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公开(公告)号：US10474456B2
公开(公告)日：2019-11-12
申请号：US16415192
申请日：2019-05-17
Applicant: SAP SE
Inventor： Michele Bezzi , Antonino Sabetta , Henrik Plate , Serena Ponta , Francesco Di Cerbo
Abstract: Systems and methods are provided for accessing a source code repository comprising a plurality of versions of code, analyzing the plurality of versions of code of the component to compute metrics to identify each version of code, analyzing the metrics to determine a subset of the metrics to use to as a fingerprint definition to identify each version of the code, generating a fingerprint for each version of code using the fingerprint definition, generating a fingerprint matrix with the fingerprint for each version of code for the software component and storing the fingerprint definition and the fingerprint matrix
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公开(公告)号：US10338916B2
公开(公告)日：2019-07-02
申请号：US15371678
申请日：2016-12-07
Applicant: SAP SE
Inventor： Michele Bezzi , Antonino Sabetta , Henrik Plate , Serena Ponta , Francesco Di Cerbo
Abstract: Systems and methods are provided for accessing a source code repository comprising a plurality of versions of code, analyzing the plurality of versions of code of the component to compute metrics to identify each version of code, analyzing the metrics to determine a subset of the metrics to use to as a fingerprint definition to identify each version of the code, generating a fingerprint for each version of code using the fingerprint definition, generating a fingerprint matrix with the fingerprint for each version of code for the software component and storing the fingerprint definition and the fingerprint matrix.
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公开(公告)号：US20190026345A1
公开(公告)日：2019-01-24
申请号：US15655753
申请日：2017-07-20
Applicant: SAP SE
Inventor： Michele Bezzi
IPC: G06F17/30
Abstract: A front end receives a request for data specifying a data type. A query handler retrieves data of the data type comprising a plurality of data records from at least one database. The query handler assigns a classification attribute to each data record using a pre-defined classification policy stored in a policy store. A discrimination detection engine statistically evaluates the classification attributes for the data to identify a mutual information metric. The query handler generates a listing of one or more discriminatory attributes and corresponding mutual information metric contributing to discriminatory data patterns based on the mutual information metric.
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公开(公告)号：US20180157486A1
公开(公告)日：2018-06-07
申请号：US15371678
申请日：2016-12-07
Applicant: SAP SE
Inventor： Michele Bezzi , Antonino Sabetta , Henrik Plate , Serena Ponta , Francesco Di Cerbo
IPC: G06F9/44
Abstract: Systems and methods are provided for accessing a source code repository comprising a plurality of versions of code, analyzing the plurality of versions of code of the component to compute metrics to identify each version of code, analyzing the metrics to determine a subset of the metrics to use to as a fingerprint definition to identify each version of the code, generating a fingerprint for each version of code using the fingerprint definition, generating a fingerprint matrix with the fingerprint for each version of code for the software component and storing the fingerprint definition and the fingerprint matrix
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公开(公告)号：US11972258B2
公开(公告)日：2024-04-30
申请号：US17850380
申请日：2022-06-27
Applicant: SAP SE
Inventor： Rocio Cabrera Lozoya , Antonino Sabetta , Michele Bezzi
IPC: G06F8/77
CPC classification number: G06F8/77
Abstract: Systems and methods are provided for training a machine learning model to generate a score indicating a level of discrepancy between a commit message and a corresponding code change. The computing system receives a commit comprising a given commit message and a given corresponding code change and analyzes, using the trained machine learning model, the given commit message and given corresponding code change to generate a score indicating the level of discrepancy between the given commit message and the given corresponding code change of the received commit.
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Patent Agency Ranking
公开(公告)号：US20220129261A1
公开(公告)日：2022-04-28
申请号：US17080520
申请日：2020-10-26
Applicant: SAP SE
Inventor： Rocio Cabrera Lozoya , Antonino Sabetta , Michele Bezzi , Arnaud Baumann
Abstract: Distributed vector representations of source code commits, are generated to become part of a data corpus for machine learning (ML) for analyzing source code. The code commit is received, and time information is referenced to split the source code into pre-change source code and post-change source code. The pre-change source code is converted into a first code representation (e.g., based on a graph model), and the post-change source code into a second code representation. A first particle is generated from the first code representation, and a second particle is generated from the second code representation. The first particle and the second particle are compared to create a delta. The delta is transformed into a first commit vector by referencing an embedding matrix to numerically encode the first particle and the second particle. Following classification, the commit vector is stored in a data corpus for performing ML analysis upon source code.
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公开(公告)号：US10963474B2
公开(公告)日：2021-03-30
申请号：US15655753
申请日：2017-07-20
Applicant: SAP SE
Inventor： Michele Bezzi
IPC: G06F16/00 , G06F16/2458 , G06F16/28 , G06F16/951 , G06K9/62 , G06Q10/06
Abstract: A front end receives a request for data specifying a data type. A query handler retrieves data of the data type comprising a plurality of data records from at least one database. The query handler assigns a classification attribute to each data record using a pre-defined classification policy stored in a policy store. A discrimination detection engine statistically evaluates the classification attributes for the data to identify a mutual information metric. The query handler generates a listing of one or more discriminatory attributes and corresponding mutual information metric contributing to discriminatory data patterns based on the mutual information metric.
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公开(公告)号：US20190272170A1
公开(公告)日：2019-09-05
申请号：US16415192
申请日：2019-05-17
Applicant: SAP SE
Inventor： Michele Bezzi , Antonino Sabetta , Henrik Plate , Serena Ponta , Francesco Di Cerbo
Abstract: Systems and methods are provided for accessing a source code repository comprising a plurality of versions of code, analyzing the plurality of versions of code of the component to compute metrics to identify each version of code, analyzing the metrics to determine a subset of the metrics to use to as a fingerprint definition to identify each version of the code, generating a fingerprint for each version of code using the fingerprint definition, generating a fingerprint matrix with the fingerprint for each version of code for the software component and storing the fingerprint definition and the fingerprint matrix
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公开(公告)号：US20230418599A1
公开(公告)日：2023-12-28
申请号：US17850380
申请日：2022-06-27
Applicant: SAP SE
Inventor： Rocio Cabrera Lozoya , Antonino Sabetta , Michele Bezzi
IPC: G06F8/77
CPC classification number: G06F8/77
Abstract: Systems and methods are provided for training a machine learning model to generate a score indicating a level of discrepancy between a commit message and a corresponding code change. The computing system receives a commit comprising a given commit message and a given corresponding code change and analyzes, using the trained machine learning model, the given commit message and given corresponding code change to generate a score indicating the level of discrepancy between the given commit message and the given corresponding code change of the received commit.
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公开(公告)号：US10831899B2
公开(公告)日：2020-11-10
申请号：US15978691
申请日：2018-05-14
Applicant: SAP SE
Inventor： Michele Bezzi , Antonino Sabetta , Henrik Plate , Serena Ponta
Abstract: Systems and methods are provided for retrieving a set of code changes to source code from a source code repository, analyzing the set of code changes to generate a vector representation of each code change of the set of code changes, analyzing the vector representation of each code change of the set of code changes using a trained security-relevant code detection machine learning model, receiving a prediction from the security-relevant code detection machine learning model representing a probability that each code change of the set of code changes contains security-relevant changes, analyzing the prediction to determine whether the prediction is below or above a predetermined threshold, and generating results based on determining whether the prediction is below or above a predetermined threshold.
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