@inbook {493, title = {Real-Time Traffic Lights Identification using YOLOv3 Algorithm For Autonomous Vehicles}, booktitle = {CAT Vehicle 2020 Technical Reports}, year = {2020}, abstract = {

Safety has always been a priority in automobile manufacture. Traffic light detection plays a major role in regards to safety in autonomous vehicles. Previ- ous methods involved utilizing a combination of image processing and training a neural network model. Those methods were not fully successful as they pre- sented limitations such as trouble detecting yellow and arrow traffic lights, the inability to identify a traffic light from a few pixels due to long distances, and the obstruction of traffic lights causing failure of detection. We propose to identify traffic lights and their states in both urban and suburban areas by developing a deep learning model utilizing a YOLOv3 model. Additionally, we will use the large dataset of traffic light images from the {\textquoteright}Bosch Small Traffic Lights Dataset{\textquoteright} to train the YOLOv3. Our proposed method will be successful because a better processed dataset indicates traffic lights in busier environments, and a balanced dataset allows the model to be better trained at identifying traffic signals and their status. The success of our proposed method will benefit autonomous ve- hicles{\textquoteright} feasibility by improving safety at intersections. The risks of this method include missing potential traffic signals which could lead to potential accidents. We will use a camera that will record the data that will later be processed. The mid-term check for success is accurate detection of traffic lights in ROS simula- tions, and the final check for success is the successful test drive of University of Arizona{\textquoteright}s CAT Vehicle by detecting traffic lights at intersections.

}, keywords = {Autonomous Driving, Neural Networks, Object Detection}, author = {Rachel Kozel and Naeemah Robert} } @inbook {476, title = {Feedback Control Algorithms for the Dissipation of Traffic Waves with Autonomous Vehicles}, booktitle = {Computational Intelligence and Optimization Methods for Control Engineering}, year = {2019}, pages = {275{\textendash}299}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

This article considers the problem of traffic control in which an autonomous vehicle is used to regulate human-piloted traffic to dissipate stop-and-go traffic waves. We first investigated the controllability of well-known microscopic traffic flow models, namely, (i) the Bando model (also known as the optimal velocity model), (ii) the follow-the-leader model, and (iii) a combined optimal velocity follow-the-leader model. Based on the controllability results, we proposed three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffics. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally, we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle-based traffic control on real human-piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up\ to 20{\%}.

}, isbn = {978-3-030-25446-9}, doi = {10.1007/978-3-030-25446-9_12}, url = {https://doi.org/10.1007/978-3-030-25446-9_12}, author = {Maria Laura Dell Monache and Liard, Thibault and Rat, Ana{\"\i}s and Raphael E Stern and Rahul Bhadani and Benjamin Seibold and Jonathan Sprinkle and Daniel B. Work and Benedetto Piccoli}, editor = {Blondin, Maude Jos{\'e}e and Pardalos, Panos M. and Sanchis S{\'a}ez, Javier} } @conference {469, title = {A Fuzzy based approach to Dampen Emergent Traffic Waves}, booktitle = {CAT Vehicle Research Experience for Undergraduates}, year = {2017}, month = {01/2017}, publisher = {CAT Vehicle Research Experience for Undergraduates}, organization = {CAT Vehicle Research Experience for Undergraduates}, address = {The University of Arizona}, abstract = {

Adaptive Cruise Control (ACC) and Traffic Aware Cruise Control (TACC) are recent advancements in cruise control design that allow a semi-autonomous vehicle to slow itself when approaching vehicles. The issue with these technologies is that they focus on keeping the distance from a leading vehicle constant. This may lead to unwanted dynamics in the following traffic flow, could result in the creation of traveling waves. \ This paper focuses on maintaining a reference velocity based on the relative position of the preceding vehicle instead of slowing down to maintain a certain following distance. Doing so could reduce the amount of braking the vehicles behind the autonomous vehicle will do. With this kind of technology implemented, the number and duration of traffic jams could be greatly reduced. Simulation results and tests run on the University of Arizona{\textquoteright}s Cognitive Autonomous Test (CAT) Vehicle illustrate the feasibility and success of this new controller.

}, keywords = {Autonomous Systems, Control System}, author = {R{\textquoteright}mani Haulcy and Nathaniel Hamilton and Rahul Bhadani and Jonathan Sprinkle and Daniel B. Work and Nathalie Risso and Benedetto Piccoli and Maria Laura Dell Monache and Benjamin Seibold} } @conference {olson2017, title = {Fuzzy Control of an Autonomous Car using a Smart Phone}, booktitle = {Proceedings of the 2017 IEEE International Conference on Automatica (ICA-ACCA)}, year = {2017}, pages = {1{\textendash}5}, publisher = {IEEE}, organization = {IEEE}, author = {Elizabeth A. Olson and Nathalie Risso and Adam M. Johnson and Jonathan Sprinkle} } @conference {sprinkle295, title = {Model Predictive Control for Space Missions}, booktitle = {The First American Model Predictive Control Summer School}, year = {2017}, author = {Bharani P. Malladi and Nathalie Risso and Yegeta Zeleke} } @conference {risso2017sufficient, title = {Sufficient conditions for asymptotic stability and feedback control of set dynamical systems}, booktitle = {American Control Conference (ACC), 2017}, year = {2017}, pages = {1923{\textendash}1928}, publisher = {IEEE}, organization = {IEEE}, author = {Nathalie Risso and Sanfelice, Ricardo G} } @article {risso2016detectability, title = {Detectability and Invariance Properties for Set Dynamical Systems}, journal = {IFAC-PapersOnLine}, volume = {49}, year = {2016}, pages = {1030{\textendash}1035}, author = {Nathalie Risso and Sanfelice, Ricardo G} } @conference {sprinkle261, title = {Adaptive Multifactor Routing with Constrained Data Sets}, booktitle = {Wireless Innovation Forum Conference on Wireless Communication Technologies and Software Defined Radio (WInnComm)}, year = {2015}, month = {03/2015}, address = {San Diego, CA}, abstract = {

Autonomous Vehicles can benefit greatly from the use of cellular infrastructure. Consequently, it may be desirable at times to consider the availability of this infrastructure when planning autonomous vehicle routes. In order to make such decisions it is necessary to have up-to-date knowledge of signal strength in surrounding areas. We consider the quality of routing possible when using incomplete knowledge of signal strength along a route. As our motivation for how signal strength information would be constrained we consider Vehicle to Vehicle communications. Such communications offer great promise in creating real-time signal maps through a decentralized data collection and aggregation process. One might envision such a process involving the transfer of signal reception information between cars within an area. Such a process, while low-latency and low-cost, could suffer from limited data availability beyond relatively short ranges. In order to route based on signal strength we employ a weighting formula to combine distance and signal strength into a single cost quantity. Then, we apply this formula to a city grid map with signal strength information. We replace the distance values with the formula{\textquoteright}s aggregate cost values. The cost values are then presented to a shortest path routing algorithm to determine the lowest cost path. Finally, we simulate a vehicle which regularly updates a signal map of its surroundings and continuously updates its route in response. The costs of its chosen path and the cost of the ideal path are then recorded. In order to rigorously test our routing formula{\textquoteright}s performance with varying degrees of information we employ a Matlab program that randomly generates thousands of city signal maps to run the routing formula and algorithms on. The routing algorithms are run with route signal knowledge between 0\% and 100\%. We chart the average ratio between partial knowledge and full knowledge path costs. We consider the performance of a variety of algorithms and conclude that using Dijkstra we may produce routes that are 95\% optimal using a signal knowledge window only 1/10 of our total route size. These results indicate the potential for excellent routing even when V2V communication can only offer highly constrained data sets. However, the use of random maps potentially weakens our results as real world signal maps tend to be patterned and non-random. Such patterns are extremely problematic as there is great potential for scenarios that do not occur frequently in a randomly generated map and that require extensive map knowledge. For example, the need to find an exit to a signal dead-zone One might view our randomized maps as presenting the signal knowledge limited algorithm a series of local minima optimization problems. In a random map with extremely high signal value variance there is likely to be a variety of immediately visible signal dead-zones and strong signal zones that all have small sizes and are consistently intermixed. As a result, a knowledge limited algorithm can easily avoid a high cost path by moving between small strong signal zones while avoiding the interspersed dead zones with little advanced knowledge. We expect that the most relevant metric for signal formula routing performance may be the ratio between the median size of extreme signal zones and the size of the signal knowledge window. This ratio directly determines the ability of the path cost minimization algorithm to solve path cost as a series of local minima. In order to test the potential value of this metric we tweak our random map generation algorithm to assign a random signal values to increasing numbers of intersections. For example, we might assign each random value to 4x4 intersection grids. Then, we would apply that single value to 8x8 grids. This modification allows us to directly alter the size of extreme signal zones and test the performance of the routing algorithm as extreme signal zones outsize the size of the signal knowledge window

}, author = {Torger Miller and Cody Ross and Matheus Marques Barbosa and Mohammed Hirzallah and Haris Volos and Jonathan Sprinkle} } @proceedings {Gray:2015:2846696, title = {{DSM 2015: Proceedings of the Workshop on Domain-Specific Modeling}}, year = {2015}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-3903-2}, author = {Jeffrey Gray and Jonathan Sprinkle and Juka-Pekka Tolvanen and Matti Rossi} } @conference {467, title = {Workshop Preview of the 15th Workshop on Domain Specific Modeling (DSM 2015)}, booktitle = {Companion Proceedings of the 2015 ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity}, year = {2015}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Code Generation, domain-specific languages, metamodeling, modeling languages}, isbn = {978-1-4503-3722-9}, doi = {10.1145/2814189.2833204}, url = {http://doi.acm.org/10.1145/2814189.2833204}, author = {Jeffrey Gray and Jonathan Sprinkle and Juka-Pekka Tolvanen and Matti Rossi} } @conference {sprinkle258, title = {A Heterogeneity Based Method to Identify Major Variability Components}, booktitle = {International Conference on Electronics, Communications, and Networks}, year = {2014}, month = {12/2014}, address = {Beijing}, author = {Fahd Shaikh and Wei He and Jonathan Sprinkle and K. Chen and Janet Roveda} } @article {214, title = {A Modular Framework to Enable Rapid Evaluation and Exploration of Energy Management Methods in Smart Home Platforms}, journal = {Energy Systems}, year = {2014}, month = {04/2014}, pages = {Online First}, abstract = {

Numerous efforts focus on developing smart grid and smart home plat- forms to provide monitoring, management, and optimization solutions. In order to more effectively manage energy resources, a holistic view is needed; however the involved platforms are complex and require integration of a multitude of parameters such as the end-user behavior, underlying hardware components, environment, etc., many of which operate on varying time scale at various levels of detail. A general and modular framework is presented to enable designers to focus on modeling, simulating, analyzing, or optimizing specific sub-components without requiring a detailed imple- mentation across all levels. We incorporate two case studies in which the proposed framework is utilized to help an end user evaluate platform configurations given an energy usage model, as well as integrate an energy optimization module to investigate rescheduling of appliance usage times in an effort to lower cost.\ 

}, issn = {1868-3967}, doi = {10.1007/s12667-014-0121-9}, url = {http://dx.doi.org/10.1007/s12667-014-0121-9}, author = {Xiao Qin and Lin Lin and Susan Lysecky and Janet Roveda and Young-Jun Son and Jonathan Sprinkle} } @conference {nanez2014symbolic, title = {A symbolic simulator for hybrid equations}, booktitle = {Proceedings of the 2014 Summer Simulation Multiconference}, year = {2014}, pages = {18}, publisher = {Society for Computer Simulation International}, organization = {Society for Computer Simulation International}, author = {Nanez, Pablo and Nathalie Risso and Sanfelice, Ricardo G} } @conference {211, title = {Generating a {ROS/JAUS} Bridge for an Autonomous Ground Vehicle}, booktitle = {Proceedings of the 2013 ACM workshop on Domain-specific modeling (DSM {\textquoteright}13)}, year = {2013}, pages = {13-18}, publisher = {ACM}, organization = {ACM}, address = {Indianapolis, IN}, abstract = {

Robotic systems have truly benefitted from standardized middleware that can componentize the development of new capabilities for a robot. The popularity of these robotic middleware systems has resulted in sizable libraries of components that are now available to roboticists. However, many robotic systems (such as autonomous vehicles) must adhere to externally defined standards that are not blessed with such a large repository of components. Due to the real-time and safety concerns that accompany the domain of unmanned systems, it is not trivial to interface these middleware systems, and previous attempts to do so have succeeded at the cost of ad hoc design and implementation. This paper describes a domain-specific approach to the synthesis of a bridge between the popular Robotic Operating System (ROS) and the Joint Architecture for Unmanned Systems (JAUS). The domain-specific nature of the approach permits the bridge to be limited in scope by the application{\textquoteright}s specific messages (and their attribute mappings between JAUS/ROS), resulting in smaller code size and overhead than would be incurred by a generic solution. Our approach is validated by tests performed on an unmanned vehicle with and without the JAUS/ROS bridge.

}, keywords = {autonomous vehicles, Code Generation}, doi = {10.1145/2541928.2541931}, url = {http://dx.doi.org/10.1145/2541928.2541931}, author = {Patrick Morley and Alex Warren and Ethan Rabb and Matthew Bunting and Sean Whitsitt and Jonathan Sprinkle} } @conference {224, title = {The 12th Workshop on Domain-specific Modeling}, booktitle = {Proceedings of the 3rd Annual Conference on Systems, Programming, and Applications: Software for Humanity}, year = {2012}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Code Generation, domain-specific languages, metamodeling, modeling languages}, isbn = {978-1-4503-1563-0}, doi = {10.1145/2384716.2384784}, url = {http://doi.acm.org/10.1145/2384716.2384784}, author = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi and Jeffrey Gray} } @conference { c:whitsitt-ecbs-2012, title = {On the Extraction and Analysis of a Social Network with Partial Organizational Observation}, booktitle = {Proceedings of the 19th IEEE International Conference and Workshops on Engineering of Computer-Based Systems}, year = {2012}, pages = {249-256}, abstract = {

The behavior of an organization may be inferred based on the behavior of its members, their contacts, and their connectivity. One approach to organizational analysis is the construction and interpretation of a social network graph, where entities of an organization (persons, vehicles, locations, events, etc.) are nodes, and edges represent varying kinds of connectivity between entities. This paper describes a transformation based approach to the extraction of a social network graph, where the original data comprising (partial) observation of the organization are embedded on a graph with a different ontology, and with many entities and edges that are unrelated to the organization of interest. Social network extraction allows the inference of implied relationships, and the selection of relationships relevant for intended analysis techniques. The analysis of the resulting social network graph is based on organizational and individual analysis, in order to permit an advanced user to draw conclusions regarding the behavior of the organization, based on established social network graph metrics. The results of the paper include a discussion of the complexity of analysis, and how the observation data graph is pruned in order to scale the application of analysis algorithms.

}, doi = {10.1109/ECBS.2012.33}, url = {http://dx.doi.org/10.1109/ECBS.2012.33}, author = {Sean Whitsitt and Abishek Gopalan and Sangman Cho and Jonathan Sprinkle and Srinivasan Ramasubramanian and Liana Suantak and Jerzy Rozenblit} } @proceedings {225, title = {Proceedings of the 12th Workshop on Domain-specific Modeling}, year = {2012}, month = {10/2012}, publisher = {ACM}, address = {New York, NY, USA}, author = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi and Jeffrey Gray} } @conference {222, title = {The 11th Workshop on Domain-specific Modeling}, booktitle = {Proceedings of the ACM International Conference Companion on Object Oriented Programming Systems Languages and Applications Companion}, year = {2011}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Code Generation, domain-specific languages, metamodeling, modeling languages}, isbn = {978-1-4503-0942-4}, doi = {10.1145/2048147.2048227}, url = {http://doi.acm.org/10.1145/2048147.2048227}, author = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi and Jeffrey Gray} } @conference {466, title = {The 11th Workshop on Domain-specific Modeling}, booktitle = {Proceedings of the Compilation of the Co-located Workshops on DSM{\textquoteright}11, TMC{\textquoteright}11, AGERE! 2011, AOOPES{\textquoteright}11, NEAT{\textquoteright}11, \& VMIL{\textquoteright}11}, year = {2011}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Code Generation, domain-specific languages, metamodeling, modeling languages}, isbn = {978-1-4503-1183-0}, doi = {10.1145/2095050.2095052}, url = {http://doi.acm.org/10.1145/2095050.2095052}, author = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Jeffrey Gray and Matti Rossi} } @conference { c:sachi-ecbs-2011, title = {Hardware/Software Communication Middleware for Data Adaptable Embedded Systems}, booktitle = {Proceedings of the 18th IEEE International Conference and Workshops on Engineering of Computer-Based Systems}, year = {2011}, pages = {34-43}, publisher = {IEEE Computer Society Press}, organization = {IEEE Computer Society Press}, abstract = {

Recent trends toward increased flexibility and configurability in emerging applications present demanding challenges for implementing systems that incorporate such capabilities. The resulting application configuration space is generally much larger than any one hardware implementation can support. We provide an overview of a new data-adaptive approach to the rapid design and implementation of such highly configurable applications. In support of this data-adaptable approach, we present and detail an efficient and flexible hardware/software communication middleware to support the seamless communication between hardware and software tasks at runtime. We highlight the flexibility of this interface and present an initial case study and results demonstrating the performance capabilities and area requirements.

}, doi = {10.1109/ECBS.2011.12}, url = {http://dx.doi.org/10.1109/ECBS.2011.12}, author = {Sachidanand Mahadevan and Vijay Gopinath and Roman Lysecky and Jonathan Sprinkle and Jerzy Rozenblit and Michael Marcellin} } @proceedings {223, title = {Proceedings of the 11th Workshop on Domain-Specific Modeling}, year = {2011}, publisher = {ACM}, address = {Portland, OR}, author = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi and Jeffrey Gray} } @proceedings {p:DSM10, title = {10th Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}10)}, year = {2010}, note = {{ISBN}: 978-952-60-1043-4}, month = {October}, publisher = {OOPSLA/SPLASH}, editor = {Matti Rossi and Juka-Pekka Tolvanen and Jonathan Sprinkle and Steven Kelly} } @conference {c:whitsitt-prose-2010, title = {Citizen Science in Support of Vegetation Index and Phenology Research}, booktitle = {Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE)}, year = {2010}, month = {October}, abstract = {

Vegetation indices (VIs) are simple transformations of images into proxy measures of greenness and vegetation health and change over time. They are also used to derive information about the land surface phenology status, providing extensive spatial coverage and direct support for global ecosystem models. These measurements however contain large uncertainties and errors. A new suite of mobile devices, equipped with geo-location, image capture, and transmission capabilities could aid with vegetation phenology observations and documentation. The iPhone, with its wide distribution and array of sensors, can contribute significantly to the field of citizen science. In this project we are developing an end-to-end system for the collection, processing, and visualization of land surface vegetation phenology. The system consists of a client-server application and a Google Earth based visualization model. The client side (an iPhone app) intuitively guides the observer to capture up to three images per location: a close-up image of leaves, flowers, or fruits, an individual plant image, and a panoramic landscape image. The iPhone automatically embeds location, orientation, date/time, and other metadata with the images and allows the observer to add text comments. The images are then transmitted to the server, where they are validated, post-processed, archived, and made available to the interactive visualization system. The images are separated into primary colors and processed into a greenness index comparable to the classical VI. These measurements are then plotted against satellite based VI time series to aid in their validation and the characterization of the location phenology. With this effort we hope to recruit global observers into contributing to the field of land surface vegetation change detection and characterization.

}, author = {Sean Whitsitt and Armando Barreto and Sundaresh Ram and Hussain Al-Helal and Maribel Hudson and Diyang Chu and Jonathan Sprinkle and Kamel Didan} } @inbook { j:sprinkle-mbeerts4-2009, title = {Metamodelling}, booktitle = {Model-Based Engineering of Embedded Real-Time Systems}, series = {Lecture Notes in Computer Science}, volume = {6100}, year = {2010}, pages = {59{\textendash}78}, publisher = {Springer}, organization = {Springer}, chapter = {4}, url = {http://www.springer.com/computer/swe/book/978-3-642-16276-3}, author = {Jonathan Sprinkle and Bernhard Rumpe and Hans Vangheluwe and G{\'a}bor Karsai} } @inbook { j:levendovszky-mbeerts14-2009, title = {Model Evolution and Management}, booktitle = {Model-Based Engineering of Embedded Real-Time Systems}, series = {Lecture Notes in Computer Science}, volume = {6100}, year = {2010}, pages = {243{\textendash}272}, publisher = {Springer}, organization = {Springer}, chapter = {10}, url = {http://www.springer.com/computer/swe/book/978-3-642-16276-3}, author = {T{\'\i}hamer Levendovszky and Bernhard Rumpe and Bernhard Sch{\"a}tz and Jonathan Sprinkle and Hans Vangheluwe} } @article { j:chu-ijmav-2010, title = {Simulations and Flight Experiments of Transition Maneuvers of a {VTOL} Micro Air Vehicle}, journal = {International Journal of Micro Air Vehicles}, volume = {2}, number = {2}, year = {2010}, note = {{ISSN} 1756-8293}, month = {June}, pages = {69{\textendash}89}, doi = {10.1260/1756-8293.2.2.69}, url = {http://dx.doi.org/10.1260/1756-8293.2.2.69}, author = {Diyang Chu and Jonathan Sprinkle and Ryan Randall and Sergey Shkarayev} } @proceedings {p:DSM09, title = {9th {OOPSLA} Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}09)}, year = {2009}, note = {ISBN: 978-952-488-371-9}, month = {October}, publisher = {OOPSLA}, url = {http://hsepubl.lib.hse.fi/FI/publ/hse/b108}, editor = {Matti Rossi and Jonathan Sprinkle and Jeffrey Gray and Juka-Pekka Tolvanen} } @conference { c:chu-gnc-2009, title = {Automatic Control of {VTOL} Micro Air Vehicle During Transition Maneuver}, booktitle = {AIAA Guidance, Navigation and Control Conference}, year = {2009}, note = {{AIAA-2009-5875}}, month = {August}, pages = {16 pages}, publisher = {AIAA}, organization = {AIAA}, url = {http://pdf.aiaa.org/preview/CDReadyMGNC09_1998/PV2009_5875.pdf}, author = {Diyang Chu and Jonathan Sprinkle and Ryan Randall and Sergey Shkarayev} } @article {HCTCPS, title = {A Community Report of the 2008 High Confidence Transportation Cyber-Physical Systems {(HCTCPS)} Workshop}, year = {2009}, month = {July 22}, address = {High Confidence Transportation Cyber-Physical Systems (HCTCPS)}, url = {http://www.ee.washington.edu/research/nsl/aar-cps/}, author = {Radha Poovendran and Raj Rajkumar and David Corman and Jim Paunicka and William P. Milam and K Venkatesh Prasad and Shige Wang and Jim Barhorst and Christopher Gill and Sandeep Gupta and Krishna Sampigethaya and Jonathan Sprinkle and Doug Stuart and Wayne Wolf and Rahul Mangharam} } @proceedings {p:DSM08, title = {8th {OOPSLA} Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}08)}, year = {2008}, note = {{ISBN: 978-0-61523-024-5}}, month = {October}, publisher = {OOPSLA}, url = {http://www.dsmforum.org/events/DSM08/Papers/DSM08-proceedings.pdf}, editor = {Jeffrey Gray and Jonathan Sprinkle and Matti Rossi and Juka-Pekka Tolvanen} } @proceedings {p:DSM07, title = {7th {OOPSLA} Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}07)}, year = {2007}, note = {ISBN: 978-951-39-2915-2}, month = {October}, publisher = {OOPSLA}, address = {Jyv{\"a}skyl{\"a}, Finland}, url = {http://www.dsmforum.org/events/DSM07/Papers.html}, editor = {Jonathan Sprinkle and Jeffrey Gray and Matti Rossi and Juka-Pekka Tolvanen} } @proceedings {p:DSM05, title = {5th {OOPSLA} Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}05)}, year = {2005}, note = {ISBN 951-39-2202-2}, month = {October}, publisher = {OOPSLA}, address = {Jyv{\"a}skyl{\"a}, Finland}, editor = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi} } @proceedings {p:DSM04, title = {4th {OOPSLA} Workshop on Domain-Specific Modeling ({DSM}{\textquoteright}04)}, year = {2004}, note = {ISBN: 951-39-1947-1}, month = {October}, publisher = {OOPSLA}, address = {Jyv{\"a}skyl{\"a}, Finland}, url = {http://www.dsmforum.org/events/DSM04/Proceedings-DSM04.zip}, editor = {Juka-Pekka Tolvanen and Jonathan Sprinkle and Matti Rossi} }