research-article

How automotive engineering is taking product line engineering to the extreme

Authors:

Len Wozniak,

Paul ClementsAuthors Info & Claims

SPLC '15: Proceedings of the 19th International Conference on Software Product Line

Pages 327 - 336

https://doi.org/10.1145/2791060.2791071

Published: 20 July 2015 Publication History

Get Access

Abstract

Automotive manufacturing ranks among the most extreme instances of systems and software product line engineering (PLE). The product family numbers in the millions, each product is highly complex in its own right, and the variation across products is literally astronomical in scale. This paper explores the aspects that make the domain extreme and the very specific implications they have for PLE. These implications include the need for efficient manufacturing, complexity management, concurrent development streams, globally distributed engineering and production, a hierarchical product family tree, multi-level variation binding, constraint management, and a highly robust and integrated PLE tooling environment. Happily, the PLE paradigm supporting these implications brings about a number of opportunities for analysis and automation that provide efficiencies of production previously unattainable. We focus on one example in depth: The management and automated generation of the many thousands of calibration parameters that determine vehicle-specific software behavior. Throughout, we use the vehicle product line at General Motors, which we believe to be the world's largest, to illustrate and ground our journey through automotive PLE.

References

[1]

Bachmann, F., Clements, P., "Variability in Software Product Lines," Technical Report CMU/SEI-2005-TR-012, Software Engineering Institute, 2005.

Google Scholar

[2]

BigLever Software, "BigLever Software's Product Line Engineering Solution," http://www.biglever.com/solution/solution.html

Google Scholar

[3]

Clements, P., Gregg, S., Krueger, C., Lanman, J., Rivera, J., Scharadin, R., Shepherd, J., Winkler, A. "Second Generation Product Line Engineering Takes Hold in the DoD," Crosstalk -- The Journal of Defense Software Engineering, vol. 27, no. 1, January/February 2014.

Google Scholar

[4]

Clements, P.; Northrop, L. Software Product Lines: Practices and Patterns, Addison-Wesley, 2002.

Digital Library

Google Scholar

[5]

Dillon, M., Rivera, J., Darbin, R., Clinger, B., "Maximizing U.S. Army Return on Investment Utilizing Software Product-Line Approach," Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), 2012.

Google Scholar

[6]

Flores, R., Krueger, C., Clements, P. "Mega-Scale Product Line Engineering at General Motors," SPLC 2012, Salvador, Brazil, 2012.

Digital Library

Google Scholar

[7]

Jensen, Paul. (2009). "Experiences with Software Product Line Development." CrossTalk 22, 1 (January 2009): 11--14.

Google Scholar

[8]

Krueger, C. "Multistage Configuration Trees for Managing Product Family Trees," in Proceedings of the 17th International Software Product Line Conference (SPLC 2013), Tokyo, Japan, Aug. 2013.

Digital Library

Google Scholar

[9]

Krueger, C., Clements, P. "Systems and Software Product Line Engineering," Encyclopedia of Software Engineering, Philip A. LaPlante ed., Taylor and Francis, 2013.

Google Scholar

[10]

Linden, Frank J. van der, Schmid, Klaus, Rommes, Eelco. Software Product Lines in Action, Springer, 2007.

Digital Library

Google Scholar

[11]

Paur, J. "Chevy Volt: King of (Software Cars)," Wired, November 5, 2010, http://www.wired.com/autopia/2010/11/chevy-volt-king-of-software-cars/

Google Scholar

[12]

Software Engineering Institute, "Catalog of Software Product Lines," http://www.sei.cmu.edu/productlines/casestudies/catalog/index.cfm

Google Scholar

[13]

Software Engineering Institute, "Framework for Product Line Practice (Version 5.0)" http://www.sei.cmu.edu/productlines/frame_report/index.html

Google Scholar

[14]

SPLC Product Line Hall of Fame, http://splc.net/fame.html

Google Scholar

Cited By

View all

Güthing LPett TSchaefer I(2024)Out-of-the-Box Prediction of Non-Functional Variant Properties Using Automated Machine LearningProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676546(82-87)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676546
Colletti RQamar ABailey WRolfes NParedis C(2024)A variable reference architecture for the management and configuration of ground vehicle simulationsInnovations in Systems and Software Engineering10.1007/s11334-022-00441-x20:3(185-207)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s11334-022-00441-x
Krapf PBerthier SLevy N(2023)Product Line Management with Graphical MBSE ViewsElectronic Proceedings in Theoretical Computer Science10.4204/EPTCS.392.4392(53-65)Online publication date: 31-Oct-2023
https://doi.org/10.4204/EPTCS.392.4
Show More Cited By

Index Terms

How automotive engineering is taking product line engineering to the extreme
1. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management

Recommendations

Mega-scale product line engineering at General Motors
SPLC '12: Proceedings of the 16th International Software Product Line Conference - Volume 1

General Motors faces probably the most complex Systems and Software Product Line Engineering (PLE) challenges ever, in terms of product complexity, richness of variation, size of organization, and an unforgiving requirement to support over a dozen ...
Second generation systems and software product line engineering
SPLC '13: Proceedings of the 17th International Software Product Line Conference

This paper describes a tutorial on an advanced set of product line engineering solutions, tools, and methods, which are being referred to as Second Generation Product Line Engineering (2GPLE).
Second generation systems and software product line engineering
SPLC '14: Proceedings of the 18th International Software Product Line Conference - Volume 1

This paper describes a tutorial on an advanced set of product line engineering solutions, tools, and methods, which are being referred to as Second Generation Product Line Engineering (2GPLE).

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

SPLC '15: Proceedings of the 19th International Conference on Software Product Line

July 2015

460 pages

ISBN:9781450336130

DOI:10.1145/2791060

General Chair:
Douglas C. Schmidt
Vanderbilt University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SPLC '15

Sponsor:

Vanderbilt University
Biglever

SPLC '15: 2015 International Conference on Software Product Lines

July 20 - 24, 2015

Tennessee, Nashville

Acceptance Rates

SPLC '15 Paper Acceptance Rate 34 of 87 submissions, 39%;

Overall Acceptance Rate 167 of 463 submissions, 36%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

35
Total Citations
View Citations
301
Total Downloads

Downloads (Last 12 months)45
Downloads (Last 6 weeks)6

Reflects downloads up to 26 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Güthing LPett TSchaefer I(2024)Out-of-the-Box Prediction of Non-Functional Variant Properties Using Automated Machine LearningProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676546(82-87)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676546
Colletti RQamar ABailey WRolfes NParedis C(2024)A variable reference architecture for the management and configuration of ground vehicle simulationsInnovations in Systems and Software Engineering10.1007/s11334-022-00441-x20:3(185-207)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s11334-022-00441-x
Krapf PBerthier SLevy N(2023)Product Line Management with Graphical MBSE ViewsElectronic Proceedings in Theoretical Computer Science10.4204/EPTCS.392.4392(53-65)Online publication date: 31-Oct-2023
https://doi.org/10.4204/EPTCS.392.4
Rodriguez HMuralidharan NSiavashi FPantelic VBandur VLawford MPaige R(2023)An Automotive Architecture Product Line for E/E Powertrain Architectures2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C59198.2023.00115(715-719)Online publication date: 1-Oct-2023
https://doi.org/10.1109/MODELS-C59198.2023.00115
Hassan MMahdi AAl-Sharhanee KAyad MShutnan WNajim A(2023)Designing a Prototype Smart Hotel with High Security, Solar Tracking, and IoT Lighting Control2023 International Conference on Engineering Applied and Nano Sciences (ICEANS)10.1109/ICEANS58413.2023.10630464(38-43)Online publication date: 25-Oct-2023
https://doi.org/10.1109/ICEANS58413.2023.10630464
Zhu LLugaresi GMatta A(2023)Automated Generation of Digital Models for Production Lines Through State Reconstruction2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)10.1109/CASE56687.2023.10260475(1-8)Online publication date: 26-Aug-2023
https://doi.org/10.1109/CASE56687.2023.10260475
Pedone CHartley DDarbin RClements P(2022)Practical Experience Applying Feature‐based Product Line Engineering in a DevOps Environment: Achieving the Best of Both WorldsINCOSE International Symposium10.1002/iis2.1295032:1(579-593)Online publication date: 26-Sep-2022
https://doi.org/10.1002/iis2.12950
Hartmann CWelm MSchreyer SHartmann CVolk W(2021)A Modular Car Body for Sustainable, Cost-Effective, and Versatile Vehicle DevelopmentTechnologies10.3390/technologies90100139:1(13)Online publication date: 9-Feb-2021
https://doi.org/10.3390/technologies9010013
Luckow AKlepsch JPichlmeier J(2021)Quantum Computing: Towards Industry Reference ProblemsDigitale Welt10.1007/s42354-021-0335-75:2(38-45)Online publication date: 8-Mar-2021
https://doi.org/10.1007/s42354-021-0335-7
Arifin HRobert Ong HDai JDaphne WChimplee N(2021)Model-Based Product Line Engineering with Genetic Algorithms for Automated Component SelectionComplex Systems Design & Management10.1007/978-3-030-73539-5_23(287-310)Online publication date: 10-Apr-2021
https://doi.org/10.1007/978-3-030-73539-5_23
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Mega-scale product line engineering at General Motors

Second generation systems and software product line engineering

Second generation systems and software product line engineering