Motivation:

Software-based systems are becoming ever more important in our professional and private lives. Autonomous driving, Industry 4.0, Internet of Things, or Big Data represent innovations for which software is the enabler. The complexity of the systems is increasing continually. A proven means for dealing with the increasing complexity of integrated systems and mastering them is to set up metrics for development processes and resulting artifacts (such as requirements, architecture, code, or test cases). This makes it possible to detect problems regarding costs, schedule, and quality early on and to initiate appropriate countermeasures.

 

This lecture focuses on improving the quality of software products and processes as well as planning and controlling software development projects making use of software measurement.

 

After the lecture, you will obtain the following learning goals:

  • Remembering basic definitions, metrics, and application fields
  • Understanding motivations for software measurement and relationships between different models and methods
  • Applying selected existing measurement models and construct your own ones

 

The lecture includes the following 12 learning modules (0 to 11):

  • 0: Organization and Introduction
  • 1: Measurement Basics
  • 2: Goal-oriented Measurement
  • 3: Static Code Analysis
  • 4: Software Quality Models
  • 5: Software Defect Management
  • 6: Project Management
  • 7: Project Effort Estimation
  • 8: Function Points and Benchmarking
  • 9: SPI and Process Maturity
  • 10: The Learning Organization
  • 11: Related Work and Summary

 

Details about the lecture are available here: https://olat.vcrp.de/url/RepositoryEntry/4531978677

For more information, please contact Dr. Andreas Jedlitschka, Fraunhofer IESE, Email: andreas.jedlitschka(at)iese.fraunhofer.de

Software Process and Project Management (SS 2023)

Motivation:

Software-based systems are becoming ever more important in our professional and private lives. Autonomous driving, Industry 4.0, Internet of Things, or Big Data represent innovations for which software is the enabler. The complexity of the systems is increasing continually. A proven means for dealing with the increasing complexity of integrated systems and mastering them is to set up metrics for development processes and resulting artifacts (such as requirements, architecture, code, or test cases). This makes it possible to detect problems regarding costs, schedule, and quality early on and to initiate appropriate countermeasures.

 

This lecture focuses on improving the quality of software products and processes as well as planning and controlling software development projects making use of software measurement.

 

After the lecture, you will obtain the following learning goals:

  • Remembering basic definitions, metrics, and application fields
  • Understanding motivations for software measurement and relationships between different models and methods
  • Applying selected existing measurement models and construct your own ones

 

The lecture includes the following 12 learning modules (0 to 11):

  • 0: Organization and Introduction
  • 1: Measurement Basics
  • 2: Goal-oriented Measurement
  • 3: Static Code Analysis
  • 4: Software Quality Models
  • 5: Software Defect Management
  • 6: Project Management
  • 7: Project Effort Estimation
  • 8: Function Points and Benchmarking
  • 9: SPI and Process Maturity
  • 10: The Learning Organization
  • 11: Related Work and Summary

 

The first video lecture (Organization and Introduction) will be published via OLAT latest by April 17, 2023, 10:00 AM. The welcome live session via MS Teams is on April 17, 2023, 6:00 PM to 6:45 PM.

OLAT link: https://olat.vcrp.de/auth/RepositoryEntry/4071064229/Infos/0

For more information, please contact Dr. Jens Heidrich, Fraunhofer IESE, Email: jens.heidrich(at)iese.fraunhofer.de.

Motivation:

Software-based systems are becoming ever more important in our professional and private lives. Autonomous driving, Industry 4.0, Internet of Things, or Big Data represent innovations for which software is the enabler. The complexity of the systems is increasing continually. A proven means for dealing with the increasing complexity of integrated systems and mastering them is to set up metrics for development processes and resulting artifacts (such as requirements, architecture, code, or test cases). This makes it possible to detect problems regarding costs, schedule, and quality early on and to initiate appropriate countermeasures.

 

This lecture focuses on improving the quality of software products and processes as well as planning and controlling software development projects making use of software measurement.

 

After the lecture, you will obtain the following learning goals:

  • Remembering basic definitions, metrics, and application fields
  • Understanding motivations for software measurement and relationships between different models and methods
  • Applying selected existing measurement models and construct your own ones

 

The lecture includes the following 12 learning modules (0 to 11):

  • 0: Organization and Introduction
  • 1: Measurement Basics
  • 2: Goal-oriented Measurement
  • 3: Static Code Analysis
  • 4: Software Quality Models
  • 5: Software Defect Management
  • 6: Project Management
  • 7: Project Effort Estimation
  • 8: Function Points and Benchmarking
  • 9: SPI and Process Maturity
  • 10: The Learning Organization
  • 11: Related Work and Summary

 

OLAT link: https://olat.vcrp.de/auth/RepositoryEntry/3670934019

For more information, please contact Dr. Jens Heidrich, Fraunhofer IESE, Email: jens.heidrich(at)iese.fraunhofer.de.

Motivation:

Software-based systems are becoming ever more important in our professional and private lives. Autonomous driving, Industry 4.0, Internet of Things, or Big Data represent innovations for which software is the enabler. The complexity of the systems is increasing continually. A proven means for dealing with the increasing complexity of integrated systems and mastering them is to set up metrics for development processes and resulting artifacts (such as requirements, architecture, code, or test cases). This makes it possible to detect problems regarding costs, schedule, and quality early on and to initiate appropriate countermeasures.

 

This lecture focuses on improving the quality of software products and processes as well as planning and controlling software development projects making use of software measurement.

 

After the lecture, you will obtain the following learning goals:

  • Remembering basic definitions, metrics, and application fields
  • Understanding motivations for software measurement and relationships between different models and methods
  • Applying selected existing measurement models and construct your own ones

 

The lecture includes the following 12 learning modules (0 to 11):

  • 0: Organization and Introduction
  • 1: Measurement Basics
  • 2: Goal-oriented Measurement
  • 3: Static Code Analysis
  • 4: Software Quality Models
  • 5: Software Defect Management
  • 6: Project Management
  • 7: Project Effort Estimation
  • 8: Function Points and Benchmarking
  • 9: SPI and Process Maturity
  • 10: The Learning Organization
  • 11: Related Work and Summary

 

OLAT link: https://olat.vcrp.de/auth/RepositoryEntry/3157655647

For more information, please contact Dr. Jens Heidrich, Fraunhofer IESE, Email: jens.heidrich(at)iese.fraunhofer.de.

 

Motivation:

Software-based systems are becoming ever more important in our professional and private lives. Autonomous driving, Industry 4.0, Internet of Things, or Big Data represent innovations for which software is the enabler. The complexity of the systems is increasing continually. A proven means for dealing with the increasing complexity of integrated systems and mastering them is to set up metrics for development processes and resulting artifacts (such as requirements, architecture, code, or test cases). This makes it possible to detect problems regarding costs, schedule, and quality early on and to initiate appropriate countermeasures.

 

This lecture focuses on improving the quality of software products and processes as well as planning and controlling software development projects making use of software measurement.

 

After the lecture, you will obtain the following learning goals:

  • Remembering basic definitions, metrics, and application fields
  • Understanding motivations for software measurement and relationships between different models and methods
  • Applying selected existing measurement models and construct your own ones

 

The lecture includes the following 12 learning modules (0 to 11):

  • 0: Organization and Introduction
  • 1: Measurement Basics
  • 2: Goal-oriented Measurement
  • 3: Static Code Analysis
  • 4: Software Quality Models
  • 5: Software Defect Management
  • 6: Project Management
  • 7: Project Effort Estimation
  • 8: Function Points and Benchmarking
  • 9: SPI and Process Maturity
  • 10: The Learning Organization
  • 11: Related Work and Summary

 

In summer term 2020, this lecture will be performed as on online course for the first time:

  • Per learning module, 45-60 minutes long videos will be uploaded and be published via OLAT together with the presented slides as PDF
  • About every second learning model will be accompanied with practical exercises, which will be published as via OLAT together with example solutions
  • Every Monday, the lecturer will be available via OLAT chat, email, and Skype for answering questions (5:30 PM to 6:30 PM)
  • In addition, questions may be asked via the lecture's OLAT Forum

 

The first lecture (Organization and Introduction) will be published via OLAT on April 20, 2020, 10:00 AM.

 

OLAT link: https://olat.vcrp.de/auth/RepositoryEntry/2560196764/

 

For more information, please contact Dr. Jens Heidrich, Fraunhofer IESE, Email: jens.heidrich(at)iese.fraunhofer.de.

 

SS 2019

Contents of the lecture

 

  • Introduction to Software Measurement (GQM, COBIT)
  • Measuring Software Products (Functional Sizing, IFPUG, Reliability Growth, ISO 25000)
  • Measuring Software Processes (Defect Flow Models, ISBSG, CoCoMo, Delphi, CART)
  • Strategic Software Measurement (GQM+Strategies®)
  • The Learning Organization (QIP, Experience Factory, PSP/TSP)

Organization

Lecturer

Dr. Jens Heidrich

Regular dates

 

  • Lecture (KIS)
    • Mo, 10:00 - 11:30, room 11-207
    • The first lecture date is Mo, 29.04.2019.

Organization and Announcements

 

  • The lecture is organized via OpenOLAT (Link).