a larger combat power gap from all test tasks, and analyze the design defects of the game based on the first reference task, so as to accurately generate the first optimization suggestion for the current game project, and can accurately analyze the defects in the game design based on the test results, which is conducive to improving the accuracy of generating optimization suggestions for game content, thereby further improving the optimization accuracy of game content.

[0225] Embodiment 4

[0226] See also Figure 6 , Figure 6 is a schematic diagram of the structure of another multi-mode game balance testing device disclosed in an embodiment of the present invention. Figure 6 As shown, the multi-mode game balance testing device may include:

[0227] A memory 401 storing executable program codes;

[0228] a processor 402 coupled to the memory 401;

[0229] The processor 402 calls the executable program code stored in the memory 401 to execute part or all of the steps in the multi-mode game balance testing method described in the first embodiment of the present invention or the second embodiment of the present invention.

[0230] Embodiment 5

[0231] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the multi-mode game balance testing method described in Embodiment 1 or Embodiment 2 of the present invention.

[0232] Embodiment 6

[0233] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute some or all of the steps in the multi-mode game balance testing method described in Example 1 or Example 2.

[0234] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0235] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0236] Finally, it should be noted that the multi-mode game balance testing method and device disclosed in the embodiments of the present invention disclose only the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-mode game balance testing method, characterized in that: The method is applied to a balance test platform, and the method comprises: Determine the test requirements corresponding to the current game project; the test requirements include test game mode, test mode setting parameters and test objects; According to the test requirements, multiple groups of test data that meet the test requirements are generated; wherein, when the test requirements include at least two of the test game modes, all of the test data include at least one group of test data for each of the test game modes; Based on the data generation algorithm set by the balance test platform, according to the test requirements, generate adversarial data corresponding to each group of the test data; Based on the test simulation algorithm set by the balance test platform, a balance test is performed for each test task to obtain a test result; each of the test tasks includes a set of the test data and adversarial data corresponding to the test data.

2. The multi-mode game balance testing method according to claim 1, characterized in that: The test game mode includes a PVP mode and / or a PVE mode; when the test game mode includes the PVP mode, the test mode setting parameters include test battle parameters, and the test battle parameters include a test battle map and / or a test battle duration; When the test game mode includes the PVE mode, the test mode setting parameters include test level parameters, and the test level parameters include test level type and / or test level difficulty; the test object includes a combination of one or more of a target character, a target lineup, a target value, a target level, and a target difficulty; Each group of the test data includes a test lineup; the test lineup includes at least one test character; each group of the test data also includes test character parameters corresponding to each of the test characters in the test lineup; the test character parameters include a combination of one or more of the test character level, test character equipment and test character skills; For each group of test data, when the test game mode corresponding to the test data is the PVP mode, the adversarial data corresponding to the test data include the adversarial lineup and the adversarial character parameters corresponding to each adversarial character in the adversarial lineup; when the test game mode corresponding to the test data is the PVE mode, the adversarial data corresponding to the test data include the level enemy lineup and the enemy parameters corresponding to each level enemy in the level enemy lineup.

3. The multi-mode game balance testing method according to claim 1, characterized in that: Before generating multiple groups of test data satisfying the test requirements according to the test requirements, the method further includes: Receive custom account parameters input by the tester; or, generate custom account parameters according to the test requirements; the custom account parameters include one or more combinations of account basic parameters, account role parameters, account resource parameters and account mode parameters; the account basic parameters include one or more combinations of account quantity, account type, account level and account resources; the account role parameters include one or more combinations of character quantity, character type, character level, character equipment and character skills; the account mode parameters include the game mode type applicable to the test account to be generated; Generate multiple test accounts according to the custom account parameters, and import all the test accounts into the balance testing platform; And, generating multiple groups of test data that meet the test requirements according to the test requirements, including: According to the test requirement, at least one set of test data is generated for each test account so that the test account meets the test requirement.

4. The multi-mode game balance testing method according to any one of claims 1 to 3, characterized in that: The test simulation algorithm set based on the balance test platform performs a balance test for each test task to obtain a test result, including: Based on the distributed computing technology corresponding to the balance test platform, each test task is allocated to a target server that meets the preset allocation conditions; the target server is one of the multiple test servers corresponding to the balance test platform; Based on all the target servers, balance tests are performed in parallel for multiple test tasks until the balance tests are completed for all the test tasks to obtain test results; wherein the test results include test task results corresponding to each of the test tasks; the test task results include a combination of one or more of battle results, character performance results, and test resource consumption results; the battle results include win-loss results and / or battle duration; Wherein, in the process of performing the balance test on multiple test tasks in parallel based on all the target servers until the balance test is completed for all the test tasks and the test results are obtained, the method further includes: Based on the cache technology corresponding to the balance test platform, the calculation results corresponding to each of the test tasks are cached to obtain cached calculation results; the calculation results include the test task results corresponding to the test task and / or the intermediate calculation results in the process of executing the balance test corresponding to the test task; After detecting that the cache calculation result is not empty, before executing the balance test for each of the test tasks, detecting whether the balance test platform has cached the cache calculation result related to the test task; For each of the test tasks, when it is detected that the balance test platform caches a cache calculation result related to the test task, the cache calculation result related to the test task is read, and based on the read cache calculation result, the test task result corresponding to the test task is determined; For each of the test tasks, when it is detected that the balance test platform does not cache the cache calculation results related to the test task, a balance test is performed on the test task based on the target server corresponding to the test task to obtain the test task result corresponding to the test task.

5. The multi-mode game balance testing method according to any one of claims 1 to 3, characterized in that: After performing a balance test on each test task based on the test simulation algorithm set by the balance test platform and obtaining the test result, the method further includes: Analyze the test results to obtain a balance analysis result corresponding to the current game project; According to the balance analysis result, determining whether the current game item meets a preset balance condition; When it is determined that the current game item does not meet the balance condition, determining a key balance factor corresponding to the current game item according to the balance analysis result; Generate an optimization suggestion according to the key balance factor; the optimization suggestion includes a first optimization suggestion and / or a second optimization suggestion; According to the optimization suggestion, the optimization object corresponding to the optimization suggestion is optimized; the optimization object includes the current game project and / or the balance testing platform.

6. The multi-mode game balance testing method according to claim 5, characterized in that: Generating optimization suggestions according to the key balance factors includes: Determine the factor type of the key balance factor; the factor type includes a game design factor type and / or a test design factor type; When the factor type of the key balance factor includes the game design factor type, generating a first optimization suggestion for the current game project according to the key balance factor; the first optimization suggestion is used to optimize the game design corresponding to the current game project; When the factor type of the key balance factor includes the test design factor type, a second optimization suggestion for the balance test platform is generated according to the key balance factor; the second optimization suggestion is used to optimize the data generation algorithm corresponding to the balance test platform; the data generation algorithm includes a combination of one or more of a test data generation algorithm, an adversarial data generation algorithm and a battle matching algorithm.

7. The multi-mode game balance testing method according to claim 6, characterized in that: Generating a first optimization suggestion for the current game project according to the key balance factor includes: Determine the combat power difference corresponding to each group of the test tasks according to the key balance factors; Filter out the test tasks whose combat power difference is greater than or equal to the preset combat power difference from the combat power difference values ​​corresponding to all the test tasks as the first reference task; Analyze the test data included in all the first reference tasks to obtain design defect information corresponding to the current game project; the design defect information includes one or more combinations of character design defect information, team design defect information, equipment design defect information, enemy design defect information and level design defect information; A first optimization suggestion for the current game project is generated based on the design defect information.

8. A multi-mode game balance testing device, characterized in that: The device is applied to a balance test platform, and the device comprises: A determination module is used to determine the test requirements corresponding to the current game project; the test requirements include a test game mode, test mode setting parameters and a test object; A generating module, configured to generate, according to the testing requirement, a plurality of groups of testing data satisfying the testing requirement; wherein, when the testing requirement includes at least two of the testing game modes, all of the testing data include at least one group of testing data for each of the testing game modes; The generating module is further configured to generate adversarial data corresponding to each group of the test data based on the data generating algorithm set by the balance testing platform and according to the test requirements; A test module is used to perform a balance test on each test task based on a test simulation algorithm set by the balance test platform to obtain a test result; each of the test tasks includes a set of the test data and adversarial data corresponding to the test data.

9. A multi-mode game balance testing device, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the multi-mode game balance testing method as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the multi-mode game balance testing method as described in any one of claims 1-7.

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