Lessons Learned from Model Based Development of a Distributed Embedded Automotive Control System

2004 ◽  
Author(s):  
Martin Törngren ◽  
Niklas Adamsson ◽  
Per Johannessen
Keyword(s):  
Control System ◽  
Lessons Learned ◽  
Automotive Control ◽  
Model Based

DEVELOPMENT OF ASYNCHRONOUS ELECTRIC DRIVE WITH SCALAR CONTROL

2019 ◽  
Author(s):  
Igor' Polyuschenkov
Keyword(s):  
Control System ◽  
Electric Drive ◽  
Microprocessor Control ◽  
Programming Technique ◽  
Scalar Control ◽  
Model Based ◽  
Asynchronous Electric Drive ◽  
Microprocessor Control System ◽  
Software And Hardware ◽  
Technical Solutions

The materials on the development of asynchronous electric drive with scalar control are given. The technical solutions associated with the design of software and hardware parts of the microprocessor control system are described. When developed, tools of model-based programming technique are used.

USING CLASSIFICATION TREES FOR SOFTWARE QUALITY MODELS: LESSONS LEARNED

1999 ◽  
Vol 09 (02) ◽  
pp. 217-231 ◽  
Author(s):  
TAGHI M. KHOSHGOFTAAR ◽  
EDWARD B. ALLEN ◽  
ARCHANA NAIK ◽  
WENDELL D. JONES ◽  
JOHN P. HUDEPOHL
Keyword(s):  
Software Quality ◽  
Classification Trees ◽  
Lessons Learned ◽  
Quality Models ◽  
Model Based ◽  
Software Product ◽  
High Assurance ◽  
Process Metrics ◽  
Product And Process ◽  
Software Quality Models

High software reliability is an important attribute of high-assurance systems. Software quality models yield timely predictions of quality indicators on a module-by-module basis, enabling one to focus on finding faults early in development. This paper introduces the Classification And Regression Trees (CART) a algorithm to practitioners in high-assurance systems engineering. This paper presents practical lessons learned on building classification trees for software quality modeling, including an innovative way to control the balance between misclassification rates. A case study of a very large telecommunications system used CART to build software quality models. The models predicted whether or not modules would have faults discovered by customers, based on various sets of software product and process metrics as independent variables. We found that a model based on two software product metrics had comparable accuracy to a model based on forty product and process metrics.

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