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1. CN112005259 - SMART SELECTION OF TEST SCRIPTS FOR COMMODITY TESTING ON MANUFACTURING FLOOR

Office
Chine
Numéro de la demande 201980002996.0
Date de la demande 01.02.2019
Numéro de publication 112005259
Date de publication 27.11.2020
Type de publication A
CIB
G06Q 10/06
GPHYSIQUE
06CALCUL; COMPTAGE
QSYSTÈMES OU MÉTHODES DE TRAITEMENT DE DONNÉES, SPÉCIALEMENT ADAPTÉS À DES FINS ADMINISTRATIVES, COMMERCIALES, FINANCIÈRES, DE GESTION, DE SURVEILLANCE OU DE PRÉVISION; SYSTÈMES OU MÉTHODES SPÉCIALEMENT ADAPTÉS À DES FINS ADMINISTRATIVES, COMMERCIALES, FINANCIÈRES, DE GESTION, DE SURVEILLANCE OU DE PRÉVISION, NON PRÉVUS AILLEURS
10Administration; Gestion
06Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
CPC
G06Q 10/06
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
10Administration; Management
06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
Déposants DELL PRODUCTS LP
戴尔产品有限公司
Inventeurs PANIKKAR SHIBI
S·帕尼卡尔
ANSHUL SHANIR
S·安舒尔
DASH SUDESHNA
S·达什
CHIN MENG TUCK
M·T·秦
JI DONG
纪东
Mandataires 北京润平知识产权代理有限公司 11283
北京润平知识产权代理有限公司 11283
Titre
(EN) SMART SELECTION OF TEST SCRIPTS FOR COMMODITY TESTING ON MANUFACTURING FLOOR
(ZH) 用于商品测试的测试脚本的智能选择
Abrégé
(EN)
In product testing, a script prioritization tool (102) is used to intelligently prioritize the execution sequence of test scripts. This tool creates a repository of test outputs from the executions oftest scripts and analyzes the outputs to train and deploy a machine learning, ML, model that defines the priority of the scripts that may need to be executed and the scripts whose execution may be skipped without affecting the quality of testing. Scripts that are more likely to fail and/or are time consuming to execute are prioritized, while other scripts may be skipped. The ML model ranks the scripts based on the average execution time of the script, a count of the execution failures of the script, a count of the number of execution retries for the script, and the most recent failure time ofthe script. The scripts can be executed based on their rankings for efficiency and time-saving.

(ZH)
在产品测试中,脚本优先级排序工具(102)用于智能地确定测试脚本的执行顺序的优先级。该工具从测试脚本的执行中创建测试输出的存储库,并分析输出以训练和部署机器学习ML模型,该模型定义可能需要执行的脚本的优先级以及可以跳过执行不影响测试质量的脚本。更可能失败和/或执行耗时的脚本会被优先处理,而其他脚本可能被跳过。ML模型根据脚本的平均执行时间、脚本执行失败的总数、脚本的执行重试次数以及脚本的最近失败时间对脚本进行排序。脚本可以根据其排序执行,以提高效率和节省时间。

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