Abstract: Generating a test case summary of an end-to-end test of a computer application includes identifying an edge for each test execution. Each execution corresponds to a transition of the user interface of the application from a source state to a target state. One or more attributes of each edge are determined. Natural language processing is performed on each edge. Based on the natural language processing, a label for each edge is derived from the one or more attributes of each edge. A test case summary of the end-to-end test is output. The test case summary combines the labels corresponding to each edge.

Abstract: An approach for determining similar text documents. The approach can calculate a first set of vectors for a first cluster of text documents and a first comparison vector for a text document of interest. The approach can select a subset of text documents from the cluster of text documents based on comparing the vectors from the first set of vectors to the first comparison vector and picking a predetermined number of closest comparison text documents. The approach can calculate a second set of vectors for the subset of documents and second comparison vector for the document of interest. The approach can generate similarity ratings for the subset of documents based on pairwise comparisons of the second comparison vector and the second set of vectors. The approach can generate a ranked list of the second cluster of text documents based on the similarity ratings.

Abstract: An approach for determining similar text documents. The approach can calculate a first set of vectors for a first cluster of text documents and a first comparison vector for a text document of interest. The approach can select a subset of text documents from the cluster of text documents based on comparing the vectors from the first set of vectors to the first comparison vector and picking a predetermined number of closest comparison text documents. The approach can calculate a second set of vectors for the subset of documents and second comparison vector for the document of interest. The approach can generate similarity ratings for the subset of documents based on pairwise comparisons of the second comparison vector and the second set of vectors. The approach can generate a ranked list of the second cluster of text documents based on the similarity ratings.

Abstract: A system, computer program product, and method are presented for executing a validation test on at least a portion of a refactored application. The refactored application is resident within a partitioned computing architecture including a plurality of partitions and communication between the partitions uses one or more boundary methods. The refactored application is at least partially similar to a transformed monolithic application. The method includes automatically generating one or more test sequences for exercising one or more functional behaviors for each boundary method of the one or more boundary methods.

Abstract: A method, system and computer program product, the method comprising: receiving a user document describing at least a part of a system to be tested; computing a similarity measurement between the user document and documents in a document corpus, each describing at least part of a system and associated with a combinatorial model representing the at least part of the system, wherein the combinatorial model comprises a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, wherein each restriction comprises at least one attribute, a respective value and a logical operator, based upon the similarity measurement, selecting selected documents from the document corpus; obtaining one or more combinatorial models corresponding to the selected documents; selecting elements from the combinatorial models; generating an initial combinatorial model for the user document, wherein said generating comprises adding the elements to the initial combinatorial model.

Abstract: A method, system and computer program product, the method comprising: receiving a partial description of a combinatorial model defining a test space and comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, each comprising an attribute, a respective value and a logical operator, the partial description comprising an attribute and a value thereof; computing a similarity measurement between the partial description and each model in a corpus, based on similarity of attributes and domains, and not on a test space defined by compared models, whereby similarity between models is indifferent to a size of the test space of the models; selecting models from the corpus according to the computed similarity measurements; determining elements from the selected models to be suggested for modifying the partial description; and outputting the suggestions to modify the partial description useful for completing the combinatorial model.

Abstract: A method, system and computer program product, the method comprising: receiving a user document describing at least a part of a system to be tested; computing a similarity measurement between the user document and documents in a document corpus, each describing at least part of a system and associated with a combinatorial model representing the at least part of the system, wherein the combinatorial model comprises a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, wherein each restriction comprises at least one attribute, a respective value and a logical operator, based upon the similarity measurement, selecting selected documents from the document corpus; obtaining one or more combinatorial models corresponding to the selected documents; selecting elements from the combinatorial models; generating an initial combinatorial model for the user document, wherein said generating comprises adding the elements to the initial combinatorial model.

Abstract: A method, system and computer program product, the method comprising: receiving a partial description of a combinatorial model defining a test space and comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, each comprising an attribute, a respective value and a logical operator, the partial description comprising an attribute and a value thereof; computing a similarity measurement between the partial description and each model in a corpus, based on similarity of attributes and domains, and not on a test space defined by compared models, whereby similarity between models is indifferent to a size of the test space of the models; selecting models from the corpus according to the computed similarity measurements; determining elements from the selected models to be suggested for modifying the partial description; and outputting the suggestions to modify the partial description useful for completing the combinatorial model.

Abstract: Techniques for monitoring computer program test design are described herein. The techniques include a method that specifies a subset of tuples in a combinatorial test model as supervised. At least some of the supervised tuples are confirmed using expert data. The method may include determining a metric indicating progress of the combinatorial test modeling process based on the supervised tuples and the confirmed tuples.

Abstract: A methods, apparatus and product for explaining partially illegal combinations in combinatorial models. The method comprising: obtaining a combinatorial model defining a legal test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and a set of restrictions, wherein the restrictions define a combination of values of the attributes that are illegal and are excluded from the legal test case; obtaining a partially illegal combination defining value assignments to a portion of the attributes; automatically identifying an extension of the partially illegal combination, wherein the extension is excluded from the legal test space, wherein the extension can be modified to become legal by changing a portion of the value assignments defined by the partially illegal combination; and outputting the extension.

Abstract: A computer-implemented method comprising: obtaining a description of a test suite which comprises a plurality of tests, wherein each test of the test suite is described by values of functional attributes, wherein at least a portion of the functional attributes are setup-related attributes, wherein a combination of values of the setup-relates attributes potentially indicate a setup activity to be performed prior to executing the test to set up a test environment for the test. Identifying, based on the description of the test suite, a setup activity that is associated with two or more tests, wherein the setup activity is configured to set up a component of the test environment, wherein the identifying is performed by a processor. Providing a first instruction to perform the setup activity prior to executing a first test of the two or more tests.

Abstract: A method executable on one or more processors for modeling a test space is provided. The method may include defining a coverage model including a set of variables. The method may also include selecting one or more variables within at least one subset of a plurality of subsets of the set of variables. The selection may be according to an interaction level requirement defined for at least one or more of the subsets, whereby the interaction level corresponds to a coverage of the test space that covers a plurality of possible combinations of the one or more variables at multiple levels. Furthermore, respective values for the one or more selected variables within the subset of the set of variables may be assigned. The method may also include one or more definitions for value combinations for said variables with assigned values.

Abstract: A method for modeling a test space is provided. The method comprises defining a coverage model including one or more attributes, wherein respective values for the attributes are assigned, one or more definitions of value properties for said attributes with assigned values, and one or more requirements that limit combination of attribute values that are legal for the model, wherein at least one of said requirements is defined using at least one value property.

Abstract: A method for refining a test plan is provided. The method comprises defining a coverage model including: one or more variables, wherein respective values for the variables are assigned, and one or more definitions for value combinations for said variables with assigned values, wherein zero or more of said value combinations are defined according to one or more restrictions for the purpose of generating a test plan to test a system for which the coverage model is constructed; determining zero or more uncovered value combinations in the test plan; and providing means to update the test plan.

Abstract: Techniques for monitoring computer program test design are described herein. The techniques include a method that specifies a subset of tuples in a combinatorial test model as supervised. At least some of the supervised tuples are confirmed using expert data. The method may include determining a metric indicating progress of the combinatorial test modeling process based on the supervised tuples and the confirmed tuples.

Abstract: A method, apparatus and product for completion of partial coverage tasks. The method comprising obtaining a partial coverage task defining a test with respect to a functional coverage model of a System Under Test (SUT), wherein the functional coverage model defining functional attributes and respective domains thereof, wherein the functional coverage model further defining one or more restrictions on value combinations of the functional attributes; and enhancing the partial coverage task to include an assignment of a value to a functional attribute, wherein the functional attribute is unassigned in the partial coverage task, wherein the value is an only valid assignment to the functional attribute in view of assignments of other functional attributes and in view of the restrictions.

Abstract: A methods, apparatus and product for explaining partially illegal combinations in combinatorial models. The method comprising: obtaining a combinatorial model defining a legal test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and a set of restrictions, wherein the restrictions define a combination of values of the attributes that are illegal and are excluded from the legal test case; obtaining a partially illegal combination defining value assignments to a portion of the attributes; automatically identifying an extension of the partially illegal combination, wherein the extension is excluded from the legal test space, wherein the extension can be modified to become legal by changing a portion of the value assignments defined by the partially illegal combination; and outputting the extension.

Abstract: A method for modeling a test space comprising defining a coverage model including: one or more variables, wherein respective values for the variables are assigned, and restrictions based on which valid variable value combinations are determined for the purpose of testing the model, wherein at least two values that are assignable to the one or more variables are merged to reduce number of variable values in the coverage model.

Abstract: A method, apparatus and product for determining a derived restriction in a combinatorial model. The method comprising: obtaining a combinatorial model defining a test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute, and a set of restrictions, wherein the restrictions define a combination of values of the attributes that are restricted from the test space; and automatically determining a derived restriction that is derived from at least a first restriction and a second restriction, the first and second restrictions are comprised by the set of restrictions, wherein the derived restriction restricts at least one combination of values that is not restricted by the first restriction and at least one combination of values that is not restricted by the second restriction.

Abstract: A method, system and product for explaining illegal combinations in combinatorial models. The method comprising obtaining a combinatorial model and an illegal combination that is excluded from the model by one or more restrictions, utilizing a Satisfiability solver on a satisfiability formula that encodes the legal test space and that assigns values to attributes as defined by the illegal combination, whereby the satisfiability solver provides an indication of unsatisfiability of the satisfiability formula and an UNSAT core comprising a subset of clauses defined by the satisfiability formula which are unsatisfiable; and identifying the one or more restrictions by mapping the clauses of the UNSAT core with clauses encoding the set of restrictions.