Linking graphical user interface testing tools and human performance modeling to enable usability assessment
Methods of providing usability predictions are set forth herein. A method includes obtaining test cases for analyzing usability of a graphical user interface of a given software application. The method further includes automatically generating, using a processor, a human performance model based on the test cases. The method also includes generating the usability predictions based on the human performance model. At least some of the test cases are generated automatically from an analysis of the given software application.
1. A method of providing usability predictions, comprising:
obtaining test cases for analyzing usability of a graphical user interface of a given software application;
automatically generating, using a processor, a human performance model based on the test cases;
generating the usability predictions based on the human performance model; and
generating a set of rules that semantically refines one or more tasks applicable to the graphical user interface,
wherein at least some of the test cases are generated automatically from an analysis of the given software application.
2. The method of claim 1 , wherein at least some of the test cases are executed to generate test case execution data, and the human performance model is automatically generated based on the test case execution data.
3. The method of claim 1 , wherein at least some of the test cases are generated from a demonstration by a human.
4. The method of claim 1 , where the human performance model includes a graphical user interface model and task models.
5. The method of claim 1 , including inferring additional possible methods for tasks not defined in the test cases.
6. The method of claim 1 , wherein the usability prediction comprises a skilled execution time.
7. The method of claim 1 , wherein the usability prediction comprises a navigation path for a given task.
8. The method of claim 1 , wherein the usability prediction comprises user errors.
9. The method of claim 1 , further comprising semantically evaluating the test cases for exclusion from said executing step based on one or more predefined criterion relating to semantics.
10. The method of claim 1 , wherein the set of rules comprise global rules and task specific rules, the global rules usable for all tasks, and the task specific rules being to a particular task.
11. The method of claim 10 , wherein the global rules comprise a particular rule mandating that each of the test cases end with a system interaction event in a main window of the graphical user interface or each of the test cases end with a terminal event resulting in only the main window being opened.
12. The method of claim 10 , wherein the global rules comprise a particular rule mandating that an event that expands a menu or a list must be immediately followed by an event that is executed on a child of the menu or the list.
13. The method of claim 10 , wherein the global rules comprise a particular rule mandating that a window in the graphical user interface cannot be opened and immediately closed without an intervening event occurring.
14. The method of claim 10 , wherein at least one of the global rules is used together with a particular one of the task specific rules such that an event is restricted from appearing more than once in any of the test cases according to the at least one of the global rules, unless the event is allowed to appear more than once according to the particular one of the task specific rules.
15. The method of claim 14 , wherein the particular one of the task specific rules mandates that events in a repeat list of events are permitted to be used more than once in a particular one or more of the test cases.
16. The method of claim 10 , wherein the task specific rules comprise a particular rule mandating that exactly one of the events in an exclusion set of events must be included in each of the test cases.
17. The method of claim 10 , wherein the task specific rules comprise a particular rule mandating a partial order on system interaction events.
18. The method of claim 10 , wherein the partial order is determined by grouping the system interaction events into a plurality of order groups, and then placing the plurality of order groups into a corresponding order, where each of the system interaction events in a respective one of the plurality of order groups are in a same respective ordering equivalence class.
19. The method of claim 10 , wherein the task specific rules comprise a particular rule mandating that events in a required list of events must appear in each of the test cases.
20. A method of providing usability predictions, comprising:
obtaining test cases for analyzing usability of a graphical user interface of a given software application;
semantically evaluating the test cases to generate test case semantic data;
generating a set of rules that semantically refines one or more tasks applicable to the graphical user interface responsive to the test case semantic data;
executing the test cases, using a processor, to generate test case execution data;
automatically generating a human performance model based on the test case execution data; and
generating the usability predictions based on the human performance model,
wherein the test cases are semantically evaluated for exclusion from said executing step based on one or more predefined criterion relating to semantics.
21. The method of claim 20 , wherein at least some of the test cases are generated automatically from an analysis of the given software application.
22. The method of claim 20 , where the human performance model includes a graphical user interface model and task models.
23. The method of claim 20 , wherein the usability prediction comprises a skilled execution time.
24. The method of claim 20 , wherein the set of rules comprise global rules and task specific rules, the global rules usable for all tasks, and the task specific rules being to a particular task.