JP7258171B2 - Impact analysis device, impact analysis method, and impact analysis program - Google Patents

Description

The present invention relates to a software influence analysis device, an influence analysis method, and an influence analysis program.

Various techniques have been proposed for impact analysis devices that analyze the impact of source code changes on software. For example, Patent Literature 1 proposes a technique for extracting the range of influence from the dependency relationships of functions and variables. For example, Patent Literature 2 proposes a technique of measuring execution traces obtained by inserting tags into source code and collecting execution times of functions.

For example, Patent Document 3 proposes a technique of holding function names in memory, and Patent Document 4, for example, proposes a technique of comparing function call histories. For example, Patent Document 5 proposes a sampling trace that collects many sequences of machine instructions at appropriate intervals. For example, Japanese Patent Application Laid-Open No. 2002-200000 proposes a technique for evaluating the degree of deviation of job histories including job types and their execution times.

JP 2015-11661 A JP-A-11-316696 Japanese Patent Application Laid-Open No. 2001-282576 JP 2006-053788 A Japanese Patent Application Laid-Open No. 2004-078338 WO2018/146714

However, conventional impact analyzers use dependencies obtained by static analysis without considering software execution. Therefore, there is a problem that even if it is possible to confirm the influence of the change in the processing content, it is not possible to confirm the influence of the difference in the conditions when the software is executed.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made in view of the above-described problems, and an object of the present invention is to provide a technique capable of displaying the effects of differences in conditions when software is executed.

An impact analysis apparatus according to the present invention collects, under a plurality of different conditions, a plurality of execution traces including a plurality of events including an entry event and an exit event of a function in software and a plurality of execution traces including the times of the plurality of events. a trace collection unit; an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit; and the plurality of events based on the plurality of execution traces accumulated in the execution trace accumulation unit. a representative execution trace calculating unit for calculating a representative execution trace including the average and variation of the times of each of the plurality of events; and a representative execution for accumulating the representative execution trace calculated by the representative execution trace calculating unit. a trace accumulation unit, an output unit for outputting the representative execution trace accumulated in the representative execution trace accumulation unit, and a tolerance based on the average contained in the representative execution trace accumulated in the representative execution trace accumulation unit. an extraction unit that defines a range and extracts the execution trace whose time is outside the allowable range from among the plurality of execution traces accumulated in the execution trace accumulation unit ; The execution trace extracted in the section is superimposed on the representative execution trace used for extraction and displayed .

According to the present invention, based on a plurality of execution traces collected under a plurality of different conditions, a representative execution trace including averages and variations in time for each of a plurality of events is calculated and displayed. According to such a configuration, it is possible to display the influence of the difference in conditions when the software is executed.

Objects, features, aspects and advantages of the present invention will become more apparent from the following detailed description and accompanying drawings.

1 is a block diagram showing the configuration of an influence analysis device according to Embodiment 1; FIG. FIG. 3 is a diagram showing an example of execution trace according to the first embodiment; FIG. FIG. 4 is a diagram showing an example of a representative execution trace according to Embodiment 1; FIG. FIG. 3 is a diagram showing a display example of the influence analysis device according to Embodiment 1; FIG. 4 is a flow chart showing the operation of the influence analysis device according to Embodiment 1; 4 is a flow chart showing the operation of the influence analysis device according to Embodiment 1; FIG. 11 is a block diagram showing the configuration of an influence analysis device according to Embodiment 2; FIG. 9 is a flow chart showing the operation of the influence analysis device according to Embodiment 2; 9 is a flow chart showing the operation of the influence analysis device according to Embodiment 2; FIG. 11 is a diagram for explaining an operation example of the influence analysis device according to the second embodiment; FIG. 11 is a diagram for explaining an operation example of the influence analysis device according to the second embodiment; FIG. 10 is a diagram showing a display example of the influence analysis device according to the second embodiment; FIG. 11 is a block diagram showing the configuration of an influence analysis device according to Embodiment 3; FIG. 13 is a diagram showing examples of a start event and an end event according to Embodiment 3; FIG. FIG. 12 is a diagram for explaining an operation example of the influence analysis device according to Embodiment 3; 11 is a flow chart showing the operation of the influence analysis device according to Embodiment 3; FIG. 12 is a block diagram showing the configuration of an influence analysis device according to Embodiment 4; FIG. 12 is a diagram for explaining an example of a mapping rule according to the fourth embodiment; FIG. FIG. 14 is a diagram for explaining an operation example of the influence analysis device according to the fourth embodiment; 14 is a flow chart showing the operation of the influence analysis device according to Embodiment 4;

<Embodiment 1>
FIG. 1 is a block diagram showing the configuration of an influence analysis device according to Embodiment 1 of the present invention. This influence analysis device is a device that analyzes the influence on the performance of software due to changes such as source code. Hereinafter, the effect will be described as "change effect", the software before change will be described as "pre-change software", and the software after change will be described as "post-change software".

The influence analysis device shown in FIG. The input of execution trace accumulation unit 2 is connected to the output of execution trace collection unit 1 . The input of representative execution trace calculator 3 is connected to the output of execution trace storage 2 . The input of the representative execution trace storage section 4 is connected to the output of the representative execution trace calculation section 3 . The input of the display section 5 is connected to the output of the representative execution trace accumulation section 4 .

The execution trace collection unit 1 is a tool that collects a plurality of execution traces under a plurality of different conditions. Although details will be described later, an execution trace is an event sequence that includes a plurality of events including entry and exit events of one or more functions in software, and the times of the plurality of events. The entrance event and the exit event can also be referred to as an entrance passage event and an exit passage event, respectively. The time is the measured time from one point in time to another point in time. For example, the event time is the measured time from the reference point in time to the time the event occurred.

The execution trace collection unit 1 may be, for example, a tool that inserts additional code into the source code, that is, an instrumenting tool. Alternatively, the execution trace collection unit 1 may be, for example, a tool that has a debugger that collects instruction traces obtained from a macrocell of a microprocessor and that has a log generation function in which a logging function is manually embedded in the source code. Alternatively, the execution trace collection unit 1 may be, for example, a sampling trace tool capable of acquiring history at sampling intervals shorter than those of events to be monitored.

FIG. 2 is a diagram showing an example of the execution trace 6. As shown in FIG. The execution trace 6 includes multiple events, including function entry and exit events, and the times at which the multiple events occur. The time may be, for example, the elapsed time from the start of tracing, or the time difference between the event and the immediately preceding event. In the example of FIG. 2, the elapsed time is shown as the time of the entry event and the exit event for the funcA function, the funcB function called from the funcA function, and the funcC function called from the funcA function, and the difference time is shown in parentheses. ing.

funcA@enter indicates the entry of the funcA function, and funcA@leave indicates the exit of the funcA function. Similarly, funcB@enter indicates the entry of the funcB function, funcB@leave indicates the exit of the funcB function, funcC@enter indicates the entry of the funcC function, and funcC@leave indicates the exit of the funcC function.

In the example of FIG. 2, the funcA function first starts processing at 0 ns (0 ns), and the funcA function calls the funcB function at 70 ns (70 ns). Then, the funcB function finishes processing in 280 ns (210 ns), the funcA function performs processing again, and the funcA function calls the funcC function in 330 ns (50 ns). The funcC function finishes processing in 500 ns (170 ns), and the funcA function performs processing again and finishes processing in 600 ns (100 ns).

A plurality of execution traces 6 are collected by operating the software to be processed under a plurality of conditions, and substantially statistically processed by the representative execution trace calculator 3 as described later. The plurality of conditions differ from each other in, for example, at least one of the continuous operating time, the number of other processes and tasks, and the activation environment of the other processes and tasks.

The execution trace accumulation unit 2 accumulates a plurality of execution traces 6 collected by the execution trace collection unit 1. FIG. A plurality of execution traces 6 may be stored in the execution trace storage unit 2 independently of each other, or may be stored in the execution trace storage unit 2 after being continuously connected or combined in a mutually distinguishable state. good.

The representative execution trace calculator 3 calculates a representative execution trace by performing statistical processing based on the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2 .

FIG. 3 is a diagram showing an example of the representative execution trace 7. As shown in FIG. The representative execution trace 7 is an event series including a plurality of events and the average and variation of the respective times of the plurality of events. The multiple events of the representative execution trace 7 are the same as the multiple events of the execution trace 6 used to calculate the representative execution trace 7 . The time may be, for example, elapsed time or differential time, as described above. Variation may be variance or standard deviation, for example. FIG. 3 shows an average difference time and a variance difference time as examples of the average and variation of the times of the representative execution trace 7 . Hereinafter, the case where the time is the differential time and the variation is the dispersion will be mainly described, but the same applies to the case where the time is the elapsed time and the variation is the standard deviation.

In the example of FIG. 3, the funcA function first starts processing with 0 ns and a variance of 0 ns, and the funcA function calls the funcB function with an average of 70 ns and a variance of 10 ns. The funcB function finishes processing with an average of 200 ns and a variance of 20 ns, the funcA function performs processing again, and the funcA function calls the funcC function with an average of 30 ns and a variance of 15 ns. The funcC function finishes processing with an average of 170 ns and a variance of 13 ns, and the funcA function performs processing again and finishes with 110 ns and a variance of 10 ns.

The representative execution trace accumulation section 4 accumulates the representative execution trace 7 calculated by the representative execution trace calculation section 3 .

The display unit 5 selects a representative execution trace 7 accumulated in the representative execution trace accumulation unit 4 and displays the selected representative execution trace 7 in the form of a timing chart. In the following explanation, the output unit is the display unit 5 that displays the representative execution trace 7, but it is not limited to this, and may be, for example, a communication unit that transmits the representative execution trace 7. FIG. Since the representative execution trace 7 has statistically processed averages and variations for each event, event transitions, which are function transitions, are displayed with event occurrence intervals corresponding to the averages and variations.

FIG. 4 is a display example of the representative execution trace 7 on the display unit 5. As shown in FIG. FIG. 4 shows an operation in which the funcA function calls the funcB function and the funcC function in this order. The display unit 5 displays the transition of the function based on the representative execution trace 7, which is the result of statistical processing. For example, the display unit 5 displays the transition of the function with an event occurrence interval of “average differential time ±2×dispersed differential time”. In the example of FIG. 4, the display unit 5 expresses the function transition from the funcA function and the like to the funcB function and the like with two arrows. The arrow on the left side indicates "average differential time - 2 x variance differential time", and the arrow on the right side indicates "average differential time + 2 x variance differential time".

The execution trace collection unit 1, the execution trace storage unit 2, the representative execution trace calculation unit 3, and the representative execution trace storage unit 4 process the pre-change software and the post-change software, respectively. The display unit 5 displays the representative execution trace 7 of the pre-change software and the representative execution trace 7 of the post-change software, so that the user can confirm the influence of the change.

<Action>
FIG. 5 is a flow chart showing the operation of visualizing the change impact by the impact analysis device according to the first embodiment. This operation will be described below with reference to FIG.

In steps S1 to S3, the pre-change software is processed. First, in step S1, the execution trace collection unit 1 acquires the execution trace 6 of the pre-change software under certain conditions and accumulates it in the execution trace accumulation unit 2. FIG. After accumulation, the process proceeds to step S2.

In step S2, the execution trace collection unit 1 determines whether or not the number of times the execution trace 6 has been acquired has reached a specified number of times specified in advance. If it is determined that the threshold has not been reached, the process returns to step S1. If it is determined that the time has been reached, the process proceeds to step S3. As described above, a plurality of execution traces 6 collected under a plurality of different conditions are accumulated in the execution trace accumulation unit 2. FIG.

At step S3, the representative execution trace calculation unit 3 calculates a representative execution trace 7 of the pre-change software based on the plurality of execution traces 6 of the pre-change software accumulated in the execution trace accumulation unit 2, and calculates the representative execution trace. Stored in the storage unit 4 . After accumulation, the process proceeds to step S4.

In steps S4 to S6, the same processing as in steps S1 to S3 is performed on the post-change software. First, in step S<b>4 , the execution trace collection unit 1 acquires the execution trace 6 of the post-change software under certain conditions and stores it in the execution trace storage unit 2 . After accumulation, the process proceeds to step S5.

In step S5, the execution trace collection unit 1 determines whether or not the number of times the execution trace 6 has been acquired has reached a specified number of times specified in advance. If it is determined that the threshold has not been reached, the process returns to step S4. If it is determined that it has reached, the process proceeds to step S6.

In step S6, the representative execution trace calculation unit 3 calculates a representative execution trace 7 of the post-change software based on the plurality of execution traces 6 of the post-change software accumulated in the execution trace accumulation unit 2, and Stored in the storage unit 4 . After accumulation, the process proceeds to step S7.

At step S<b>7 , the display unit 5 displays the representative execution trace 7 accumulated in the representative execution trace accumulation unit 4 . The display unit 5, for example, selectively or simultaneously displays the representative execution trace 7 of the pre-change software and the representative execution trace 7 of the post-change software. This allows the user to check the effect on the performance of the software due to the change made between the pre-change software and the post-change software. After the display, the operation of FIG. 5 ends.

FIG. 6 is a flow chart showing the operation of calculating the representative execution trace 7 in steps S3 and S6. This operation will be described below with reference to FIG.

First, in step S11, the representative execution trace calculator 3 empties the event series list. After that, the process proceeds to step S12.

At step S<b>12 , the representative execution trace calculation unit 3 acquires the execution trace 6 from the execution trace storage unit 2 . After acquisition, the process proceeds to step S13.

At step S13, the representative execution trace calculator 3 checks whether the event sequence of the execution trace 6 obtained at step S12 exists in the event sequence list. If it does not exist, the process proceeds to step S14, and if it exists, the process proceeds to step S15.

In step S14, the representative execution trace calculator 3 adds the event series that did not exist to the event series list. After the addition, the process proceeds to step S15.

In step S15, the representative execution trace calculator 3 calculates the difference time from the immediately preceding event for the events of the event series in the event series list. After the calculation, the process proceeds to step S16.

At step S<b>16 , the representative execution trace calculator 3 determines whether or not there is an unprocessed execution trace 6 among the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2 . If it is determined to exist, the process returns to step S12, and the representative execution trace calculator 3 acquires the unprocessed execution trace 6 from the execution trace storage 2 in step S12. If it is determined that it does not exist, the process proceeds to step S17. Through the above operations, the same type of event is obtained in the same number as the plurality of execution traces 6 at maximum, and the difference time is calculated for each. For example, when N (N is a natural number equal to or greater than 1) execution traces 6 shown in FIG. be. That is, the differential times of one type of N (N is a natural number equal to or greater than 1) events are calculated.

In step S17, the representative execution trace calculator 3 acquires one or more events of one type from the event series list. After acquisition, the process proceeds to step S18.

In step S18, the representative execution trace calculation unit 3 calculates an average value and a variance value from the differential times of one or more events of one type. The representative execution trace calculator 3 generates a representative execution trace 7 including one type of event and the average differential time and variance differential time of the one type of event. After that, the process proceeds to step S19.

In step S19, the representative execution trace calculator 3 determines whether or not there is an unprocessed event in the event series list. If it is determined that the event exists, the process returns to step S17, and in step S17, the representative execution trace calculator 3 acquires an unprocessed event from the event sequence list. If it is determined that it does not exist, the operation of FIG. 6 ends.

<Summary of Embodiment 1>
According to the impact analysis apparatus according to the first embodiment as described above, based on a plurality of execution traces 6 collected under a plurality of different conditions, the average and variation of each time of a plurality of events are calculated. A representative execution trace 7 is calculated and displayed. According to such a configuration, it is possible to perform a display for confirming the influence of the difference in software execution conditions on the performance of the software, for example, the influence of other tasks, other processes, interrupts, and the like. Therefore, the user can confirm the performance impact considering the impact.

<Embodiment 2>
According to the first embodiment, the user compares the average time, which is the average of the times of the representative execution trace 7, with the time of the execution trace 6, and identifies the execution trace 6 having a certain amount of difference from the representative execution trace 7. Therefore, the cause of the difference can be investigated. However, if the event sequence of the representative execution trace 7 is long, or if the number of execution traces 6 is large, the work becomes difficult. In view of this, as will become clear from the following description, the effect analysis apparatus according to the second embodiment of the present invention automatically extracts an execution trace 6 having a certain amount of difference from the representative execution trace 7. is possible.

FIG. 7 is a block diagram showing the configuration of the influence analysis device according to the second embodiment. Hereinafter, among the constituent elements according to the second embodiment, constituent elements that are the same as or similar to the above-described constituent elements are denoted by the same or similar reference numerals, and different constituent elements will be mainly described.

The configuration of the impact analysis device shown in FIG. 7 is the same as the configuration of the impact analysis device according to the first embodiment (FIG. 1) with an execution trace outlier extraction unit 8 added as an extraction unit. The input of execution trace accumulation unit 2 is connected to the output of execution trace collection unit 1 . The input of representative execution trace calculator 3 is connected to the output of execution trace storage 2 . The input of representative execution trace calculator 3 is connected to the output of execution trace storage 2 . The input of the representative execution trace storage section 4 is connected to the output of the representative execution trace calculation section 3 . The input of the execution trace outlier extraction unit 8 is connected to the output of the execution trace accumulation unit 2 and the output of the representative execution trace accumulation unit 4 . The input of the display unit 5 is connected to the output of the representative execution trace accumulation unit 4 and the output of the execution trace outlier extraction unit 8 .

In the second embodiment, the representative execution trace accumulation unit 4 accumulates a plurality of representative execution traces 7 (for example, traces similar to traces A to D in FIG. 10) having different combinations of a plurality of events. The fact that the combination of a plurality of events is different includes that at least one of the types and the number of events is different.

The execution trace outlier extracting unit 8 extracts the difference between the combination of the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2 and the plurality of events among the plurality of representative execution traces 7 accumulated in the representative execution trace accumulation unit 4. Get the representative execution trace 7 with the smallest . Hereinafter, the representative execution trace 7 acquired by the execution trace outlier extracting unit 8 may also be referred to as "the representative execution trace 7 of the nearest neighborhood sequence".

The execution trace outlier extraction unit 8 defines an allowable range based on the average time included in the representative execution trace 7 of the nearest neighbor sequence, and extracts the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2. Among them, an execution trace 6 whose time is outside the permissible range is extracted. Hereinafter, the execution trace 6 extracted by the execution trace outlier extraction unit 8 may be referred to as an "outlier execution trace 6".

The display unit 5 displays the execution trace 6 of the outlier extracted by the execution trace outlier extraction unit 8 superimposed on the representative execution trace 7 of the nearest neighbor sequence used for extraction. Thereby, the user can confirm the representative execution trace 7 and the execution trace 6 having some difference from the representative execution trace 7 .

<Action>
FIG. 8 is a flow chart showing the operation of visualizing the change impact by the impact analysis device according to the second embodiment. This operation will be described below with reference to FIG.

In steps S21 to S23, processing similar to that of steps S1 to S3 in FIG. 5 described in the first embodiment is performed on the pre-change software. First, in step S21, the execution trace collection unit 1 acquires the execution trace 6 of the pre-change software under certain conditions, and accumulates it in the execution trace accumulation unit 2. FIG. After accumulation, the process proceeds to step S22.

In step S22, the execution trace collection unit 1 determines whether or not the number of acquisitions of the execution trace 6 has reached a specified number of times specified in advance. If it is determined that the threshold has not been reached, the process returns to step S21. If it is determined that the time has been reached, the process proceeds to step S23. As a result, a plurality of execution traces 6 of the pre-change software are accumulated in the execution trace accumulation unit 2 .

At step S23, the representative execution trace calculation unit 3 calculates a representative execution trace 7 of the pre-change software based on the plurality of execution traces 6 of the pre-change software accumulated in the execution trace accumulation unit 2, and calculates the representative execution trace. Stored in the storage unit 4 .

The above processing is performed for a plurality of execution traces 6 (for example, traces similar to traces A to D in FIG. 10) having different combinations of a plurality of events. As a result, a plurality of representative execution traces 7 having different combinations of a plurality of events are accumulated in the representative execution trace accumulation unit 4 for the pre-change software. After accumulation, the process proceeds to step S24.

In steps S24 and S25, the same processing as in steps S21 and S22 is performed on the post-change software. As a result, a plurality of execution traces 6 of the post-change software are accumulated in the execution trace accumulation unit 2 . After accumulation, the process proceeds to step S26.

In step S26, the execution trace outlier extracting unit 8 acquires the representative execution trace 7 of the nearest neighbor series of the pre-change software from the plurality of representative execution traces 7 of the pre-change software accumulated in the representative execution trace accumulation unit 4. do. Then, the execution trace outlier extraction unit 8 compares the representative execution trace 7 of the nearest neighbor series of the pre-change software with the plurality of execution traces 6 of the post-change software accumulated in the execution trace accumulation unit 2, and Extract an outlier execution trace 6 for the software. Then, the display unit 5 displays the execution trace 6 of the extracted outlier superimposed on the representative execution trace 7 of the nearest neighbor series. As a result, the user can confirm the representative execution trace 7 of the pre-change software and the execution trace 6 of the post-change software having a certain amount of difference from the representative execution trace 7 .

FIG. 9 is a flow chart showing the operation of acquiring the representative execution trace 7 of the nearest neighbor series and the operation of extracting and displaying the outlier execution trace 6 in step S26. These operations will be described below with reference to FIG.

First, in step S<b>31 , the execution trace outlier extraction unit 8 acquires the representative execution trace 7 from the representative execution trace accumulation unit 4 . After acquisition, the process proceeds to step S32.

In step S32, the execution trace outlier extraction unit 8 extracts a combination of multiple events between the representative execution trace 7 acquired in step S31 and the multiple execution traces 6 accumulated in the execution trace accumulation unit 2. Calculate the difference between After the calculation, the process proceeds to step S33.

In step S33, the execution trace outlier extraction unit 8 determines whether the difference calculated in step S32 is smaller than the difference similarly calculated for the representative execution trace 7 of the nearest neighbor series. If determined to be small, the process proceeds to step S34, and if determined not to be small, the process proceeds to step S35.

In step S34, the execution trace outlier extraction unit 8 updates the representative execution trace 7 of the nearest neighborhood sequence to the representative execution trace 7 acquired in step S31. After updating, the process proceeds to step S35.

In step S<b>35 , the execution trace outlier extracting unit 8 determines whether or not there is an unprocessed representative execution trace 7 among the plurality of representative execution traces 7 accumulated in the representative execution trace accumulation unit 4 . If it is determined to exist, the process returns to step S31, and the execution trace outlier extraction unit 8 acquires the unprocessed representative execution trace 7 from the representative execution trace accumulation unit 4 in step S31. If it is determined that it does not exist, the process proceeds to step S36.

FIG. 10 is a diagram for explaining an operation example of steps S32 to S35. In the example of FIG. 10, the reference trace is the execution trace 6 accumulated in the execution trace accumulation unit 2, the trace A is the representative execution trace 7 acquired in the first step S31, . , the representative execution trace 7 acquired in the fourth step S31. Hereinafter, the difference between combinations of multiple events will be abbreviated as "event difference".

In the event series of the reference trace, the funcA function is called, and the funcB and funcC functions are called in the funcA function. Since the event series of trace A is equal to the event series of the reference trace, the event difference is "0".

In the event series of trace B, only the funcC function is called in the funcA function. In other words, in the event series of trace B, the event difference is "2" because there is no entry event or exit event for the funcB function accompanying the call of the funcB function.

In the event series of trace C, the funcB function and the funcD function are called in the funcA function. That is, in the event series of trace C, the funcD function is called instead of the funcC function, and the entrance event and exit event of the funcC function are different from the entrance event and exit event of the funcD function, so the event difference is "2". .

In the event series of trace D, funcB function, funcC function, and funcD function are called in funcA function. Since the number of entry events and exit events of the funcD function has increased by the number of calls of the funcD function, the event difference is "2".

When the execution trace outlier extraction unit 8 performs the processes of steps S32 to S35 for the above example, the execution trace outlier extractor 8 selects the trace A, which has the smallest event difference from the execution trace 6 among the traces A to D, as the nearest neighbor sequence. Acquired as a representative execution trace 7.

In the above description, the combination of the multiple events of the multiple execution traces 6 to be compared with the representative execution trace 7 is the same, but it may be different. In such a case, for example, the execution trace outlier extracting unit 8 obtains the event difference between each execution trace 6 and the representative execution trace 7, and the sum of the differences for a plurality of execution traces 6 is the maximum value. The smaller representative execution trace 7 may be obtained as the representative execution trace 7 of the nearest neighborhood sequence. For example, when there are one first reference trace in FIG. 11 and five second reference traces in FIG. , 2, 10, 14, and 14, respectively. In such a case, the execution trace outlier extraction unit 8 may acquire the trace A, which has the smallest event difference from the execution trace 6 among the traces A to D, as the representative execution trace 7 of the nearest neighborhood sequence.

The processing after step S36 in FIG. 9 is performed for each of the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2. FIG.

First, in step S36, the execution trace outlier extraction unit 8 acquires an event from the representative execution trace 7 of the nearest neighbor sequence. After that, the process proceeds to step S37.

In step S37, the execution trace outlier extraction unit 8 defines an allowable range based on the average time of events acquired in step S36. For example, when the variance included in the representative execution trace 7 is the variance time, the execution trace outlier extraction unit 8 defines the allowable range as the average time±(variance time×2). The execution trace outlier extraction unit 8 determines whether the time of the event of the execution trace 6 is within the allowable range. If it is determined that it fits, the process proceeds to step S38. If it is determined that it does not fit, the process proceeds to step S39.

In step S38, the execution trace outlier extraction unit 8 determines whether or not there is an unprocessed event in the representative execution trace 7 of the nearest neighbor series. If it is determined to exist, the process returns to step S36, and in step S36, the execution trace outlier extraction unit 8 acquires an unprocessed event from the representative execution trace 7 of the nearest neighbor series. If it is determined that it does not exist, the operation of FIG. 9 ends.

In step S39, the execution trace outlier extraction unit 8 determines the execution trace 6 determined in step S37 as the outlier execution trace 6, and the display unit 5 uses the outlier execution trace 6 for extraction. is superimposed on the representative execution trace 7 of the nearest neighbor series. After the display, the operation of FIG. 9 ends.

FIG. 12 is a diagram showing a display example of step S39. The dotted line indicates the representative execution trace 7 of the nearest neighbor sequence, and the solid line indicates the outlier execution trace 6 . According to the display as shown in FIG. 12, among the outlier execution traces 6, the transition timing from the funcA function to the funcB function and the transition timing from the funcA function to the funcC function are the allowable values of the representative execution trace 7. It can be read that it is out of range.

<Summary of Embodiment 2>
According to the impact analysis apparatus according to the second embodiment as described above, among the plurality of execution traces 6 accumulated in the execution trace accumulation unit 2, the execution traces 6 whose times are outside the allowable range are extracted and displayed. do. According to such a configuration, the user can confirm the representative execution trace 7 and the execution trace 6 having some difference from the representative execution trace 7 . Therefore, it is expected that the investigation of the cause of the execution trace 6 being different from the representative execution trace 7 will be facilitated.

In the above explanation, the execution trace outlier extracting unit 8 extracts the execution trace 6 whose difference from the average time of the representative execution trace 7 of the nearest neighbor series is equal to or greater than a certain value, and the display unit 5 displays the execution trace 6 is displayed, but it is not limited to this. For example, the execution trace outlier extraction unit 8 extracts an execution trace 6 having a certain number or more of differences in combinations of multiple events with respect to the representative execution trace 7 of the nearest neighbor sequence, and the display unit 5 displays the execution trace 6 may be displayed. Such a configuration can also be expected to facilitate the investigation of the cause of the difference.

<Embodiment 3>
In the first and second embodiments, it is assumed that the execution traces 6 collected by the execution trace collection unit 1 have the same start event and end event. If the execution traces 6 collected by the execution trace collection unit 1 do not have the same start event and end event, there is a possibility that the execution traces 6 cannot be compared correctly. In view of this, as will become clear from the following description, in the impact analysis apparatus according to the third embodiment of the present invention, it is possible to align the start and end of events of a plurality of execution traces 6. .

FIG. 13 is a block diagram showing the configuration of an influence analysis device according to the third embodiment. Hereinafter, among the constituent elements according to the third embodiment, constituent elements that are the same as or similar to the above-described constituent elements are denoted by the same or similar reference numerals, and different constituent elements will be mainly described.

The impact analysis device shown in FIG. 13 has the same configuration as the configuration of the impact analysis device according to the second embodiment (FIG. 7) with an event restriction unit 10 added as a restriction unit.

The input of event limiter 10 is connected to the output of execution trace collector 1 . The input of execution trace storage unit 2 is connected to the output of event limiter 10 . The input of representative execution trace calculator 3 is connected to the output of execution trace storage 2 . The input of the representative execution trace storage section 4 is connected to the output of the representative execution trace calculation section 3 . The input of the execution trace outlier extraction unit 8 is connected to the output of the execution trace accumulation unit 2 and the output of the representative execution trace accumulation unit 4 . The input of the display unit 5 is connected to the output of the representative execution trace accumulation unit 4 and the output of the execution trace outlier extraction unit 8 .

The event restriction unit 10 classifies the execution traces 6 accumulated in the execution trace accumulation unit 2 into pre-designated start events and pre-designated end events from the execution traces 6 collected by the execution trace collection unit 1. Execution trace 6 with If the execution trace 6 collected by the execution trace collection unit 1 contains one or more event sequences from the same event as the start event to the same event as the end event, the event restriction unit 10 defines the event sequence as the execution trace 6. , is stored in the execution trace accumulation unit 2 . If the execution trace 6 collected by the execution trace collection unit 1 does not contain even one event series from the same event as the start event to the same event as the end event, the event restriction unit 10 transfers the execution trace 6 to the execution trace accumulation unit 2. Do not store in

14A and 14B are diagrams showing examples of start events and end events specified by the event restriction unit 10. FIG. In FIG. 14, the entry event of the funcA function is designated as the start event, and the exit event of the funcA function is designated as the end event.

FIG. 15 is a diagram for explaining an example of event restriction using the start event and exit event of FIG. 14; In the input event sequence, that is, the execution trace 6 collected by the execution trace collection unit 1, the funcE function calls the funcA function, and then the funcA function calls the funcB function and the funcC function in this order. As shown in FIG. 14, when the entry event and the exit event of the funcA function are specified as the start event and the end event, the event limiter 10 limits only the event series in which the funcA function calls the funcB function and the funcC function in this order. , is output as an output event sequence. As a result, in the examples of FIGS. 14 and 15 , an event sequence that does not include the entry event and exit event of the funcE function is accumulated as the execution trace 6 in the execution trace accumulation unit 2 .

<Action>
FIG. 16 is a flow chart showing the operation of the event limiter 10. As shown in FIG. This operation will be described below with reference to FIG.

First, in step S41, the event limiter 10 sets the output flag to invalid. After that, the process proceeds to step S42.

At step S<b>42 , the event restriction unit 10 acquires events from the execution traces 6 collected by the execution trace collection unit 1 . After that, the process proceeds to step S43.

In step S43, the event restriction unit 10 determines whether or not the output flag is set to valid. If it is determined that the output flag is set valid, the process proceeds to step S47, and if it is determined that the output flag is set invalid, the process proceeds to step S44.

At step S44, the event restriction unit 10 determines whether or not the event acquired at step S42 matches the start event. If it is determined that they match, the process proceeds to step S45, and if it is determined that they do not match, the process proceeds to step S50.

In step S45, the event limiter 10 sets the output flag to valid. After that, the process proceeds to step S46.

At step S46, the event limiter 10 creates a new execution trace 6. FIG. After that, the process proceeds to step S47.

In step S47, the event restriction unit 10 includes the event acquired in step S42 in the execution trace 6 being created. After that, the process proceeds to step S48.

At step S48, the event restriction unit 10 determines whether or not the event obtained at step S42 matches the end event. If it is determined that they match, the process proceeds to step S49, and if it is determined that they do not match, the process proceeds to step S50.

In step S49, the event limiter 10 sets the output flag to invalid. After that, the process proceeds to step S50.

In step S50, the event restriction unit 10 determines whether or not the execution trace 6 collected by the execution trace collection unit 1 has an unprocessed event. If it is determined that the event exists, the process returns to step S42, and in step S42, the event limiter 10 acquires an unprocessed event from the execution trace 6 collected by the execution trace collector 1. FIG. If it is determined that it does not exist, the operation of FIG. 16 ends.

<Summary of Embodiment 3>
According to the impact analysis apparatus according to the third embodiment as described above, the execution trace 6 accumulated in the execution trace accumulation unit 2 is an execution trace having a pre-specified start event and a pre-specified end event. Limit to 6. According to such a configuration, processing of execution traces 6 and representative execution traces 7 whose event sequence differs from the desired event sequence can be suppressed. Therefore, it is possible to improve the processing efficiency of the influence analysis device and the work efficiency of the user.

<Embodiment 4>
In the third embodiment, the execution trace 6 and the representative execution trace 7 are classified only by the event sequence of the function transition, and the execution trace 6 and the representative execution trace 7 are not classified by the difference of variables such as states. In the third embodiment, when the execution trace 6 collected by the execution trace collection unit 1 contains variables, the types of events are subdivided with respect to the discrete values of the variables. As a result, even if the contents of two events are substantially the same, the events may be treated differently due to the variables in the events being different. As a result, the number of execution traces 6 and thus the number of representative execution traces 7 may increase unnecessarily. In view of this, as will become clear from the following description, in the influence analysis apparatus according to the fourth embodiment of the present invention, it is possible to suppress the processing of the execution trace 6 and the representative execution trace 7 with respect to variables. ing.

FIG. 17 is a block diagram showing the configuration of an influence analysis device according to the fourth embodiment. Hereinafter, among the constituent elements according to the fourth embodiment, constituent elements that are the same as or similar to the above-described constituent elements are denoted by the same or similar reference numerals, and different constituent elements will be mainly described.

The impact analysis device shown in FIG. 17 has the same configuration as the configuration of the impact analysis device according to Embodiment 3 (FIG. 13) with an event conversion unit 12 added as a conversion unit.

The input of the event converter 12 is connected to the output of the execution trace collector 1 . The input of the event limiter 10 is connected to the output of the event converter 12 . The input of execution trace storage unit 2 is connected to the output of event limiter 10 . The input of representative execution trace calculator 3 is connected to the output of execution trace storage 2 . The input of the representative execution trace storage section 4 is connected to the output of the representative execution trace calculation section 3 . The input of the execution trace outlier extraction unit 8 is connected to the output of the execution trace accumulation unit 2 and the output of the representative execution trace accumulation unit 4 . The input of the display unit 5 is connected to the output of the representative execution trace accumulation unit 4 and the output of the execution trace outlier extraction unit 8 .

In the fourth embodiment, the execution trace 6 contains variables. When the variables of the execution trace 6 collected by the execution trace collection unit 1 include pre-specified variables, the event conversion unit 12 uses a mapping that reduces the types of discrete values that the pre-specified variables can take. , the variables of the execution trace 6 are converted. On the other hand, when the variables of the execution trace 6 collected by the execution trace collection unit 1 do not include the variables specified in advance, the event conversion unit 12 outputs the execution trace 6 as it is.

FIG. 18 is a diagram showing an example of mapping rules used by the event conversion unit 12. As shown in FIG. In FIG. 18, conversion conditions of x<0, 0≤x<15, and 15≤x are defined as rules for mapping the variable x to one of 0, 1, and 2, respectively. As a rule for mapping the variable y to either 0 or 1, conversion conditions of y<5 and 5≦y are defined.

FIG. 19 is a diagram showing an output example of the event conversion unit 12. As shown in FIG. FIG. 19 shows, as an input event sequence, an event sequence in which x=7 after calling funcA function, y=10 after calling funcB function, y=-1 after calling funcC function, and x=30 after completing funcC function. It is shown. When the event conversion unit 12 converts the input event series shown in FIG. 19 using the rules shown in FIG. 18, the output event series shown in FIG. 19 is obtained. That is, an event sequence is obtained in which x=1 after the funcA function is called, y=1 after the funcB function is called, y=0 after the funcC function is called, and x=2 after the funcC function is completed.

<Action>
FIG. 20 is a flow chart showing the operation of the event conversion section 12. As shown in FIG. This operation will be described below with reference to FIG.

First, in step S<b>61 , the event conversion unit 12 acquires an event from the execution trace 6 collected by the execution trace collection unit 1 . After that, the process proceeds to step S62.

In step S62, the event conversion unit 12 determines whether the variables in the event acquired in step S61 match the variables specified by the mapping rule as shown in FIG. If it is determined that they match, the process proceeds to step S63, and if it is determined that they do not match, the process proceeds to step S64.

In step S63, the event conversion unit 12 converts the value of the variable in the event acquired in step S61 according to the mapping rule, rewrites the converted value to the converted value, and outputs the converted value. After that, the process proceeds to step S65.

In step S64, the event conversion unit 12 outputs the event obtained in step S61 as it is. After that, the process proceeds to step S65.

In step S65, the event conversion unit 12 determines whether or not the execution trace 6 collected by the execution trace collection unit 1 has an unprocessed event. If it is determined that the event exists, the process returns to step S61. If it is determined not to exist, the operation of FIG. 20 ends.

<Summary of Embodiment 4>
According to the influence analysis apparatus according to the fourth embodiment as described above, the variables of the execution trace 6 collected by the execution trace collection unit 1 are converted using a mapping that reduces the types of variables. According to such a configuration, it is possible to compare performance influences and visualize cause locations in consideration of not only function transitions but also variable conversion conditions. At this time, since the number of execution traces 6 and by extension the number of representative execution traces 7 can be suppressed by reducing the types of variables, it is possible to improve the processing efficiency of the influence analysis device and the work efficiency of the user.

<Others>
The execution trace collection unit 1, the representative execution trace calculation unit 3, the execution trace outlier extraction unit 8, the event restriction unit 10, and the event conversion unit 12 are, for example, a CPU (Central Processing Unit, not shown) of a computer corresponding to the impact analysis device. ) are implemented as functions of the CPU by executing a program stored in a storage device such as a semiconductor memory (not shown) of the influence analysis device.

In addition, within the scope of the invention, each embodiment can be freely combined, and each embodiment can be appropriately modified or omitted.

While the invention has been described in detail, the foregoing description is, in all its aspects, illustrative and not intended to limit the invention. It is understood that numerous variations not illustrated can be envisioned without departing from the scope of the invention.

1 execution trace collection unit 2 execution trace accumulation unit 3 representative execution trace calculation unit 4 representative execution trace accumulation unit 5 display unit 6 execution trace 7 representative execution trace 8 execution trace outlier extraction unit 10 event restriction part, 12 event conversion part;

Claims (10)

an execution trace collection unit that collects, under a plurality of different conditions, a plurality of execution traces including a plurality of events including entry and exit events of a function in software and the times of the plurality of events;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
representative execution trace calculation for calculating a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events based on the plurality of execution traces accumulated in the execution trace accumulation unit; Department and
a representative execution trace accumulation unit for accumulating the representative execution trace calculated by the representative execution trace calculation unit;
an output unit that outputs the representative execution trace accumulated in the representative execution trace accumulation unit ;
defining an allowable range based on the average contained in the representative execution trace accumulated in the representative execution trace accumulation unit, and determining, among the plurality of execution traces accumulated in the execution trace accumulation unit, an extraction unit that extracts the execution trace that is out of an acceptable range;
with
The impact analysis device, wherein the output unit displays the execution trace extracted by the extraction unit superimposed on the representative execution trace used for extraction. an execution trace collection unit that collects, under a plurality of different conditions, a plurality of execution traces including a plurality of events including entry and exit events of a function in software and the times of the plurality of events;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
representative execution trace calculation for calculating a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events based on the plurality of execution traces accumulated in the execution trace accumulation unit; Department and
a representative execution trace accumulation unit for accumulating the representative execution trace calculated by the representative execution trace calculation unit;
an output unit that outputs the representative execution trace accumulated in the representative execution trace accumulation unit ;
limiting the execution traces accumulated in the execution trace accumulation unit to execution traces having a pre-designated start event and a pre-designated end event among the execution traces collected by the execution trace collection unit and
an impact analysis device. an execution trace collection unit that collects, under a plurality of different conditions, a plurality of execution traces including a plurality of events including entry and exit events of a function in software, times of the plurality of events , and variables ;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
representative execution trace calculation for calculating a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events based on the plurality of execution traces accumulated in the execution trace accumulation unit; Department and
a representative execution trace accumulation unit for accumulating the representative execution trace calculated by the representative execution trace calculation unit;
an output unit that outputs the representative execution trace accumulated in the representative execution trace accumulation unit ;
a conversion unit that converts the variables of the execution trace collected by the execution trace collection unit using a mapping that reduces the types of variables;
an impact analysis device. The impact analysis device according to claim 1 ,
The representative execution trace accumulation unit
accumulating a plurality of representative execution traces having different combinations of the plurality of events;
The extractor is
Among the plurality of representative execution traces accumulated in the representative execution trace accumulation unit, the representative execution trace having the smallest difference between the plurality of execution traces accumulated in the execution trace accumulation unit and the combination of the plurality of events is selected. Influence analysis equipment used for extraction. an execution trace collection unit collecting a plurality of events including function entry and exit events in software and a plurality of execution traces including times of the plurality of events under a plurality of different conditions;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
A representative execution trace calculation unit, based on the plurality of execution traces accumulated in the execution trace accumulation unit, calculates a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events. to calculate
a representative execution trace accumulating unit accumulating the representative execution trace calculated by the representative execution trace calculating unit;
an output unit outputting the representative execution trace accumulated in the representative execution trace accumulation unit;
an extraction unit defining an allowable range based on the average included in the representative execution trace accumulated in the representative execution trace accumulation unit, and among the plurality of execution traces accumulated in the execution trace accumulation unit, extracting the execution trace whose time is outside the allowable range;
The impact analysis method , wherein the output unit displays the execution trace extracted by the extraction unit so as to be superimposed on the representative execution trace used for extraction. an execution trace collection unit collecting a plurality of events including function entry and exit events in software and a plurality of execution traces including times of the plurality of events under a plurality of different conditions;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
A representative execution trace calculation unit, based on the plurality of execution traces accumulated in the execution trace accumulation unit, calculates a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events. to calculate
a representative execution trace accumulating unit accumulating the representative execution trace calculated by the representative execution trace calculating unit;
an output unit outputting the representative execution trace accumulated in the representative execution trace accumulation unit;
the execution trace accumulated in the execution trace accumulation unit having a pre-designated start event and a pre-designated end event among the execution traces collected by the execution trace collection unit; An impact analysis method that limits execution traces . an execution trace collection unit collects, under a plurality of different conditions, a plurality of events including entry and exit events of functions in software, a plurality of execution traces including times of the plurality of events , and variables ;
an execution trace accumulation unit for accumulating the plurality of execution traces collected by the execution trace collection unit;
A representative execution trace calculation unit, based on the plurality of execution traces accumulated in the execution trace accumulation unit, calculates a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events. to calculate
a representative execution trace accumulating unit accumulating the representative execution trace calculated by the representative execution trace calculating unit;
an output unit outputting the representative execution trace accumulated in the representative execution trace accumulation unit;
The impact analysis method , wherein a transformation unit transforms the variables of the execution trace collected by the execution trace collection unit using a variable type reduction mapping. means for collecting a plurality of execution traces including a plurality of events including entry and exit events of a function in software and the times of the plurality of events under a plurality of different conditions;
means for accumulating the plurality of collected execution traces;
means for calculating, based on the accumulated execution traces, a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events;
means for accumulating the calculated representative execution trace;
means for outputting the accumulated representative execution trace;
means for prescribing an allowable range based on the average included in the accumulated representative execution traces, and extracting the execution trace whose time is outside the allowable range from among the plurality of accumulated execution traces; , on the computer , and
The impact analysis program , wherein the means for outputting the representative execution trace displays the extracted execution trace superimposed on the representative execution trace used for extraction. means for collecting a plurality of execution traces including a plurality of events including entry and exit events of a function in software and the times of the plurality of events under a plurality of different conditions;
means for accumulating the plurality of collected execution traces;
means for calculating, based on the accumulated execution traces, a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events;
means for accumulating the calculated representative execution trace;
means for outputting the accumulated representative execution trace;
means for limiting the accumulated execution traces to those execution traces having a pre-specified start event and a pre-specified end event among the collected execution traces. program. means for collecting a plurality of execution traces including a plurality of events including function entry and exit events in software, the times of the plurality of events , and variables under a plurality of different conditions;
means for accumulating the plurality of collected execution traces;
means for calculating, based on the accumulated execution traces, a representative execution trace including the plurality of events and the average and variation of the times of each of the plurality of events;
means for accumulating the calculated representative execution trace;
means for outputting the accumulated representative execution trace;
and means for transforming said variables of said collected execution traces using a variable type reducing mapping .

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