In this lab, we consider human aspects in software engineering from different perspectives. We develop tools and techniques focusing on improving the usability of a software system. We help developers with frameworks, APIs and techniques so that they can build usable software systems. We also research on improving developers productivity while working on a legacy system. Research topics that we highlight in this lab software architecture design and evaluation for supporting various non-functional quality attributes (such as ease of use, collaboration, and provenance), software comprehension at architectural level, software analytics, big data analysis and visualization. We combine techniques from software engineering and HCI in our research methodology.

Current projects

VizSciFlow: A visually guided script-based framework for supporting composition of complex scientific workflows with minimal cognitive load and concisely but precisely. Project details.

Hossain MM, Roy B, Roy C, Schneider K. (2020). VizSciFlow: A Visually Guided Scripting Framework for Supporting Complex Scientific Data Analysis. Journal Proceedings of the ACM on Human-Computer Interaction (EICS 2020). 34 pages. Accepted (Journal).

SciWorCS: A cloud-based framework for supporting real-time collaboration in scientific workflow management system. Project details.

Mostaeen G, Roy B, Roy C, Schneider K. (2019). Designing for Real-Time Groupware Systems to Support Complex Scientific Data Analysis. Journal Proceedings of the ACM on Human-Computer Interaction. 3(EICS): 9:1–9:28. (Journal). 

RISP: Recommending Intermediate States for Pipelines/Workflows. We are developing a data management scheme that will allow us handle intermediate states intelligently or optimally. This scheme will make sure whether intermediate states should be reused by a workflow or regenerated during the execution time. Project details.

Debasish Chakroborti, Manishankar Mondal, Banani Roy, Chanchal K. Roy, Kevin A. Schneider:
Optimized Storing of Workflow
Outputs through Mining Association Rules. BigData 2018: 508-515. 

Software Reference Architecture and Platform for Hydrological Modelling and software co-evolution: Core computing team of GWF project had been working on migrating CRHM Borland to a modern platform. CRHM is a state-of the-art legacy software tool in North America for generating hydrological cycles which differ both naturally and operationally depending on geographical locations, environmental variabilities or parameters throughout the world. Canada’s hydrology produces one of the most complex cycles known to us. CHRM is designed keeping this variability in mind. Migration became essential for the system as the Borland C++ compiler is getting outdated.  We have been working on producing the next generation CRHM. We have adopted different migration strategies, including separate code between Core and GUI components, develop a console version of CRHM 2018 that runs in a standard C++ environment, and create APIs to access CRHM core data structures, remove Borland dependencies and minimize MFC dependency. We have partially migrated CRHM where different functionalities are working (such as opening, and viewing projects, constructing a new project and macro functionality for combining and changing existing projects). We are also working on developing an automated testing framework to make sure CRHM is working as expected which includes unit testing, system testing and user acceptance testing. Project details.


  • Consistency Handling in Collaborative Scientific Workflow: One of the main challenges of scientific collaborative system is consistency management – in the face of conflicting concurrent operations by the collaborators. The existing research works use locking techniques where a collaborator gets exclusive Write access to a part of the workflow to facilitate the consistency management . we o work on efficient locking algorithms that can reduce average waiting time of the collaborators and thus can improve the usability of a collaborative scientific workflow management system.
  • ProvMod-Viz: Workflow provenance is important for workflow behavior analysis, data quality measurement, usage pattern mining, fault detection, monitoring, providing user recommendations, resource management and so on. Data intensive workflow systems are never complete without provenance support. We have been developing a workflow programming model that is based on the Python Programming Language, extendable to a broad range of use cases, adaptable to third party tools and offers automated provenance, easy configuration and provenance querying via data visualizations.
  • Cross Language Software Similarity Detection (CroLSIM): As workflow management systems include software tools across various programming, languages, we are working on developing a tool that can detect similar software applications written in various programming languages.  
  • Meta data handling: We have been working on creating a dictionary based website for describing P2IRC-metadata.