Patents by Inventor Eitan Daniel Farchi
Eitan Daniel Farchi has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20240176784Abstract: An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features using feature grouping. The processor can then detect an anomaly in response to detecting that an associated unbiased outlier score of the sample is higher than a predefined threshold.Type: ApplicationFiled: November 30, 2022Publication date: May 30, 2024Inventors: Yair ALLOUCHE, Aviad COHEN, Samuel Solomon ACKERMAN, Ofer Haim BILLER, Eitan Daniel FARCHI
-
Patent number: 11995068Abstract: A method including: receiving a set of data representing usage by entities of objects in a computing resource; extracting, from the initial set of data, one or more feature vectors representing the usage by one of the entities with respect to the objects; generating, from the feature vectors, a feature matrix; with respect to each entry in the feature matrix: (i) assigning a binary value to the entry, based on a predefined usage threshold, (ii) identifying, among the one or more entities, k nearest neighbor entities with respect to the one of the entities, based on a predefined distance threshold, and (iii) modifying the usage value of the entry, based on usage values associated with each of the k nearest neighbor entities with respect to the one of the objects; and updating the feature matrix with the modified usage values, to obtain a manipulated feature matrix.Type: GrantFiled: May 3, 2023Date of Patent: May 28, 2024Assignee: International Business Machines CorporationInventors: Yair Allouche, Aviad Cohen, Eitan Daniel Farchi
-
Patent number: 11979421Abstract: In some examples, a system for decorating network traffic flows with outlier scores includes a processor and a memory device to store traffic flows received from a network. The processor is configured to receive a set of traffic flows from the memory device and generate a tree model to split the traffic flows into clusters of traffic flows. Each cluster corresponds with a leaf of the tree model. The processor is further configured to generate machine learning models for each of the clusters of traffic flows separately. For a new traffic flow, the processor is configured to identify a specific one of the machine learning models that corresponds with the new traffic flow, compute an outlier score for the new traffic flow using the identified specific one of the machine learning models, and decorate the new traffic flow with the outlier score.Type: GrantFiled: December 31, 2021Date of Patent: May 7, 2024Assignee: International Business Machines CorporationInventors: Yair Allouche, Aviad Cohen, Ravid Sagy, Ofer Haim Biller, Eitan Daniel Farchi
-
Patent number: 11914593Abstract: Embodiments are for generating a digital signature of a query execution plan using similarity hashing. A technique includes generating a node digital signature for nodes in a query and generating an edge digital signature for edges in the query, the edges connecting the nodes. The technique includes selecting at least one previously executed query based on the node digital signature and the edge digital signature for the query and causing the query to be processed according to an assignment associated with the at least one previously executed query.Type: GrantFiled: April 22, 2022Date of Patent: February 27, 2024Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Sweta Singh, Vaibhav Murlidhar Kulkarni, Mario Dominic Savio Briggs, Deepak Anil Mahajan, Eitan Daniel Farchi
-
Publication number: 20230342356Abstract: Embodiments are for generating a digital signature of a query execution plan using similarity hashing. A technique includes generating a node digital signature for nodes in a query and generating an edge digital signature for edges in the query, the edges connecting the nodes. The technique includes selecting at least one previously executed query based on the node digital signature and the edge digital signature for the query and causing the query to be processed according to an assignment associated with the at least one previously executed query.Type: ApplicationFiled: April 22, 2022Publication date: October 26, 2023Inventors: Sweta Singh, Vaibhav Murlidhar Kulkarni, MARIO Dominic Savio BRIGGS, Deepak Anil Mahajan, Eitan Daniel Farchi
-
Patent number: 11768758Abstract: Methods, systems, and computer program products for path-coverage directed black box application programming interface (API) testing are provided herein. A computer-implemented method includes determining constraints based on inputs and corresponding outputs of an API in a production environment; generating initial test inputs based at least in part on the constraints; creating a program dependency graph based on trace sequences and request-response data obtained in response to providing the initial test inputs to an endpoint of the API; enhancing the program dependency graph by generating additional test inputs directed to one or more paths of the dependency graph; identifying, based on the enhanced program dependency graph, at least a portion of the API that is not covered by an existing test suite; and using the enhanced program dependency graph to generate new test cases for the test suite based on the identifying.Type: GrantFiled: October 6, 2021Date of Patent: September 26, 2023Assignee: International Business Machines CorporationInventors: Diptikalyan Saha, Devika Sondhi, Eitan Daniel Farchi
-
Publication number: 20230237343Abstract: An example system includes a processor to receive a test set, data slices, and a measure of interest. The processor can rank the data slices based on the test set, the data slices, and the set of measures of interest. The test set includes data points from the same feature space used to train a machine learning model. Each data slice is ranked according to generated slice grades representing unique information contribution of each data slice to the measure of interest with respect to the other data slices. The processor can then present the ranked data slices.Type: ApplicationFiled: January 26, 2022Publication date: July 27, 2023Inventors: Orna RAZ, Samuel Solomon ACKERMAN, Marcel ZALMANOVICI, Eitan Daniel FARCHI, Ramasuri NARAYANAM
-
Publication number: 20230237222Abstract: In some examples, a system for generating optimization constraints includes a memory device to store human-generated constraint and/or objective definitions that have been programmed in a general-purpose programming language by a human user, and a processor configured to generate labeled data for a plurality of solutions to an optimization problem using the stored constraint and/or objective definitions. The processor is also configured to generate a formal constraint and/or objective model from the labeled constraint and/or objective data, wherein the formal constraint and/or objective model comprises automatically generated constraint and/or objective definitions that are syntactically different from the human-generated constraint and/or objective definitions and syntactically correct for a specific optimization engine.Type: ApplicationFiled: January 24, 2022Publication date: July 27, 2023Inventors: Eliezer Segev WASSERKRUG, Yishai Abraham FELDMAN, Eitan Daniel FARCHI
-
Publication number: 20230216870Abstract: In some examples, a system for decorating network traffic flows with outlier scores includes a processor and a memory device to store traffic flows received from a network. The processor is configured to receive a set of traffic flows from the memory device and generate a tree model to split the traffic flows into clusters of traffic flows. Each cluster corresponds with a leaf of the tree model. The processor is further configured to generate machine learning models for each of the clusters of traffic flows separately. For a new traffic flow, the processor is configured to identify a specific one of the machine learning models that corresponds with the new traffic flow, compute an outlier score for the new traffic flow using the identified specific one of the machine learning models, and decorate the new traffic flow with the outlier score.Type: ApplicationFiled: December 31, 2021Publication date: July 6, 2023Inventors: Yair ALLOUCHE, Aviad COHEN, Ravid SAGY, Ofer Haim BILLER, Eitan Daniel FARCHI
-
Publication number: 20230205847Abstract: Systems and methods for automatically identifying in a dataset insufficient data for learning, or records with anomalous combinations of feature values, by partition of numeric and/or categorical data space into human-interpretable regions are disclosed. The method comprises: receiving a dataset of numeric and/or categorical features with a plurality of observations. Calculating observation density for each observation according to a distance or anomaly based metric, and receiving a density measurement. Partitioning the dataset along the numeric and/or categorical features according to the density measurement of each observation by a perpendicular cut along the feature spaces, receiving a map of a plurality of hyper-rectangular shapes representing various levels of density including empty spaces.Type: ApplicationFiled: December 26, 2021Publication date: June 29, 2023Inventors: Samuel Solomon Ackerman, Orna Raz, Marcel Zalmanovici, Eitan Daniel Farchi, Avi Ziv
-
Publication number: 20230106929Abstract: Methods, systems, and computer program products for path-coverage directed black box application programming interface (API) testing are provided herein. A computer-implemented method includes determining constraints based on inputs and corresponding outputs of an API in a production environment; generating initial test inputs based at least in part on the constraints; creating a program dependency graph based on trace sequences and request-response data obtained in response to providing the initial test inputs to an endpoint of the API; enhancing the program dependency graph by generating additional test inputs directed to one or more paths of the dependency graph; identifying, based on the enhanced program dependency graph, at least a portion of the API that is not covered by an existing test suite; and using the enhanced program dependency graph to generate new test cases for the test suite based on the identifying.Type: ApplicationFiled: October 6, 2021Publication date: April 6, 2023Inventors: Diptikalyan Saha, Devika Sondhi, Eitan Daniel Farchi
-
Publication number: 20230102152Abstract: A system, program product, and method for automatic detection of data drift in a data set are presented. The method includes determining changes to relations in the data set through generating baseline and production data sets. The method further includes generating a production data set with some inserted data distortion, and defining, for a plurality of features in the baseline data set, potential relations for participant features. The method also includes determining a first likelihood and a second likelihood of each potential relation in the baseline and production data sets, respectively, for the participant features. The method further includes comparing each first likelihood with each second likelihood, generating a comparison value that is compared with a threshold value, and determining, subject to the comparison value exceeding the threshold value, the potential relation in the baseline data set does not describe a relation in the production data set.Type: ApplicationFiled: September 24, 2021Publication date: March 30, 2023Inventors: Eliran Roffe, Samuel Solomon Ackerman, Eitan Daniel Farchi, Orna Raz
-
Patent number: 11556847Abstract: A method, system and computer program product, the method comprising: obtaining computer code of an employed system comprising a plurality of components; obtaining data related to operating the plurality of components; based on the computer code and the data, identifying: a first component from the plurality of components, to be maintained; and a second component from the plurality of components, to be at least partly replaced by a machine learning component; and providing to a user an identification of the first component and the second component.Type: GrantFiled: October 17, 2019Date of Patent: January 17, 2023Assignee: International Business Machines CorporationInventors: Eitan Daniel Farchi, Howard Michael Hess, Orna Raz
-
Patent number: 11556810Abstract: A method, computer system, and a computer program product for assessing a likelihood of success associated with developing at least one machine learning (ML) solution is provided. The present invention may include generating a set of questions based on a set of raw training data. The present invention may also include computing a feasibility score based on an answer corresponding with each question from the generated set of questions. The present invention may then include, in response to determining that the computed feasibility score satisfies a threshold, computing a level of effort associated with developing the at least one ML solution to address a problem. The present invention may further include presenting, to a user, a plurality of results associated with assessing the likelihood of success of the at least one ML solution.Type: GrantFiled: July 11, 2019Date of Patent: January 17, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Pathirage Dinindu Sujan Udayanga Perera, Orna Raz, Ramani Routray, Eitan Daniel Farchi
-
Publication number: 20220414523Abstract: A method processes information. Training pairs are generated by a computer system using matching fields in matching pairs of records for a data type, wherein matches are present between the matching fields in the matching pairs of records. Similarities between the training pairs are determined by the computer system using an importance map with importance values for the matching fields. Shapley values are determined by the computer system using the training pairs and the similarities between the training pairs. The importance map is adjusted by the computer system using the Shapley values.Type: ApplicationFiled: June 29, 2021Publication date: December 29, 2022Inventors: Mohammad Khatibi, Eitan Daniel Farchi, Martin Oberhofer
-
Publication number: 20220222543Abstract: A method matches information. A first center node in a first subgraph and a second center node in a second subgraph are identified. Groups of neighboring nodes having the neighboring nodes from both of subgraphs are identified. A group of the neighboring nodes in the groups has the neighboring nodes with a same node type. A best matching node pair of the neighboring nodes in each cluster is identified. The neighboring nodes in each best matching node pair comprise a first node from the first subgraph and a second node from the second subgraph. Whether the center nodes match is determined based on an overall distance between the center nodes using the first and second center node and the best matching node pair pairs.Type: ApplicationFiled: January 13, 2021Publication date: July 14, 2022Inventors: Mohammad Khatibi, Eitan Daniel Farchi, Martin Oberhofer
-
Publication number: 20220172124Abstract: A system and method for generating data slices for validating a classifier and validating the classifier. The classifier is trained using a training data set to train the underlying machine learning algorithm. Data is passed through the trained classifier to obtain results. The results are scored to determine the likelihood that the classifier correctly classified the data. Features are identified in the data set that can be used to validate the classifier. Based on the identified features at least one data slice in the data set is identified. The classifier is validated using the at least one data slice.Type: ApplicationFiled: December 2, 2020Publication date: June 2, 2022Inventors: Orna Raz, Marcel Zalmanovici, Eitan Daniel Farchi, Raviv Gal, Avi Ziv
-
Publication number: 20210117848Abstract: A method, system and computer program product, the method comprising: obtaining computer code of an employed system comprising a plurality of components; obtaining data related to operating the plurality of components; based on the computer code and the data, identifying: a first component from the plurality of components, to be maintained; and a second component from the plurality of components, to be at least partly replaced by a machine learning component; and providing to a user an identification of the first component and the second component.Type: ApplicationFiled: October 17, 2019Publication date: April 22, 2021Inventors: Eitan Daniel Farchi, Howard Michael Hess, Orna Raz
-
Publication number: 20210012221Abstract: A method, computer system, and a computer program product for assessing a likelihood of success associated with developing at least one machine learning (ML) solution is provided. The present invention may include generating a set of questions based on a set of raw training data. The present invention may also include computing a feasibility score based on an answer corresponding with each question from the generated set of questions. The present invention may then include, in response to determining that the computed feasibility score satisfies a threshold, computing a level of effort associated with developing the at least one ML solution to address a problem. The present invention may further include presenting, to a user, a plurality of results associated with assessing the likelihood of success of the at least one ML solution.Type: ApplicationFiled: July 11, 2019Publication date: January 14, 2021Inventors: Pathirage Dinindu Sujan Udayanga Perera, Orna Raz, Ramani Routray, Eitan Daniel Farchi
-
Patent number: 10452525Abstract: A method, apparatus and product for utilizing semantic clusters to predict software defects. The method comprising: obtaining a plurality of software elements that are associated with a version of a System Under Test (SUT), wherein the plurality of software elements comprise defective software elements which are associated with a defect in the version of the SUT; defining, by a processor, a plurality of clusters, wherein each cluster of the plurality of clusters comprises software elements having an attribute, wherein the attribute is associated with a functionality of the SUT; and determining a score of each cluster of the plurality of clusters, wherein the score of a cluster is based on a relation between a number of defect software elements in the cluster and a number of software elements in the cluster.Type: GrantFiled: June 20, 2016Date of Patent: October 22, 2019Assignee: International Business Machines CorporationInventors: Eitan Daniel Farchi, Andre Heilper, Aviad Zlotnick