Publications

• Title   :   

  KADRE: Domain-Specific Architectural Recovery for Scientific Software Systems.

  Abstract   :   

  Scientists today conduct new research via software-based experimentation and validation in a host of disciplines. Scientific software represents a significant investment due to its complexity and longevity yet there is little reuse of scientific software beyond small libraries which increases development and maintenance costs. To alleviate this disconnect, we have developed KADRE, a domain-specific architecture recovery approach and toolset to aid automatic and accurate identification of workflow components in existing scientific software. KADRE improves upon state of the art general cluster techniques, helping to promote component-based reuse within the domain.
  
  D. Woollard, C. Mattmann, D. Popescu, and N. Medvidovic. KADRE: Domain-Specific Architectural Recovery for Scientific Software Systems. In Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering, Antwerp, Belgium, September, 2010.
• Title   :   

  A Distributed Computing Infrastructure for the Evaluation of Climate Models Using NASA Observational Data.

  Abstract   :   

  We describe and motivate an emerging distributed data analysis environment for the empirical evaluation of climate models. This work has several components, including: model scoring, initialization and parameterization, all of which require massive amounts of NASA observational data. Though the effort is in its nascence, there has been recent success in partnering with the DOE Earth System Grid to unify data from NASA's AIRS mission and model outputs available from the Program for Climate Model Diagnosis and Intercomparison (PCMDI).
  
  C. Mattmann, D. Crichton, A. Braverman, D. Williams, M. Gunson, D. Woollard, S. Kelly, M. Cayanan. A Distributed Computing Infrastructure for the Evaluation of Climate Models Using NASA Observational Data. Proceedings of the IEEE International Conference on Data Mining Workshops, Miami, Florida, December, 2009.
• Title   :   

  A Science Data System Approach for the SMAP Mission.

  Abstract   :   

  Though Science Data System (SDS) development has not traditionally been part of the mission concept phase, lessons learned and study of past Earth science missions indicate that SDS functionality can greatly benefit algorithm developers in all mission phases. We have proposed a SDS approach for the SMAP Mission that incorporates early support for an algorithm testbed, allowing scientists to develop codes and seamlessly integrate them into the operational SDS. This approach will greatly reduce both the costs and risks involved in algorithm transitioning and SDS development.
  
  D. Woollard, O. ig Kwoun, T. Bicknell, S. Dunbar, and K. Leung. A Science Data System Approach for the SMAP Mission. In IEEE Radar, 2009.
• Title   :   

  Injecting Software Architectural Constraints into Legacy Scientific Applications.

  Abstract   :   

  While software architectures have been shown to aid developers in maintenance, reuse, and evolution as well as many other software engineering tasks, there is little language-level support for these architectural concepts in scientific programming languages such as Fortran and C. Because many existing scientific codes are written in legacy languages, it is difficult to integrate them into architected software systems. By wrapping scientific codes in architecturally-aware interfaces, we are able to componentize legacy programs, integrating them into systems built with first-class architectural elements while meeting performance and throughput requirements of scientific codes.
  
  D. Woollard, C. Mattmann, and N. Medvidovic. Injecting Software Architectural Constraints into Legacy Scientific Applications. In proceedings of the 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering, Vancouver, Canada, May 2009.
• Title   :   

  A Reusable Process Control System Framework for the Orbiting Carbon Observatory and NPP Sounder PEATE Missions.

  Abstract   :   

  We describe a reusable architecture and implementation framework for managing science processing pipelines for mission ground data systems. Our system, dubbed "PCS," for Process Control System, improves upon an existing software component, the OODT Catalog and Archive (CAS), which has already supported the QuikSCAT, SeaWinds and AMT earth science missions. This paper focuses on PCS within the context of two current earth science missions: the Orbiting Carbon Observatory (OCO), and NPP Sounder PEATE projects.
  
  C. Mattmann, D. Freeborn, D. Crichton, B. Foster, A. Hart, D. Woollard, S. Hardman, P. Ramirez, S. Kelly, A. Chang, C. Miller. A Reusable Process Control System Framework for the Orbiting Carbon Observatory and NPP Sounder PEATE Missions. In proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology, 2009.
• Title   :   

  Supporting the Engineering Aspects of e-Science Through Workflow Services.

  Abstract   :   

  Workflows are models of computation that provide abstractions useful to the scientist conducting e-Science. Workflow practitioners interested in experiment repeatability and large volume data processing must manage both scientific and engineering aspects of workflow development. Engineering concerns are often encapsulated as Workflow Services, though no uniform method of accessing these services exists. A domain-specific software architecture can aid the scientist in accessing these services, isolating the concerns of the engineer from those of scientists through the use of software connectors.
  
  D. Woollard. Supporting the Engineering Aspects of e-Science Through Workflow Services. Proceedings of II e-Sience Workshop do XXIII Simpósio Brasileiro de Bancos de Dados e XXII Simpósio Brasileiro de Engenharia de Software, Campinas, Brazil, October, 2008.
• Title   :   

  Scientific Software as Workflows: From Discovery to Distribution.

  Abstract   :   

  Scientific workflows – models of computation that capture the orchestration of scientific codes to conduct "in silico" research – are gaining recognition as an attractive alternative to script-based orchestration. Despite growing interest, there are a number of fundamental challenges that researchers developing scientific workflow technologies must address, including developing the underlying "science" of scientific workflows. In this article, we present a broad classification of scientific workflow environments based on three major phases of in-silico research as well as highlight active research projects that illustrate this classification With our tripartite classification, based on the phases of "in silico" research, scientists will be capable of making more informed decisions regarding the adoption of particular workflow environments.
  
  D. Woollard, N. Medvidovic, Y. Gil, and C. Mattmann. Scientific Software as Workflows: From Discovery to Distribution. IEEE Software - Special Issue on Developing Scientific Software, 2008.
• Title   :   

  Exploiting Connector Knowledge to Efficiently Disseminate Highly Voluminous Data Sets.

  Abstract   :   

  Ever-growing amounts of data that must be distributed from data providers to consumers across the world necessitate a greater understanding of the software architectural implications of choosing data movement technologies. Currently, this understanding is mired in the minds of software architects who have been there before, and who rely on past intuition and choices, failing to properly document their rationale and context. In this paper we describe a software architecture-based decision making framework called DISCO for selecting data movement technologies, or software connectors. DISCO effectively captures (traditionally undocumented) insight, observation and ultimately architectural knowledge about the connectors, demonstrating the effectiveness of using such information to accurately encode the connector selection decision making process.
  
  C. Mattmann, D. Woollard, N. Medvidovic. Exploiting Connector Knowledge to Efficiently Disseminate Highly Voluminous Data Sets. Proceedings of the ICSE 2008 Workshop on SHAring and Reusing architectural Knowledge - SHARK 2008, Leipzig, Germany, May, 2008.
• Title   :   

  Case Studies in Science Data Systems: Meeting Software Challenges in Competitive Environments.

  Abstract   :   

  Science data systems – the hardware and software systems designed to process and generate scientific data – are growing more complex in both computational task and data volumes/rates in direct response to the growing complexity of scientific instruments being designed and flown on space science missions today. At the same time, cost capping of these missions has reduced available funding for software development. Leveraging existing science data system software offers the possibility of reducing development costs, though software reuse has been shown to be neither panacean nor a software engineering "silver bullet." Rather than take a prescriptive stand, we chose to explore the current state of practice in the development of science data systems, presenting four case studies of existing Earth Science missions lead by the Jet Propulsion Laboratory. In addition to presenting these case studies, we summarize our recommendation for the next generation of science data systems, looking to reduce costs through areas of likely software reuse as well as new technologies to simplify the development process.
  
  D. Woollard, D. Freeborn, E. Kay-Im, S. LaVoie. Case Studies in Science Data Systems: Meeting Software Challenges in Competitive Environments. In proceedings of the 10th International Conference on Space Operations, Heidelberg, Germany, May 2008.
• Title   :   

  Software Connector Classification and Selection for Data-intensive Systems.

  Abstract   :   

  Data-intensive systems and applications transfer large volumes of data and metadata to highly distributed users separated by geographic distance and organizational boundaries. An influential element in these large volume data transfers is the selection of the appropriate software connector that satisfies user constraints on the required data distribution scenarios. Currently, this task is typically accomplished by consulting "gurus," who rely on their intuitions, at best backed by anecdotal evidence. In this paper we present a systematic approach for selecting software connectors based on eight key dimensions of data distribution that we use to represent the data distribution scenarios. Our approach, dubbed DISCO, has been implemented as a Java-based framework. The early experience with DISCO indicates good accuracy and scalability.
  
  C. Mattmann, D. Woollard, N. Medvidovic and R. Mahjourian. Software Connector Classification and Selection for Data-intensive Systems. Proceedings of the ICSE 2007 Workshop on Incorporating COTS Software into Software Systems: Tools and Techniques (IWICSS), Minneapolis, MN, May 22, 2007.
• Title   :   

  An Architectural Style for High-Performance Asymmetrical Parallel Computations.

  Abstract   :   

  Researchers with deep knowledge of scientific domains are becoming more interested in developing highly-adaptive and irregular (asymmetrical) parallel computations, leading to development challenges for both delivery of data for computation and mapping of processes to physical resources. Using software engineering principles, we have developed a new communications protocol and architectural style for asymmetrical parallel computations called ADaPT. Utilizing the support of architecturally-aware middleware, we show that ADaPT provides a more efficient solution in terms of message passing and load balancing than asymmetrical parallel computations using collective calls in the Message-Passing Interface (MPI) or more advanced frameworks implementing explicit load-balancing policies. Additionally, developers using ADaPT gain significant windfall from good practices in software engineering, including implementation-level support of architectural artifacts and separation of computational loci from communication protocols.
  
  D. Woollard and N. Medvidovic. An Architectural Style for High-Performance Asymmetrical Parallel Computations. Proceedings of the International Conference of Software Engineering (ICSE 2006), Shanghai, China, May, 2006.
• Title   :   

  ADaPT: An Event-Passing Protocol for Reducing Delivery Costs in Scatter-Gather Parallel Processes.

  Abstract   :   

  The scatter-gather event pattern is commonly used in many high-performance codes to deliver data subsets for use in data-parallel processes and return the results. There are a number of collective algorithms and multiple collective calls in the ubiquitous Message Passing Interface standards which perform aspects of gathering. Programmers have traditionally been left to their own devices, however, to perform complex scatterings of data subsets to processors executing the data-parallel computation. We have developed ADaPT, an Adaptive Data-parallel Publication/Subscription Transport protocol, to reduce the time lost to excessive synchronization with the unicast event-passing commands often employed to scatter data.
  
  D. Woollard, N. Medvidovic, W. Yamada, and T. Berger. ADaPT: An Event-Passing Protocol for Reducing Delivery Costs in Scatter-Gather Parallel Processes. In proceedings of the Workshop for Patterns in High Performance Computing, Urbana, Illinois, May, 2005.
• Title   :   

  Software Engineering for Neural Dynamics: A Case Study.

  Abstract   :   

  The Center for Neural Dynamics has developed a form of biologically based neural network (the dynamic synapse neural network, or DSNN), which is used in natural language and general acoustics processing. Both sample sizes and complexity of optimization algorithms suggested that a parallel implementation executed on our high-performance cluster would allow our researchers to experiment with improved optimization techniques and perform more computationally intensive experiments. We surveyed the software engineering practices utilized in the development of the parallel DSNN, including product line architecture and object orientation. Additionally, due to the lack of parallel programming experience of our researchers, we developed PS.LINDA, an architecturally aware shared-memory middleware in order to assure conformance to this architecture.
  
  D. Woollard, W. Yamada, and T. Berger. Software Engineering for Neural Dynamics: A Case Study. In proceedings of the First International Workshop on Software Engineering for High Performance Computing System Applications, Edinburgh, Scotland, May, 2004.