# US 2019/0155717 A1 · Method and apparatus for test modeling > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0155717 A1 - Document ID: US20190155717A1 - Status: Published application - Kind: A1 - Application number: 15/818,770 - Filed: 2017-11-21 - Published: 2019-05-23 - Earliest claimed: 2017-11-21 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Howard Hess; Eitan Farchi; Orna Raz; Rachel Tzoref-Brill; Aviad Zlotnick - Web page: https://patentgrep.com/patent/US20190155717A1 ## CPC - G06F 11/3684: {for test design, e.g. generating new test cases} - G06F 11/3668: Testing of software - G06F 18/22: Matching criteria, e.g. proximity measures - G06F 11/3672: {Test management} - G06Q 40/08: Insurance - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## 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. ## Claims ### Claim 1 A computer-implemented method, comprising: receiving a partial description of a combinatorial model, the combinatorial model defining a test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, wherein each restriction of the restrictions comprises at least one attribute, a respective value thereof and a logical operator, wherein the partial description comprising at least one attribute of the set of attributes and at least one value for the at least one attribute; computing a similarity measurement between the partial description and each model in a corpus of existing combinatorial models, wherein the similarity measurement is computed based on similarity of attributes and respective domains thereof and not based on the test space defined by models being compared, whereby similarity between models is indifferent to a size of the test space of the models; selecting one or more selected models from the corpus of existing combinatorial models in accordance with similarity measurements computed for the existing combinatorial models; determining one or more elements from the one or more selected models to be provided as a modification suggestion for modifying the partial description; and outputting the modification suggestion to modify the partial description based on the one or more elements, whereby the modification suggestion is useful in completing the partial description to create the combinatorial model. ### Claim 2 (depends on 1) The computer-implemented method of claim 1. wherein the at least one restriction comprises an illegal combination of attribute values. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein the similarity measurement is determined in accordance with common restrictions on combinations of attributes and values. ### Claim 4 (depends on 2) The computer-implemented method of claim 2, wherein the similarity measurement is determined in accordance with common attributes. ### Claim 5 (depends on 2) The computer-implemented method of claim 2, wherein the similarity measurement is determined in accordance with common attribute values. ### Claim 6 (depends on 2) The computer-implemented method of claim 2, wherein the similarity measurement is determined in accordance with common attributes and values thereof. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute and at least one value, setting the modification suggestion to comprise at least one second attribute or at least one second value comprised in at least one of the multiplicity of models. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute and the at least one value, setting the modification suggestion to comprise an element that is comprised in a number of models from the multiplicity of models that exceeds a threshold, wherein the element is selected from a group consisting an attribute and a value. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute or at least one value, setting the modification suggestion to comprise at least one second attribute or at least one second value comprised in a model from the one or more selected models. ### Claim 10 A system having a processor, the processor being adapted to perform the steps of: receiving a partial description of a combinatorial model, the combinatorial model defining a test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, wherein each restriction comprises at least one attribute, a respective value thereof and a logical operator, wherein the partial description comprising at least one attribute of the set of attributes and at least one value for the at least one attribute; computing a similarity measurement between the partial description and each model in a corpus of existing combinatorial models, wherein the similarity measurement is computed based on similarity of attributes and respective domains thereof and not based on the test space defined by models being compared, whereby similarity between models is indifferent to a size of the test space of the models; selecting one or more selected models from the corpus of existing combinatorial models in accordance with similarity measurements computed for the existing combinatorial models; determining one or more elements from selected models to be provided as a modification suggestion for modifying the partial description; and outputting the modification suggestion to modify the partial description based on the one or more elements, whereby the modification suggestion is useful in completing the partial description to create the combinatorial model. ### Claim 11 (depends on 10) The system of claim 10, wherein the at least one restriction comprises an illegal combination of attribute values. ### Claim 12 (depends on 11) The system of claim 11, wherein the similarity measurement is determined in accordance with common restrictions on combinations of attributes and values. ### Claim 13 (depends on 11) The system of claim 11, wherein the similarity measurement is determined in accordance with common attributes. ### Claim 14 (depends on 11) The system of claim 11 wherein the similarity measurement is determined in accordance with common attribute values. ### Claim 15 (depends on 11) The system of claim 11, wherein the similarity measurement is determined in accordance with common attributes and values thereof. ### Claim 16 (depends on 10) The system of claim 10, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute and at least one value, setting the modification suggestion to comprise at least one second attribute or at least one second value comprised in at least one of the multiplicity of models. ### Claim 17 (depends on 10) The system of claim 10, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute and the at least one value, setting the modification suggestion to comprise an element that is comprised in a number of models from the multiplicity of models that exceeds a threshold, wherein the element is selected from a group consisting an attribute and a value. ### Claim 18 (depends on 10) The system of claim 10, wherein subject to the existing corpus of models comprising a multiplicity of models each comprising the at least one attribute or at least one value, setting the modification suggestion to comprise at least one second attribute or at least one second value comprised in a model from the one or more selected models. ### Claim 19 A computer program product comprising a non-transitory computer readable medium retaining program instructions, which instructions when read by a processor, cause the processor to perform a method comprising: receiving a partial description of a combinatorial model, the combinatorial model defining a test space, the combinatorial model comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, wherein each restriction comprises at least one attribute, a respective value thereof and a logical operator, wherein the partial description comprising at least one attribute of the set of attributes and at least one value for the at least one attribute; computing a similarity measurement between the partial description and each model in a corpus of existing combinatorial models, wherein the similarity measurement is computed based on similarity of attributes and respective domains thereof and not based on the test space defined by models being compared, whereby similarity between models is indifferent to a size of the test space of the models; selecting one or more selected models from the corpus of existing combinatorial models in accordance with the similarity measurements computed for the existing combinatorial models; determining one or more elements from the one or more selected models to be provided as a modification suggestion for modifying the partial description; and outputting the modification suggestion to modify the partial description based on the one or more elements, whereby the modification suggestion is useful in completing the partial description to create the combinatorial model.