CN113535573A - GOMS model improvement-based software availability quantitative evaluation method - Google Patents

GOMS model improvement-based software availability quantitative evaluation method Download PDF

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CN113535573A
CN113535573A CN202110841584.5A CN202110841584A CN113535573A CN 113535573 A CN113535573 A CN 113535573A CN 202110841584 A CN202110841584 A CN 202110841584A CN 113535573 A CN113535573 A CN 113535573A
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王坤龙
李墈婧
刘兵
宋颖毅
田宗凯
苗旭
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Beijing Institute of Computer Technology and Applications
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Abstract

The invention relates to a GOMS model-based improved software availability quantitative evaluation method, and belongs to the field of software evaluation. The invention relates to a quantitative evaluation method of software availability based on GOMS model improvement, which scores the service frequency and the importance degree of different services of software by adopting an expert scoring method so as to determine the weight of each service; dividing the business target into several sub-targets, and continuously subdividing the sub-targets until the sub-targets are decomposed into basic operations which cannot be decomposed; calculating the complexity of different basic operations based on the basic operation time of the GOMS model; calculating the complexity of the service according to the complexity of the basic operation; and obtaining the complexity of the software system according to the complexity of each service of the software system. According to the invention, for different design schemes of the software system, the software interface design complexity of each scheme is calculated, and the higher the software interface design complexity is, the worse the software availability is, so that the quantitative evaluation of the software availability of each design scheme can be realized.

Description

GOMS model improvement-based software availability quantitative evaluation method
Technical Field
The invention belongs to the field of software evaluation, and particularly relates to a quantitative evaluation method for software availability based on GOMS model improvement.
Background
Software usability evaluation can be roughly divided into two types from the interface development process: firstly, evaluation in the initial stage of software interface design and in the testing process is called as staged evaluation; and the evaluation taken at the final stage of software interface design is called summarized evaluation. The stage evaluation mainly adopts an open means, finds problems in the design and optimizes and improves the problems through the forms of questionnaires, interviews and the like; the summary evaluation is to perform an overall evaluation on the interface design mainly through rigorous quantitative analysis, such as indexes of completion rate, completion time and the like. Common test methods designed for software interfaces mainly include an availability test method, an availability questionnaire survey method, an observation method, a user interview method and the like, mainly take qualitative evaluation as a main part, and also include a quantitative evaluation method based on GOMS.
Currently, the software usability evaluation is mainly subjective evaluation, is greatly influenced by personal experience, psychological state and the like, and has the problems of lack of objectivity, difficulty in quantitative analysis of an evaluation result and the like. If the usability test method can be combined with the cognitive characteristics, usability problems can be easily found, the objectivity is strong, but the test time is long and the cost is high; the usability questionnaire method has the characteristics of convenience for finding subjective preference of a user, simplicity, practicability and low cost, but is easy to misunderstand and greatly influenced by personal preference of the user; the observation method can reflect the real operation of the user, but is greatly influenced by an observer and an observed person; the user interview method can be long in time consumption for mining the actual needs of the users, and results are difficult to quantitatively analyze. In order to realize quantitative evaluation of software interface usability, partial scholars use the GOMS model to research the online shopping process of the user, so that the operation theoretical time required by the user when the user completes the same task by using different shopping platforms can be predicted, the operation theoretical time is compared with the actual time obtained by a performance experiment, and different operation processes are optimized. However, the current software interface availability evaluation method based on the GOMS model calculates the average operation time of each basic operation, and lacks consideration on the particularity of an operation object, such as the size of a button has a great influence on the positioning time and the time difficulty when the button is positioned by a mouse, so that more effective software availability evaluation needs to be researched, and support is provided for software design optimization.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the technical problem of how to provide a quantitative evaluation method for software availability based on GOMS model improvement so as to solve the problems that subjective evaluation is dominant, the influence of personal experience/psychological state is large, objectivity is lacked, or the evaluation result is difficult to quantitatively analyze and the like in the conventional software availability evaluation.
(II) technical scheme
In order to solve the technical problem, the invention provides a quantitative software availability evaluation method based on GOMS model improvement, which comprises the following steps:
s1, analyzing the service weight;
adopting an expert scoring method to score the service frequency and the importance degree of different services of the software so as to determine the weight of each service;
s2, analyzing each business process
Dividing the business target into several sub-targets, and continuously subdividing the sub-targets until the sub-targets are decomposed into basic operations which cannot be decomposed;
s3, calculating service complexity
Calculating the complexity of different basic operations based on the basic operation time of the GOMS model; calculating the complexity of the service according to the complexity of the basic operation;
s4 calculating the overall complexity of the system
And obtaining the complexity of the software system according to the complexity of each service of the software system.
Further, in the step S1, the service T is scored based on the expertjWeight W (T) ofj) The calculation formula is as follows:
Figure BDA0003179084770000031
wherein, F (T)j)、I(Tj) Respectively for the expert to the service TjThe frequency of use and the degree of importance of (c) are scored to obtain a mean value.
Further, for traffic TjThe rules for scoring the frequency of use and the degree of importance of (1) are: 1 indicates that the frequency of use is low, 2 indicates that the frequency of use is low, 3 indicates that the frequency is general, 4 indicates that the frequency of use is high, and 5 indicates that the frequency of use is high.
Further, for traffic TjThe rules for scoring the frequency of use and the degree of importance of (1) are: 1 indicates that the service is not important, 2 indicates that the service is not so important, 3 indicates that the degree of importance is general, 4 indicates that the service is more important, and 5 indicates that the service is important.
Further, the operation process of the user shopping process comprises the following steps:
(1) and (3) menu navigation: user mouse points to left side menu bar P1Area S1Second level menu bar appears pointing to the commodity key word P2Area S2And click K;
(2) and (3) browsing the commodities: the page jumps into a merchandise page S, the user browses merchandise details and rolls the mouse R x the average rolling times, the user points to the intention merchandise P3Area S3Click K;
(3) and (3) browsing the detail page: the page jumps to the commodity detail page S, the user browses the commodity details and rolls the mouse R multiplied by the average rolling times, and the user points to the evaluation page P4Area S4Clicking the evaluation page K, rolling the mouse R times the average rolling times, and pointing the mouse to a certain commodity configuration P5Area S5Click onK, mouse pointing to buy P immediately6Area S6Click K;
(4) the user views and submits the order: the page jumps into order page S, the user browses the order details, the user points to submit order P7Area S7Clicking K, skipping to enter the payment page S, pointing the payment button P with the mouse8Area S8Clicking K, inputting popup window S when payment password appears, resetting to keyboard H, inputting password T, pointing to definite button P by mouse9Area S9Click K.
Further, in the step S3, when calculating the complexity of different basic operations, based on three basic assumptions:
(1) the complexity of user operation is in direct proportion to the basic operation time of the GOMS model;
(2) the positioning complexity of the static interface elements is inversely proportional to the physical area of the elements;
(3) the complexity of mouse positioning the whole screen is equal to the complexity of mouse clicking operation.
Further, the complexity of the mouse clicking operation is 1, and the complexity of different operations is calculated as follows:
click mouse C complexity: cC＝1；
Complexity of key K: cK＝TK/TC＝1；
Reset H complexity: cH＝TH/TC＝2；
Mouse scroll R complexity: cR＝TR/TC＝1；
Page switching S complexity: cS＝TS/TC＝8；
Text entry T complexity: cT＝N×TK/TC＝N；
Assume that the user displays screen area S0If the resolution is X × Y, the physical area s of a certain static interface element occupies X × Y, the complexity of positioning the static interface element by the mouse is as follows:
Figure BDA0003179084770000041
further, the calculating the service complexity according to the complexity of the basic operation in step S3 specifically includes: the service is operated by a single basic operation AiTandem composition, service TjThe operation complexity calculation method is as follows:
Figure BDA0003179084770000042
wherein the content of the first and second substances,
Figure BDA0003179084770000043
refers to the complexity of the base operation Ai.
Further, the step S4 specifically includes:
calculating the complexity of each service of the software system based on the step S3 to obtain the complexity C of the software system:
Figure BDA0003179084770000044
wherein n is the number of services in the software.
Further, the complexity of each scheme of the software system is calculated, and the higher the complexity is, the poorer the software availability is.
(III) advantageous effects
The invention provides a GOMS model-based improved software availability quantitative evaluation method, which is used for scoring the service frequency and the importance degree of different services of software by adopting an expert scoring method so as to determine the weight of each service; dividing the business target into several sub-targets, and continuously subdividing the sub-targets until the sub-targets are decomposed into basic operations which cannot be decomposed; calculating the complexity of different basic operations based on the basic operation time of the GOMS model; calculating the complexity of the service according to the complexity of the basic operation; and obtaining the complexity of the software system according to the complexity of each service of the software system. The invention realizes the quantitative evaluation of the software interface usability, and for different design schemes of a software system, the higher the complexity of the software interface design is, the worse the software usability is, thereby realizing the quantitative evaluation of the software usability of each design scheme.
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FIG. 1 is an exploded view of a user shopping operation of the present invention.
Detailed Description
In order to make the objects, contents and advantages of the present invention clearer, the following detailed description of the embodiments of the present invention will be made in conjunction with the accompanying drawings and examples.
In order to further improve the scientificity and the rationality of software human-computer interface design evaluation and combine the actual characteristics and the limiting conditions of each evaluation method, the patent provides a quantitative evaluation method for software interface design, and aims to achieve the following purposes:
(1) defining a set of indexes capable of supporting quantitative evaluation of a software interface based on GOMS and a calculation method thereof;
(2) a quantitative evaluation strategy of a software interface is provided to realize quantitative evaluation of software availability.
The scheme of the invention specifically comprises the following steps:
step S1 analyzes traffic weight
Different user roles must be combined in the service weight analysis to clarify the following problems:
1) which tasks are used frequently? Which tasks are used less frequently?
2) Which tasks are important? Which tasks are unimportant?
3) How well each task should go?
The method carries out software availability evaluation, and scores the service frequency and the importance degree of different services of the software by adopting an expert scoring method, thereby determining the weight of each service.
TABLE 1 expert scoring presentation
Figure BDA0003179084770000061
The expert scoring table is shown in the table above, and the scoring rule is as follows: 1 indicates low frequency of use (traffic is not important), 2 indicates low frequency of use (traffic is not important), 3 indicates generally, 4 indicates high frequency of use (traffic is important), and 5 indicates high frequency of use (traffic is important), i.e. the score obtained is higher. Service T based on expert scoringjWeight W (T) ofj) The calculation formula is as follows:
Figure BDA0003179084770000062
wherein, F (T)j)、I(Tj) Respectively for the expert to the service TjThe frequency of use and the degree of importance of (c) are scored to obtain a mean value.
Step S2 of analyzing each business process
The business objective may be divided into several sub-objectives, which may continue to be subdivided until decomposed into elementary operations that cannot be decomposed.
Taking the shopping process of the user of the mainstream shopping website as an example, the operation flow is roughly as follows: the user opens the website to log in, the search user enters the commodity list page through search, the menu user enters the commodity list page through the menu, and the browse user enters the special subject page through browse. Different users may choose different methods on the item detail page: the user can choose to buy or join the shopping cart immediately, the user choosing to buy immediately needs to directly enter the order page and complete the order payment operation, and the user choosing to join the shopping cart can continue shopping. As shown in fig. 1.
The above process can be simply divided into six business processes, taking the business process of 'login-menu-commodity list-detail page-order page/payment' as an example, the operation process mainly comprises:
(1) and (3) menu navigation: user mouse points to left side menu bar P1(area S)1) Second level menu bar appears pointing to the commodity key word P2(area S)2) And click K;
(2) and (3) browsing the commodities: the page jumps to the merchandise page S, the user browses the merchandise details and scrolls the mouse R20 (average scrolling times), the user points to the intention merchandise P3(area S)3) Click K;
(3) and (3) browsing the detail page: the page jumps to the item detail page S, the user browses the item details and scrolls the mouse R x 10 (average scrolling times), the user points to the evaluation page P4(area S)4) Clicking the evaluation page K, rolling the mouse R8 (average number of rolling), pointing the mouse to a certain merchandise configuration P5(area S)5) Click K, mouse pointing to buy P immediately6(area S)6) Click K;
(4) the user views and submits the order: the page jumps into order page S, the user browses the order details, the user points to submit order P7(area S)7) Clicking K, skipping to enter the payment page S, pointing the payment button P with the mouse8(area S)8) Clicking K, inputting a payment password popup window S, resetting to a keyboard H, inputting a password T (6), and pointing to a determined button P by a mouse9(area S)9) Click K.
Based on the above procedure, the business objective can be decomposed into elementary operations that cannot be decomposed. To sum up, the necessary operations required to implement the business process of "login-menu-merchandise list-detail page-order page/payment" are:
P1P2KS(R×20)P3KS(R×10)P4K(R×8)P5K P6SP8KSH(T(6))P9。
step S3 business complexity calculation
3.1 Single operation complexity calculation
The decomposition of behavior and target by GOMS shows that the method can be applied to qualitative research and quantitative analysis of an interactive interface. The constructor of GOMS gives typical times of several basic operational behaviors defined through a summary refinement and experimental study of user behavior (see table 1). The time taken by the user to complete a certain goal is the total time of the sum of the basic operations of the user interacting with the interface. From the perspective of quantitative analysis, the method can predict the time required by a user to use a certain function interface, evaluate the performance of the interface, and perfect and optimize the existing interface. In order to better evaluate the usability of the interface, the patent provides an interface complexity concept based on the basic operation time of the GOMS model, increases the consideration on the positioning difficulty of the static elements of the interface, and provides a complexity quantitative calculation method for fusing interface operation and the static interface elements.
TABLE 2 GOMS model basic operation time (extension)
Figure BDA0003179084770000081
This patent proposes three basic assumptions:
(1) the complexity of user operation is in direct proportion to the basic operation time of the GOMS model;
(2) the positioning complexity of the static interface elements is inversely proportional to the physical area of the elements;
(3) the complexity of mouse positioning the whole screen (the mouse moves freely in the interface) is equal to the complexity of mouse clicking operation.
Based on the above assumptions, the complexity of mouse clicking operations is 1, and the complexity of different operations can be calculated:
click mouse C complexity: cC＝1；
Complexity of key K: cK＝TK/TC＝1；
Reset H complexity: cH＝TH/TC＝2；
Mouse scroll R complexity: cR＝TR/TC＝1；
Page switching S complexity: cS＝TS/TC＝8；
Text entry T complexity: cT＝N×TK/TC＝N；
Assume that the user displays screen area S0When the resolution is X multiplied by Y, the physical area s of certain static interface element occupies X multiplied by Y, the mouse is positioned to the static boundaryThe complexity of the bin elements is:
Figure BDA0003179084770000091
3.2 Business operation complexity calculation
From the above analysis, the service is composed of a series of basic operations Ai, and thus, the complexity of the operation Tj is calculated as follows:
Figure BDA0003179084770000092
wherein the content of the first and second substances,
Figure BDA0003179084770000093
refers to the complexity of the base operation Ai.
For the example in step S1, the necessary operations to implement the business process of "login-menu-merchandise list-details page-order page/payment" are: p1P2KJ(R×20)P3KJ(R×20)P4K(R×8)P5K P6J P8KJH(T(6))P9. Then the corresponding service complexity is:
Figure BDA0003179084770000094
wherein S isiFor position location operation PiCorresponding interface element area, S0To display screen area.
Step S4 calculating the overall complexity of the system
Based on the complexity of each service of the software system calculated in step S3, the complexity C of the software system can be obtained:
Figure BDA0003179084770000101
wherein n is the number of services in the software.
For different design schemes of the software system, the higher the complexity of the software interface design is, the worse the software availability is by calculating the software interface design complexity of each scheme, thereby realizing the quantitative evaluation of the software availability of each design scheme.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A quantitative software availability evaluation method based on GOMS model improvement is characterized by comprising the following steps:
s1, analyzing the service weight;
adopting an expert scoring method to score the service frequency and the importance degree of different services of the software so as to determine the weight of each service;
s2, analyzing each business process
Dividing the business target into several sub-targets, and continuously subdividing the sub-targets until the sub-targets are decomposed into basic operations which cannot be decomposed;
s3, calculating service complexity
Calculating the complexity of different basic operations based on the basic operation time of the GOMS model; calculating the complexity of the service according to the complexity of the basic operation;
s4 calculating the overall complexity of the system
And obtaining the complexity of the software system according to the complexity of each service of the software system.
2. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in claim 1, wherein in said step S1, based on expert scored business TjWeight W (T) ofj) The calculation formula is as follows:
Figure FDA0003179084760000011
wherein, F (T)j)、I(Tj) Respectively for the expert to the service TjThe frequency of use and the degree of importance of (c) are scored to obtain a mean value.
3. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in claim 2, characterized in that for service TjThe rules for scoring the frequency of use and the degree of importance of (1) are: 1 indicates that the frequency of use is low, 2 indicates that the frequency of use is low, 3 indicates that the frequency is general, 4 indicates that the frequency of use is high, and 5 indicates that the frequency of use is high.
4. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in claim 2, characterized in that for service TjThe rules for scoring the frequency of use and the degree of importance of (1) are: 1 indicates that the service is not important, 2 indicates that the service is not so important, 3 indicates that the degree of importance is general, 4 indicates that the service is more important, and 5 indicates that the service is important.
5. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in any one of claims 1-4, wherein the operation process of the user shopping process comprises:
(1) and (3) menu navigation: user mouse points to left side menu bar P1Area S1Second level menu bar appears pointing to the commodity key word P2Area S2And click K;
(2) and (3) browsing the commodities: the page jumps into a merchandise page S, the user browses merchandise details and rolls the mouse R x the average rolling times, the user points to the intention merchandise P3Area S3Click K;
(3) and (3) browsing the detail page: the page jumps to the commodity detail page S, the user browses the commodity details and rolls the mouse R multiplied by the average rolling times, and the user points to the evaluation page P4Area S4Clicking the evaluation page K, rolling the mouse R times the average rolling times, and pointing the mouse to a certain commodity configuration P5Area S5Click K, mouse pointing to buy P immediately6Area S6Click K;
(4) the user views and submits the order: the page jumps into order page S, the user browses the order details, the user points to submit order P7Area S7Clicking K, skipping to enter the payment page S, pointing the payment button P with the mouse8Area S8Clicking K, inputting popup window S when payment password appears, resetting to keyboard H, inputting password T, pointing to definite button P by mouse9Area S9Click K.
6. The quantitative evaluation method for software availability based on GOMS model improvement according to any one of claims 1 to 4, wherein the step S3 is based on three basic assumptions when calculating the complexity of different basic operations:
(1) the complexity of user operation is in direct proportion to the basic operation time of the GOMS model;
(2) the positioning complexity of the static interface elements is inversely proportional to the physical area of the elements;
(3) the complexity of mouse positioning the whole screen is equal to the complexity of mouse clicking operation.
7. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in claim 6, wherein the complexity of mouse click operation is 1, and the complexity of different operations is calculated as follows:
click mouse C complexity: cC＝1；
Complexity of key K: cK＝TK/TC＝1；
Reset H complexity: cH＝TH/TC＝2；
Mouse scroll R complexity: cR＝TR/TC＝1；
Page switching S complexity: cS＝TS/TC＝8；
Text entry T complexity: cT＝N×TK/TC＝N；
Assume that the user displays screen area S0If the resolution is X × Y, the physical area s of a certain static interface element occupies X × Y, the complexity of positioning the static interface element by the mouse is as follows:
Figure FDA0003179084760000031
8. the quantitative evaluation method for software availability based on GOMS model improvement according to claim 6, wherein the calculating the service complexity according to the complexity of the basic operation in step S3 specifically comprises: the service is operated by a single basic operation AiTandem composition, service TjThe operation complexity calculation method is as follows:
Figure FDA0003179084760000033
wherein the content of the first and second substances,
Figure FDA0003179084760000034
finger basic operation AiOf the system.
9. The method for quantitative evaluation of software availability based on GOMS model improvement as claimed in claim 8, wherein said step S4 specifically comprises:
calculating the complexity of each service of the software system based on the step S3 to obtain the complexity C of the software system:
Figure FDA0003179084760000032
wherein n is the number of services in the software.
10. The quantitative evaluation method for software availability based on GOMS model improvement as claimed in claim 9, characterized in that the complexity of each scheme of the software system is calculated, and the higher the complexity, the worse the software availability.
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