WO2021104027A1

WO2021104027A1 - Code performance testing method, apparatus and device, and storage medium

Info

Publication number: WO2021104027A1
Application number: PCT/CN2020/128337
Authority: WO
Inventors: 林全昌; 卢道和; 林挺
Original assignee: 深圳前海微众银行股份有限公司
Priority date: 2019-11-28
Filing date: 2020-11-12
Publication date: 2021-06-03
Also published as: CN110990271A

Abstract

A code performance testing method, apparatus and device, and a storage medium. The method comprises: when a performance testing instruction is received, acquiring a source code to be tested and a preset performance statistical code, and determining target functions in the source code to be tested and target statement blocks in the target functions (S10); on the basis of target position information of the target functions and target statement blocks in the source code to be tested, injecting the performance statistical code into a target injection position in the source code to be tested, and taking the source code to be tested, which is subjected to the injection, as a target code (S20); executing the target code, and on the basis of an execution statistical code and line counting statistical code in the performance statistical code, respectively acquiring first performance data of the target functions and second performance data of the target statement blocks (S30); and according to the first performance data and the second performance data, determining a function to be optimized in the target functions, and a sentence to be optimized in the function to be optimized (S40).

Description

Code performance detection method, device, equipment and storage medium

This application claims the priority of the Chinese patent application filed on November 28, 2019, the application number is 201911190460.4, and the title is "Code performance detection method, device, equipment and storage medium", the entire content of which is incorporated into this application by reference in.

Technical field

This application relates to the technical field of financial technology (Fintech), in particular to code performance testing methods, devices, equipment, and computer-readable storage media.

Background technique

With the development of computer technology, more and more technologies are applied in the financial field. The traditional financial industry is gradually transforming to Fintech. However, due to the security and real-time requirements of the financial industry, higher technology is also proposed. Requirements. For the bank’s front-end system, the front-end development usually uses JavaScript to write code. In order to improve the efficiency of code operation, it is necessary to perform performance testing on the code written with JavaScript, and analyze the performance of the code through the test results, and then analyze the performance. The best code is optimized. Since JavaScript is an analytical language, if you want to collect runtime information for dynamic program analysis, there are two implementation schemes in the prior art: one is to use the interface for collecting running data provided by the JavaScript engine to implement JavaScript within a period of time. Export of code running data; the other is to inject running data collection code into compiled source code to collect running data. However, the first implementation scheme is only suitable for large and complex project codes, and the performance statistics data of the functions in the detected code are obtained, so it can only reflect the performance pros and cons of the detected code at the function level; while the second implementation scheme Because it is designed for small code snippets, it cannot be applied to the performance testing of large or medium-sized program codes. The second implementation scheme can only compare the performance of the code snippets tested, and users can only qualitatively pass the test results. Determine whether the performance of the multiple code fragments detected is good or bad. From the above two implementation schemes, it is impossible to know the specific reasons for the poor performance of the code fragments, which leads to the low accuracy of the existing code performance detection results. problem.

Technical solutions

The main purpose of this application is to propose a code performance detection method, device, equipment, and computer-readable storage medium, which aims to solve the technical problem of low accuracy of existing code performance detection results.

To achieve the above objective, the present application provides a code performance detection method, the code performance detection method includes:

When receiving the performance detection instruction, obtain the source code to be tested and the preset performance statistics code, and determine the target function in the source code to be tested and the target sentence block in the target function;

Based on the target function and target location information of the target sentence block in the source code to be tested, inject the performance statistics code into the target injection location in the source code to be tested, and use the injected source code to be tested as the target code;

Execute the target code, and obtain the first performance data of the target function and the second performance data of the target sentence block respectively based on the execution statistics code and the line count statistics code in the performance statistics code;

According to the first performance data and the second performance data, a function to be optimized in the objective function and a sentence to be optimized in the function to be optimized are determined.

In addition, in order to achieve the above objective, the present application also provides a code performance detection device, the code performance detection device including:

The function sentence determination module is used to obtain the source code to be tested and the preset performance statistics code when the performance test instruction is received, and to determine the target function in the source code to be tested and the target sentence block in the target function;

The performance code injection module is used to inject the performance statistics code into the target injection position in the source code to be tested based on the target function and target sentence block target location information in the source code to be tested, and the injected The source code to be tested is used as the target code;

The performance data acquisition module is configured to execute the target code, and obtain the first performance data of the target function and the first performance data of the target sentence block based on the execution statistics code and the line count statistics code in the performance statistics code. 2. Performance data;

The optimized sentence determination module is configured to determine the function to be optimized in the objective function and the sentence to be optimized in the function to be optimized according to the first performance data and the second performance data.

In addition, in order to achieve the above objective, the present application also provides a code performance testing device, the code performance testing device includes: a memory, a processor, and code performance testing stored on the memory and running on the processor A program that implements the steps of the code performance detection method as described above when the code performance detection program is executed by the processor.

In addition, in order to achieve the above-mentioned object, the present application also provides a computer-readable storage medium having a code performance detection program stored on the computer-readable storage medium, and when the code performance detection program is executed by a processor, the above-mentioned The steps of the code performance detection method.

This application enables users to obtain more accurate optimization targets than the entire function. Especially for inexperienced programmers, it is more difficult to analyze the determinants of target code performance through existing code performance test results. This application can directly obtain the execution status of the target sentence block, and then quickly analyze the specific reasons leading to poor code performance, improve the accuracy of the code performance test results, and solve the problem of the existing code performance test results. Technical problems with low accuracy.

Description of the drawings

FIG. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the present application;

FIG. 2 is a schematic flowchart of the first embodiment of the code performance detection method of this application.

Embodiments of the present invention

It should be understood that the specific embodiments described here are only used to explain the present application, and are not used to limit the present application.

As shown in FIG. 1, FIG. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the present application.

The code performance detection device of the embodiment of the present application may be a PC or a server device, on which a Java virtual machine runs.

As shown in FIG. 1, the code performance detection device may include: a processor 1001, such as a CPU, a network interface 1004, a programmer interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to implement connection and communication between these components. The programmer interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard), and the optional programmer interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a magnetic disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

Those skilled in the art can understand that the structure of the device shown in FIG. 1 does not constitute a limitation on the device, and may include more or fewer components than those shown in the figure, or a combination of certain components, or different component arrangements.

As shown in FIG. 1, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a programmer interface module, and a code performance testing program.

In the device shown in Figure 1, the network interface 1004 is mainly used to connect to the back-end server and communicate with the back-end server; the programmer interface 1003 is mainly used to connect to the client (programmer's side) and communicate with the client; and The processor 1001 may be used to call a code performance detection program stored in the memory 1005, and perform operations in the following code performance detection method.

Based on the above hardware structure, an embodiment of the code performance detection method of the present application is proposed.

Referring to FIG. 2, FIG. 2 is a schematic flowchart of a first embodiment of a code performance detection method according to this application. The code performance detection method includes:

Step S10, when receiving the performance testing instruction, obtain the source code to be tested and the preset performance statistical code, and determine the target function in the source code to be tested and the target sentence block in the target function;

At present, for code written in JavaScript, if you want to collect runtime information for dynamic program analysis, there are two implementation schemes in the prior art: one is to use the interface for collecting running data provided inside the JavaScript engine to implement JavaScript within a period of time. Export of code running data; the other is to inject running data collection code into compiled source code to collect running data. However, the first implementation scheme is only suitable for large and complex project codes, and the performance statistics data of the functions in the detected code are obtained, so it can only reflect the performance pros and cons of the detected code at the function level; while the second implementation scheme Because it is designed for small code snippets, it cannot be applied to the performance testing of large or medium-sized program codes. The second implementation scheme can only compare the performance of the code snippets tested, and users can only qualitatively pass the test results. It is judged whether the performance of the multiple code fragments detected is good or bad, and there is no way to know the specific reasons for the poor performance of the code fragments, which leads to the problem of low accuracy of the existing code performance detection results. For example, the current source code to be tested is a medium-sized program code that contains a function that couples multiple functions. If you use v8-profiler to analyze the performance of this source code, it will take a long time to get this The execution statistics of the source code. Among the execution statistics, the CPU occupancy rate and other data are not helpful to the performance analysis of the small and medium-sized program codes. In the execution statistics, the execution data of the functions in the program can only qualitatively determine the function. The pros and cons of performance. At this time, the programmer knows that the performance of this large function is poor according to the test results, which seriously affects the performance of the entire program, but more detailed information cannot be obtained from the test results to determine the specific cause of the poor performance, the programmer It takes a long time to analyze which key statements in this large function can be changed.

In this embodiment, in order to solve the above problems, this application provides a code performance detection method, that is, this application obtains a preset performance statistical code that can detect the performance of the target sentence block, so that the object of the code performance detection is refined. Part of the sentences in the source code to be tested has broken through the limitation in the prior art that only functions in the code to be tested can be used as the smallest refinement object; by injecting the preset performance statistics code into the source code to be tested, the The performance of the target sentence block can be tested through the preset performance statistics code; according to the first and second performance statistics obtained, the user can understand the execution of the function in the target code, and perform the target code according to this execution. More detailed performance analysis than the existing solution; by determining the sentence to be optimized in the function to be optimized, users can get more accurate optimization goals than the entire function, especially for programmers with inexperience. Existing code performance testing results are more difficult to analyze the determinants of the performance of the target code. However, through this application, the execution status of the target sentence block can be directly obtained, and the specific reasons leading to the poor performance of the code can be quickly analyzed. , Improve the accuracy of the code performance detection results, thereby solving the technical problem of low accuracy of the existing code performance detection results. The code performance detection method is applied to a terminal equipped with Node.js (a JavaScript runtime environment based on the Chrome V8 engine).

The performance testing instruction can be initiated by the programmer importing the source code to be tested and the preset performance statistics code, or it can be initiated automatically by the terminal according to the preset instruction. The preset performance statistics code includes line count statistics code, execution statistics code, and related regular expressions, which are used to match the target sentence block and target function in the source code to be tested and detect their performance. They are pre-written and commonly used for most The performance statistics code of the code; for a small part of the more complex source code, the preset performance statistics code can be optimized before use. The target sentence block includes but is not limited to key sentences such as loop sentences, selection sentences, judgment sentences, and return sentences. The target function is all the functions that need to be executed in the source code to be tested. Specifically, the user initiates a code performance test instruction to a computer equipped with Node.js by importing a current medium-sized program code as the source code to be tested, and a general performance statistics code. The computer receives the code performance test instruction, and obtains the source code to be tested and the preset performance statistics code in the performance test instruction. The computer obtains the regular expression from the preset performance statistics code, and matches the source code to be tested line by line through the regular expression, thereby determining the target function in the source code to be tested and the key sentence in the target function.

Step S20, based on the target position information of the target function and the target sentence block in the source code to be tested, inject the performance statistics code into the target injection location in the source code to be tested, and use the injected source code to be tested as Target code

The target location information includes the first location information of the target function in the source code to be detected and the second location information of the target sentence block in the source code to be detected. The target injection location includes a first injection location corresponding to the execution statistics code in the source code to be detected and a second injection location corresponding to the line count statistics code in the source code to be detected.

In this embodiment, the terminal equipped with Node.js injects the above-mentioned performance statistics code into the corresponding position of the source code to be checked. It should be noted that the semantics of the source code to be tested before and after the performance statistics code is injected will not change. Specifically, the performance statistics code includes row count statistics code and execution statistics code. The line count statistics code injects a global object count in the execution context, uses the statement type type + source line number line + source code column number column as the key of the object, and the number of executions is used as the value to record the number of executions of the statement. The statement types include key statements such as if, else if, else, for, while, and return. The key-value pair is initialized to 1 when the first count is performed, and then it continues to overlap. The execution statistics code obtains the start time and end time of the system time before and after the function is executed by injecting performance.now() statements before and after the function. The execution time of the corresponding function can be obtained by subtracting two values, and each time the execution time of a function is obtained, it means that it is executed once. Then you can get the function execution time and execution times. After obtaining the execution time and execution times, record the function execution times and execution time through the global variable profile. The computer encapsulates the line count statistics code into the lineCounter function, and receives three parameters type (statement type), line (source line number), column (source code column number), this function returns undefined (undefined) parameters; it will also execute The statistical code is encapsulated into the functionProfiler function, which receives two parameters: functionName (function name) and time (function execution time). It should be noted that in order to prevent naming conflicts, JavaScript built-in functions will add the corresponding object name. For example, Math.sqrt will be converted to Math_sqrt, and _selfExecution will be used instead for anonymous functions. The computer injects the line count statistics code into the corresponding positions of key sentences such as loop statements, judgment statements, and return statements in the source code to be tested, and injects the execution statistics code into the corresponding locations before and after the function is executed in the source code to be tested.

In some embodiments, the way of injecting the preset performance statistics code may also be to analyze the source code to be detected as an abstract syntax tree, and then inject the corresponding target sentence block into the preset performance statistics code, and finally generate the target code; or One function sinks to the JavaScript parsing engine, and the JavaScript parsing engine outputs the corresponding row count result. However, the parsing process of the abstract syntax tree requires manpower and material resources, and the cost is high, and the JavaScript parsing engine needs to embed the target code into the engine and analyze the code online, which may affect the performance of the code.

Step S30, execute the target code, and obtain the first performance data of the target function and the second performance data of the target sentence block respectively based on the execution statistics code and the line count statistics code in the performance statistics code;

The execution statistics code is used to count the first performance data of the target function in the source code to be tested, and the row count statistics code is used to count the second performance data of the target sentence block in the target function. The first performance data may be the execution times and execution time of the target sentence block. The second performance data includes, but is not limited to, the number of executions of the objective function, the total execution time, and the average execution time.

In this embodiment, the terminal executes the target code based on the operating environment of Node.js, and obtains performance statistics in the execution result. Specifically, during the execution of the target code, the computer reads the data of the global object count in the target code, and parses out the number of executions, the number of rows, and the number of columns of the target sentence block, that is, the value and the line and column in the key, and Write the number of executions in front of the line corresponding to the target code. Then read the data of the global object profile in the target code, analyze the total execution time and execution times of the corresponding function, and obtain the average execution time corresponding to the function through the total execution time and execution times. It should be noted that this application only performs performance testing on the entire function and the target statement block, that is, the key statement, and does not perform performance testing on all statements in the function. First, it takes a long time to detect all statements. This is because most of the detection data obtained by testing all sentences is not helpful to the analysis of the problem, and may also interfere with the analysis of the problem.

Step S40: Determine the function to be optimized in the objective function and the sentence to be optimized in the function to be optimized according to the first performance data and the second performance data.

In this embodiment, the function to be optimized and the sentence to be optimized can be determined by the terminal after analyzing the first performance data and the second performance data, or can be determined by the user after the first performance data and the second performance data are displayed to the user. to make sure. Specifically, the computer analyzes the first performance data, determines the function corresponding to the data that meets the preset conditions as the function to be optimized, obtains the data corresponding to the function to be optimized in the second performance data, and performs the data corresponding to the function to be optimized Analyze and determine the sentence corresponding to the data in the target sentence block that exceeds the preset threshold as the sentence to be optimized.

This application obtains preset performance statistics codes that can locate specific sentences in the code, and then detect the performance of the target sentence block, so that the object of code performance testing is refined to some sentences in the source code to be tested, which breaks through the prior art. Only the functions in the code to be tested can be used as the limit of the minimum refinement object; by injecting the preset performance statistics code into the source code to be tested, the performance of the target sentence block in the source code to be tested can be tested by the preset performance statistics code ;According to the acquisition of the first and second performance statistics, the user can understand the internal execution of the function in the target code, and perform a more detailed performance analysis of the target code based on this execution than the existing scheme; by determining The statement to be optimized in the function to be optimized enables users to obtain more accurate optimization goals than the entire function, especially for programmers with inexperience, through the existing code performance test results on the performance of the target code It is difficult to analyze the determinants, and through this application, the execution status of the target sentence block can be directly obtained, and then the specific reasons leading to poor code performance can be quickly analyzed, and the accuracy of the code performance detection results is improved, thereby solving The existing technical problem of low accuracy of code performance detection results.

Based on the first embodiment shown in FIG. 2 above, a second embodiment of the code performance detection method of the present application is proposed.

In this embodiment, step S10 specifically includes:

Step a: Obtain a first regular expression related to the target function and a second regular expression corresponding to the target sentence block from the performance statistics code, and combine the first regular expression with the second regular expression The regular expression matches the source code to be detected line by line;

In this embodiment, the programmer analyzes the semantic environment of the target sentence block, writes the first regular expression corresponding to the function execution code in the source code to be tested, and the second regular expression corresponding to the key sentence, and Enter the above regular expression into the terminal. The terminal obtains the foregoing first and second regular expressions, and in the process of executing the target code, matches each line of code line by line through the foregoing first and second regular expressions. Specifically, take the selection statement if as an example. The if statement has two manifestations in the code, one is if() {} and the other is if () {}. The programmer writes the corresponding if statement The regular expression /$\s+if\s+?$*.$/, the computer uses this regular expression to match line by line to find the if statement in the source code to be tested.

Step b: When there is a first part of code matching the first regular expression in the source code to be detected, determine that the first part of code is the execution sentence of the target function, and determine the execution sentence according to the execution sentence. The objective function;

In this embodiment, if the matching process ends and the result shows that there is a first part of code matching the first regular expression in the source code to be detected, the terminal can determine that the first part of code is the execution statement of the function in the source code to be detected . Specifically, if the matching result shows that there are six codes matching the first regular expression in the source code to be tested, it is determined that these six codes are all execution statements of the function, that is, there are six codes in the source code to be tested. The function to be executed.

Step c: When there is a second part of code matching the second regular expression in the source code to be detected, it is determined that the second part of code is the target sentence block.

In this embodiment, if the matching process ends and the result shows that there is a second part of code matching the regular expression in the source code to be detected, the terminal can determine that the second part of code is the target sentence block to be found. Specifically, the computer uses /$\s+if\s+?$*.$/ to match the source code to be tested line by line, and the matching result shows that there are five codes that match this regular expression in the source code to be tested, then It can be determined that these five codes are the codes of the judgment statement if.

Further, in this embodiment, after step c, it further includes:

Step d: Obtain the first position information of the execution sentence and the second position information of the target sentence block, and use the first position information and the second position information as the target position information;

In this embodiment, the terminal obtains the first position information corresponding to the target sentence block in the source code to be detected, where the first position information is usually the number of rows and columns of the function execution sentence. And obtain the second position information of the target sentence block in the source code to be detected, the second position information is usually the number of rows and columns of the target sentence block.

Step e: Based on the target position information, determine a first injection position and a second injection position respectively corresponding to the execution statistics code and the row count statistics code, and use the first injection position and the second injection position as the target Injection position

Among them, the first injection position has different positions in different types of key statements, and the second injection position is the position before and after the execution statement of the function.

In this embodiment, the terminal determines the first injection position of the line count statistical code in the source code to be detected and the second injection position of the execution statistical code according to the above-mentioned first position information and the second position information. Specifically, the computer uses the first regular expression to match the source code to be tested line by line, judges the successfully matched statement as the function execution code corresponding to the above function, and injects the const __start = performance.now(); statement before the function execution code, And inject the const __end = performance.now(); statement after the function executes the code. The position before and after the function execution code is the above-mentioned first injection position. Taking the target sentence block as the judgment statement if as an example, the computer obtains the number of rows and columns of a judgment statement if(), and according to this number of rows and columns, replaces the first "in the if() statement with the lineCounter function (", this position is the second injection position, and the injected code is written into the js_profile_code.js file. In more embodiments, the judgment statement else if, loop statement for, and while all have "()" To determine whether the statement is executed, the injection method is consistent with the injection method of the above if statement. For the return statement return, the computer directly inserts the lineCounter function before the return statement determined by the match to complete the injection.

Step f: Inject the performance statistics code into the target injection location, and use the injected source code to be detected as the target code.

In this embodiment, the terminal injects the execution statistics code into the determined first injection position, and injects the row count statistics code into the determined second injection position. After the injection operation is completed, the terminal uses the source code to be tested that has been injected with the execution statistics code and the line count statistics code as the target code to be run.

Further, after step d, it also includes:

Step g, judging whether there is a specific sentence in the target sentence block;

In this embodiment, the terminal determines whether there is a specific sentence in each code determined as the target sentence block through detection and matching. Among them, the specific sentence is the sentence included in the "{}" of the else sentence in the key sentence.

Step h, if the specific sentence exists in the target sentence block, use the position where the specific sentence is located as the first injection position, and inject the line count statistics code into the first injection position;

In this embodiment, if the terminal determines that a specific sentence exists in the current target sentence block, the line count statistics code is injected into the first injection position where the specific sentence is located. Specifically, if it is determined that there is a sentence included in "{}" in this else sentence, the computer injects the lineCounter function into this sentence, and this position is the aforementioned first injection position.

Step i, if the specific sentence does not exist in the target sentence block, add the specific sentence to the target sentence block, and repeat the steps: use the position of the specific sentence as the first injection Position, and inject the row count statistics code into the first injection position.

In this embodiment, if the terminal determines that there is no specific sentence in the current target sentence block, the specific sentence is added to the target sentence block, and the line count statistics code is injected into the first injection position where the specific sentence is located. Specifically, if it is determined that the sentence included in "{}" does not exist in this else sentence, the computer adds this particular sentence to this else sentence, and then injects the line count statistics code into the first sentence where this particular sentence is located. Injection position.

The present application provides a code performance detection method, which further matches the execution sentence and target sentence block of the function in the source code to be tested through regular expressions, thereby improving the efficiency and accuracy of identifying functions and target sentence blocks in the code ; Inject the line count statistics code and execution statistics code into the corresponding positions of the source code to be tested, so that the line count statistics code and execution statistics code can run normally, and the performance data of the target statement block and function are counted, and more detailed code is realized Performance testing: By identifying specific statements, it is possible to accurately determine the injection position of the line count statistics code in the else statement, which improves the accuracy of code injection.

Based on the first embodiment shown in FIG. 2 above, a third embodiment of the code performance detection method of the present application is proposed.

In this embodiment, step S40 specifically includes:

Step j: Obtain the number of function execution times and the function execution time in the first performance data, and determine whether the number of function execution times and the function execution time exceed a preset first threshold and a preset second threshold, respectively;

The function execution time includes the total function execution time and the average function execution time. The preset first threshold value is a value that defines the number of times the function is executed, and the preset second threshold value is a time value that defines the function's execution time. In this embodiment, the preset second threshold can be set to a preset average execution time. The threshold and the preset total execution time threshold are two different values. The above three thresholds can be flexibly set according to specific conditions, which are not specifically limited in this embodiment.

In this embodiment, after the terminal injects the execution statistics code into the corresponding position in the source code to be detected, by running the target code, it obtains the execution times and the total execution time of all the functions executed in the source code to be detected, and calculates each function The average execution time. The data is compared with the preset first threshold, the preset average execution time threshold, and the preset total execution time threshold. Specifically, the computer obtains and displays the second performance data as follows: the number of executions of the main function is 1, the total execution time is 18.17299ms, and the average execution time is 18.17299ms; the number of executions of the prime function is 999, and the total execution time is 14.78644ms. , The average execution time is 0.01480ms; the number of executions of the Math_sqrt function is 999, the total execution time is 0.41335ms, and the average execution time is 0.00041ms. Taking the preset average execution time threshold value of 1 ms, the preset first threshold value of 500, and the preset total execution time threshold value of 10 ms as an example, it is determined whether the above data exceeds the threshold value.

Step k, if the number of executions of the function exceeds the first threshold and the execution time of the function exceeds the second threshold, it is determined that the function corresponding to the data exceeding the first threshold and the second threshold is the function to be optimized ；

In this embodiment, using the data in the above specific embodiment, it can be seen from the above data that the number of executions of the function in the main function, the total execution time of the function, and the average execution time of the function all exceed the threshold, then it is determined that the main function is a function to be optimized; The number of executions of the function in the prime function and the total time of the function exceed the threshold, and the average execution time does not exceed the threshold, the prime function is determined to be a function to be optimized; in the Math_sqrt function, only the number of executions of the function exceeds the threshold, and the execution time of the function is the average of the function If the execution time does not exceed the threshold, it is determined that the Math_sqrt function does not need to be optimized.

Step 1. Obtain the execution times of the target sentence block corresponding to the function to be optimized in the second performance data, and determine whether the execution times of the target sentence block exceeds a preset third threshold;

The preset third threshold is a value for determining the number of executions of the sentence to be optimized, and is flexibly set according to specific conditions.

In this embodiment, the terminal obtains the execution times of the key sentence corresponding to each function to be optimized according to the function to be optimized determined in the objective function. The terminal compares the preset third threshold with the number of executions of the key sentence. Specifically, following the above-mentioned embodiment, it is assumed that the current computer obtains that in the main function, the if statement is executed 300 times, the for statement is executed 50 times, and the return statement is executed 50 times; in the prime function, the for statement is executed 200 times. The return statement was executed 30 times; in the Math_sqrt function, the if statement was executed 20 times, and the return statement was executed 30 times. The preset third threshold is set to 100, and the computer determines whether the above data exceeds the preset third threshold.

Step m: If the number of executions of the target sentence block exceeds the third threshold, it is determined that the sentence corresponding to the data exceeding the third threshold is a sentence to be optimized.

In this embodiment, the terminal determines the sentence corresponding to the data that exceeds the preset third threshold among the execution times of the target sentence block as a sentence to be optimized. Specifically, using the data of the above specific embodiment, it can be determined that the number of executions of the if statement 300 in the main function exceeds the preset third threshold 100, so it is determined that the if statement in the main function is the key statement to be optimized; in the prime function The number of executions of the for statement 200 exceeds the preset third threshold of 100, so it is determined that the for statement in the prime function is a key statement to be optimized.

Further, in this embodiment, step S10 specifically includes:

Step n: When receiving the performance test instruction, obtain the original code in the performance test instruction, and determine whether there is a function to be executed in the original code;

In this embodiment, the user initiates a performance test instruction by importing an original code. The terminal receives the performance test instruction, obtains the original code in the performance test instruction, and uses the function to recognize characters or sentences to determine whether the original code is in the original code. Whether there is a function to be executed. It should be noted that most program codes have functions to be executed, and only some small code fragments may consist of only a few statements, and there are no functions to be executed.

Step o: If the function to be executed exists in the original code, determine that the original code is the source code to be tested, and obtain the performance statistics code;

In this embodiment, if the terminal determines that there is a function to be executed in the original code after identification, it will use this original code as the source code to be tested, and use the solution in this application to perform performance testing on this original code. If there is no function to be executed in the original code, it can be explained that the original code is a small code fragment composed of several statements.

Step p: Determine the target function and target sentence block according to the performance statistics code.

In this embodiment, the terminal obtains the first regular expression and the second regular expression from the preset performance statistics code, and matches the source code to be tested with the first and second regular expressions line by line, and determines the source code to be tested The objective function and objective sentence block.

Further, in this embodiment, before step S40, the method further includes:

Step q, generating a performance reference value of each objective function according to the preset weight, the number of executions of the function of the objective function, and the execution time of the function, wherein the number of executions of the function and the execution time of the function are the second performance data;

The preset weight includes a first weight corresponding to the number of executions of the function and a second weight corresponding to the total execution time of the function. The first weight and the second weight can be flexibly set according to specific conditions.

In this embodiment, the terminal sorts the product of the first weight and the execution times of each function in descending order, obtains the first sequence number of each objective function, uses the first sequence number as the numerator, and sets the objective function As the denominator, the first weight score corresponding to each objective function is obtained. The terminal sorts the product of the second weight and the total execution time of each function in descending order, obtains the second sequence number of each objective function, uses the second sequence number as the numerator, and the number of the objective function as the numerator, and obtains The second weight score corresponding to each objective function. The terminal uses the sum of the first weight score and the second weight score as the performance reference value of each objective function.

Step r, displaying the name of the target function and the corresponding function execution times and function execution time according to the performance reference value from high to low;

In this embodiment, the terminal displays the function name of the function to be optimized and the corresponding total execution time of all current execution functions in order from high to low according to the performance pros and cons weight of each objective function generated after the determination. Number of executions and average execution time. The user analyzes the performance of the objective function through the above display results, and determines the function to be optimized in the objective function.

In step s, the target sentence block names and the corresponding target sentence block execution times are sequentially displayed in descending order of the target sentence block execution times, and the target sentence block execution times are the first performance data.

In this embodiment, the terminal sorts the target sentence blocks corresponding to each function according to the numerical value, and preferentially displays the target sentence blocks with the most execution times in each function and the execution times of each target sentence block. After obtaining the above display results, the user analyzes each target sentence block and determines the sentence to be optimized in the target sentence block. Specifically, if the number of executions of the if statement in the main function is 300, the number of executions of the else statement is 250, the number of executions of the for statement is 200, and the number of executions of the return statement is 400, then the terminal follows the return statement, main The order of statement, if statement, else statement, and for statement is displayed. The user can analyze the performance of the target sentence based on the data displayed above.

Further, the code performance detection method further includes:

Step t, obtaining the tool function in the target code and the performance statistical function in the performance statistical code, and use the tool function and the performance statistical function as the statistical tool function;

The tool function is a method of processing the statistical data, and the performance statistics function is the row count function and the execution statistics function.

In this embodiment, the terminal separately obtains the tool function in the target code, and the row count function and execution statistics function in the performance statistics code, and uses the above tool function, row count function, and execution statistics function as the statistics tool function.

Step u: Write the statistical tool function into a designated file to perform performance data statistics on the next code to be tested based on the statistical tool function in the designated file.

In this embodiment, the terminal writes the above-mentioned statistical tool function into a file named js_profile_code.js, so that when the function and target sentence block in the code are tested again in the future, the above-mentioned function can be called directly from the file js_profile_code.js. Statistical tool function.

The present application provides a code performance detection method. The code performance detection method further directly obtains the execution times of the target sentence block in the function to be optimized, and accurately locates several sentences that reduce the performance of the function to be optimized, so that the code performance is improved. Analysis efficiency saves code performance analysis time; by judging whether the original code is a code with functions to be executed, an optimal scope of application is determined; by giving priority to displaying low-performance functions and target sentence blocks, programmers can Obtain more intuitively the information about the relevant code that takes the longest time and the most execution times, so as to quickly locate the specific function that causes the poor performance of the code, and then locate the target statement block in the function to be optimized, and further improve the code Performance optimization efficiency, while improving user experience; by summarizing statistical tool functions and writing them into specific files, it can be directly called from specific files when relevant functions are needed later, which improves the efficiency of computer performance testing of code.

This application also provides a code performance detection device, including:

The code performance detection device further includes:

The regular acquisition and matching module is used to acquire a first regular expression related to the target function and a second regular expression corresponding to the target sentence block from the performance statistics code, and express the first regular expression The formula matches the source code to be detected line by line with the second regular expression;

The first regular matching module is used to determine that the first part of the code is the execution sentence of the target function when there is a first part of the code matching the first regular expression in the source code to be detected, and according to the The execution sentence determines the objective function;

The second regular matching module is configured to determine that the second part of the code is the target sentence block when there is a second part of the code that matches the second regular expression in the source code to be detected.

The performance code injection module specifically includes:

A location information acquiring unit, configured to acquire first location information of the execution sentence and second location information of the target sentence block, and use the first location information and the second location information as the target location information;

The injection position determining unit is configured to determine, based on the target position information, a first injection position and a second injection position corresponding to the execution statistics code and the line count statistics code, respectively, and compare the first injection position and the second injection position As the target injection position;

The performance code injection unit is configured to inject the performance statistics code into the target injection location, and use the injected source code to be detected as the target code.

The code performance detection device further includes:

The specific sentence judgment module is used to judge whether there is a specific sentence in the target sentence block;

The direct code injection module is configured to, if the specific sentence exists in the target sentence block, use the position of the specific sentence as the second injection position, and inject the line count statistics code into the second Injection position

The code indirect injection module is used to add the specific sentence to the target sentence block if the specific sentence does not exist in the target sentence block, and repeat the steps: take the location of the specific sentence as the target sentence block. The second injection position, and the row count statistical code is injected into the second injection position.

The performance data acquisition module specifically includes:

The function data judgment unit is configured to obtain the number of function execution times and the function execution time in the first performance data, and determine whether the number of function execution times and the function execution time exceed a preset first threshold and a preset second threshold, respectively;

An optimized function determining unit, configured to determine the function corresponding to the data exceeding the first threshold and the second threshold if the number of executions of the function exceeds the first threshold and the execution time of the function exceeds the second threshold Is the function to be optimized;

A sentence data judgment unit, configured to obtain the execution times of the target sentence block corresponding to the function to be optimized in the second performance data, and judge whether the execution times of the target sentence block exceeds a preset third threshold;

The optimized sentence determining unit is configured to determine that the sentence corresponding to the data exceeding the third threshold is a sentence to be optimized if the number of executions of the target sentence block exceeds the third threshold.

For the method executed by the above-mentioned program modules, please refer to the various embodiments of the code performance detection method of the present application, which will not be repeated here.

This application also provides a code performance testing device.

The code performance testing device includes a processor, a memory, and a code performance testing program that is stored on the memory and can run on the processor, where the code performance testing program is executed by the processor to achieve the above The steps of the code performance detection method.

For the method implemented when the code performance detection program is executed, reference may be made to the various embodiments of the code performance detection method of the present application, which will not be repeated here.

The application also provides a computer-readable storage medium.

The computer-readable storage medium of the present application stores a code performance detection program, and when the code performance detection program is executed by a processor, the steps of the code performance detection method described above are implemented.

For the method implemented when the code performance detection program is executed, reference may be made to each embodiment of the code performance detection method of this application, which will not be repeated here.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, It also includes other elements that are not explicitly listed, or elements inherent to the process, method, article, or system. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article, or system that includes the element.

The serial numbers of the foregoing embodiments of the present application are for description only, and do not represent the superiority or inferiority of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better.的实施方式。 Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disks, optical disks), including several instructions to make a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of the present application.

The above are only the preferred embodiments of this application, and do not limit the scope of this application. Any equivalent structure or equivalent process transformation made using the content of the description and drawings of this application, or directly or indirectly used in other related technical fields , The same reason is included in the scope of patent protection of this application.

Claims

A code performance detection method, wherein the code performance detection method includes:

When receiving the performance detection instruction, obtain the source code to be tested and the preset performance statistics code, and determine the target function in the source code to be tested and the target sentence block in the target function;

Based on the target function and target location information of the target sentence block in the source code to be tested, inject the performance statistics code into the target injection location in the source code to be tested, and use the injected source code to be tested as the target code;

Execute the target code, and obtain the first performance data of the target function and the second performance data of the target sentence block respectively based on the execution statistics code and the line count statistics code in the performance statistics code;

According to the first performance data and the second performance data, a function to be optimized in the objective function and a sentence to be optimized in the function to be optimized are determined.
3. The code performance detection method according to claim 1, wherein the step of determining the target function in the source code to be tested and the target sentence block in the target function specifically comprises:

Obtain a first regular expression related to the target function and a second regular expression corresponding to the target sentence block from the performance statistics code, and combine the first regular expression with the second regular expression Match the source code to be detected line by line;

When there is a first part of code matching the first regular expression in the source code to be detected, it is determined that the first part of code is the execution sentence of the target function, and the target function is determined according to the execution sentence ；

When there is a second part of code matching the second regular expression in the source code to be detected, it is determined that the second part of code is the target sentence block.
The code performance detection method according to claim 2, wherein the performance statistics code is injected into the source code to be checked based on the target position information of the target function and the target sentence block in the source code to be checked The target injection position of the target code, the steps to use the injected source code to be detected as the target code specifically include:

Acquiring first position information of the execution sentence and second position information of the target sentence block, and using the first position information and the second position information as the target position information;

Based on the target position information, determine a first injection position and a second injection position respectively corresponding to the execution statistics code and the line count statistics code, and use the first injection position and the second injection position as the target injection positions;

Inject the performance statistics code into the target injection location, and use the injected source code to be detected as the target code.
The code performance detection method according to claim 3, wherein the first position information of the execution sentence and the second position information of the target sentence block are obtained, and the first position information and the second position information are combined After the step of serving as the target location information, it further includes:

Judging whether there is a specific sentence in the target sentence block;

If the specific sentence exists in the target sentence block, use the position where the specific sentence is located as the second injection position, and inject the line count statistics code into the second injection position;

If the specific sentence does not exist in the target sentence block, add the specific sentence to the target sentence block, and repeat the steps: use the position of the specific sentence as the second injection position, and The row count statistics code is injected into the second injection position.
The code performance detection method of claim 1, wherein the function to be optimized in the objective function and the sentence to be optimized in the function to be optimized are determined according to the first performance data and the second performance data The specific steps include:

Acquiring the number of function execution times and the function execution time in the first performance data, and determining whether the number of function execution times and the function execution time exceed a preset first threshold and a preset second threshold, respectively;

If the number of executions of the function exceeds the first threshold and the execution time of the function exceeds the second threshold, determining that the function corresponding to the data exceeding the first threshold and the second threshold is a function to be optimized;

Acquiring the execution times of the target sentence block corresponding to the function to be optimized in the second performance data, and determining whether the execution times of the target sentence block exceeds a preset third threshold;

If the number of executions of the target sentence block exceeds the third threshold, it is determined that the sentence corresponding to the data exceeding the third threshold is a sentence to be optimized.
The code performance detection method according to claim 1, wherein when the performance detection instruction is received, the source code to be checked and the preset performance statistics code are obtained, and the target function and the target in the source code to be checked are determined The steps of the target sentence block in the function specifically include:

When receiving the performance detection instruction, obtain the original code in the performance detection instruction, and determine whether there is a function to be executed in the original code;

If the function to be executed exists in the original code, determine that the original code is the source code to be tested, and obtain the performance statistics code;

According to the performance statistics code, the target function and the target sentence block are determined.
The code performance detection method of claim 1, wherein the function to be optimized in the objective function and the sentence to be optimized in the function to be optimized are determined according to the first performance data and the second performance data Before the steps, it also includes:

Generating a performance reference value for each objective function according to a preset weight, the number of executions of the function of the objective function, and the execution time of the function, wherein the number of executions of the function and the execution time of the function are the second performance data;

Display the target function name and the corresponding function execution times and function execution time according to the performance reference value from high to low;

The target sentence block names and the corresponding target sentence block execution times are sequentially displayed in descending order of the target sentence block execution times, wherein the target sentence block execution times are the first performance data.
7. The code performance detection method according to any one of claims 1-7, wherein the code performance detection method further comprises:

Acquiring the tool function in the target code and the performance statistical function in the performance statistical code, and use the tool function and the performance statistical function as the statistical tool function;

Write the statistical tool function into a designated file to perform performance data statistics on the next code to be tested based on the statistical tool function in the designated file.
A code performance detection device, wherein the code performance detection device includes:

The function sentence determination module is used to obtain the source code to be tested and the preset performance statistics code when the performance test instruction is received, and to determine the target function in the source code to be tested and the target sentence block in the target function;

The performance code injection module is used to inject the performance statistics code into the target injection position in the source code to be tested based on the target function and target sentence block target location information in the source code to be tested, and the injected The source code to be tested is used as the target code;

The performance data acquisition module is configured to execute the target code, and obtain the first performance data of the target function and the first performance data of the target sentence block based on the execution statistics code and the line count statistics code in the performance statistics code. 2. Performance data;

The optimized sentence determination module is configured to determine the function to be optimized in the objective function and the sentence to be optimized in the function to be optimized according to the first performance data and the second performance data.
9. The code performance detection device according to claim 9, wherein the code performance detection device further comprises:

The regular acquisition and matching module is used to acquire a first regular expression related to the target function and a second regular expression corresponding to the target sentence block from the performance statistics code, and express the first regular expression The formula matches the source code to be detected line by line with the second regular expression;

The first regular matching module is used to determine that the first part of the code is the execution sentence of the target function when there is a first part of the code matching the first regular expression in the source code to be detected, and according to the The execution sentence determines the objective function;

The second regular matching module is configured to determine that the second part of the code is the target sentence block when there is a second part of the code that matches the second regular expression in the source code to be detected.
9. The code performance detection device according to claim 9, wherein the performance code injection module specifically comprises:

A location information acquiring unit, configured to acquire first location information of the execution sentence and second location information of the target sentence block, and use the first location information and the second location information as the target location information;

The injection position determining unit is configured to determine, based on the target position information, a first injection position and a second injection position corresponding to the execution statistics code and the line count statistics code, respectively, and compare the first injection position and the second injection position As the target injection position;

The performance code injection unit is configured to inject the performance statistics code into the target injection location, and use the injected source code to be detected as the target code.
11. The code performance detection device of claim 11, wherein the code performance detection device further comprises:

The specific sentence judgment module is used to judge whether there is a specific sentence in the target sentence block;

The direct code injection module is configured to, if the specific sentence exists in the target sentence block, use the position of the specific sentence as the second injection position, and inject the line count statistics code into the second Injection position

The code indirect injection module is used to add the specific sentence to the target sentence block if the specific sentence does not exist in the target sentence block, and repeat the steps: take the location of the specific sentence as the target sentence block. The second injection position, and the row count statistical code is injected into the second injection position.
The code performance detection device according to any one of claims 9-12, wherein the performance data acquisition module specifically comprises:

The function data judgment unit is configured to obtain the number of function execution times and the function execution time in the first performance data, and determine whether the number of function execution times and the function execution time exceed a preset first threshold and a preset second threshold, respectively;

An optimized function determining unit, configured to determine the function corresponding to the data exceeding the first threshold and the second threshold if the number of executions of the function exceeds the first threshold and the execution time of the function exceeds the second threshold Is the function to be optimized;

A sentence data judgment unit, configured to obtain the execution times of the target sentence block corresponding to the function to be optimized in the second performance data, and judge whether the execution times of the target sentence block exceeds a preset third threshold;

The optimized sentence determining unit is configured to determine that the sentence corresponding to the data exceeding the third threshold is a sentence to be optimized if the number of executions of the target sentence block exceeds the third threshold.
A code performance testing device, wherein the code performance testing device includes a memory, a processor, and a code performance testing program stored on the memory and running on the processor, the code performance testing program being When the processor is executed, the steps of the code performance detection method according to any one of claims 1 to 8 are implemented.
A computer-readable storage medium, wherein a code performance detection program is stored on the computer-readable storage medium, and when the code performance detection program is executed by a processor, the method according to any one of claims 1 to 8 is realized. The steps of the code performance detection method.