Active Research Projects


The Panini project is developing the capsule-oriented programming model. This model is aimed at making concurrent software development easier by providing two properties: (1) given a module it ought to be possible to statically, and modularly identify all points in its code where other modules might interfere (interference points), and (2) given a module and the interfaces of other modules, that the subject module interacts with, it ought to be possible to statically and modularly construct an upper bound on the behavior of all potentially interferring tasks at each interference point. We show that if a programming model has these two properties, then it is possible to modularly reason about concurrent programs in that model. By the first property, humans and tools can identify points where interference from other concurrent tasks must be considered. By the second property, the computed upper bound can be used for reasoning instead of needing the implementation of interferring modules. Compared to alternatives, where reasoning either becomes a global process or entails a global step, modular reasoning afforded by this programming model makes both manual and automated reasoning about concurrent software more scalable.

Following research papers document progress on this project:

We have created two software systems that support this programming model so far:

  • an extension of Java (and the reference compiler javac) that we call PaniniJ, and
  • an annotation-based framework that uses annotation processing facilities, instead of syntax extensions, that we call @PaniniJ.

PI Rajan and students on the Panini project thank the US National Science Foundation for supporting our work under following grants:

More information about the Panini project


Boa project is applying big data analytics toward improving software engineering. It is developing a domain-specific language and its infrastructure whose goal is to significantly ease the experimental cost of mining ultra-large-scale open source repositories. Boa is a research infrastructure that consists of a domain-specific language, its compiler and data updating tools, terabytes (and growing) of raw data from open source repositories that contains hundreds of thousands of open source projects, a backend based on map-reduce to effectively analyze this dataset, a compute cluster, and a web-based frontend for writing analysis programs. Following research papers document progress on this project:

Boa project has been supported in part by the following grants.

  • US National Science Foundation, CI-EN: Boa: Enhancing Infrastructure for Studying Software and its Evolution at a Large Scale. PI: Hridesh Rajan and Co-I: Tien Nguyen, Robert Dyer (2015-2018), Total award amount: $1,559,806, Links: ISU and BGSU.

  • US National Science Foundation, SHF: Large:Collaborative Research: Inferring Software Specifications from Open Source Repositories by Leveraging Data and Collective Community Expertise. PI: Hridesh Rajan and Co-I: Robert Dyer, Tien Nguyen, Gary T. Leavens, and Vasant Honavar (2015-2018), Total award amount: $1,604,843, Links: ISU, BGSU, UCF, and PSU.

  • US National Science Foundation, EAGER: Boa: A Community Research Infrastructure for Mining Software Repositories. PI: Hridesh Rajan and Co-I: Tien Nguyen (2013-2015).

More information about the Boa project.


A software is created to satisfy user needs (also called concerns). These concerns may change often and unanticipatedly. On a concern change, the parts of the software called modules, responsible for that concern must also be revised. A module revision incurs costs and may introduce new errors. It is thus desirable to minimize module revisions. Some concerns, called crosscutting concerns e.g. security, fault tolerance, accountability, etc; have systemic effect. If many modules are responsible for such a concern, a change in it could trigger costly and error-prone systemic module revisions. Advanced separation of concerns mechanisms help avert these systemic revisions.

Ptolemy project is designing an event-based language whose goal is to enable more modular reasoning about advanced separation of concerns mechanisms such as implicit invocation and aspects. Ptolemy provides quantified-typed events that act as an interface between modules. A key benefit of quantified-typed events is that they allow programmers to write new kinds of contracts that we call translucid contracts, which enables modular reasoning about modules that announce events and those that listen to events.

Following research papers document progress on this project:

Ptolemy project has been supported in part by the following grant.

US National Science Foundation, SHF:Small:Balancing Expressiveness and Modular Reasoning for Aspect-oriented Programming. PI: Hridesh Rajan (2010 - 2013).

More information about the Ptolemy project.

Past Research Projects


Eos is a unified aspect-oriented extension for C# on Microsoft® .NET Framework™. Eos unifies aspects and objects as classpects. The unified language model improves the conceptual integrity of the language design and the compositionality of aspect modules to better support hierarchical advising structures.


The Frances project produces tools for teaching topics related to code generation and mapping high-level languages to low-level langages. First, Frances is designed to help teach code generation and assembly language. Second, Frances-A is designed to help teach computer architecture, assembly language, and how high-level code actually executes on a system.


The Nu (pronounced new) project is exploring intermediate language design and corresponding virtual machine extensions to better support new features of aspect-oriented languages. The potential impacts of this project include better compatibility with the existing tool chain, better run-time performance, cross AO language compatibility, improved pointcut expressivity, efficient run-time weaving support, etc.


As multi-core processors are becoming common, vendors are starting to explore trade offs between the die size and the number of cores on a die, leading to heterogeneity among cores on a single chip. For efficient utilization of these processors, application threads must be assigned to cores such that the resource needs of a thread closely matches resource availability at the assigned core. Current methods of thread-to-core assignment often require an application’s execution trace to determine it’s runtime properties. These traces are obtained by running the application on some representative input. A problem is that developing these representative input sets is time consuming, and requires expertise that the user of a general-purpose processor may not have. In this project, we are designing, implementing and evaluating automatic thread-to-core assignment techniques for heterogeneous multi-core processors that will enhance the utilization of these processors.


The Slede project is looking at specification language design and supporting verification mechanisms for specifying and verifying cryptographic protocols for sensor networks. Applications of sensor networks are numerous from military to environmental research. By providing mechanisms to find cryptographic errors in the security protocols for sensor networks this research program is improving the reliability of these networks, making a direct impact on all areas where these networks are utilized.


The key notion in service-oriented architecture is decoupling clients and providers of a service based on an abstract service description, which is used by the service broker to point clients to a suitable service implementation. A client then sends service requests directly to the service implementation. A problem with the current architecture is that it does not provide trustworthy means for clients to specify, service brokers to verify, and service implementations to prove that certain desired non-functional properties are satisfied during service request processing. An example of such non-functional property is access and persistence restrictions on the data received as part of the service requests. In this project, we are developing an extension of the service-oriented architecture that provides these facilities. We are also developing a prototype implementation of this architecture that demonstrate the potential practical value of the proposed architecture in real-world software applications.


Comprehending software is hard. As system complexity and size increases, existing approaches for program comprehension become less usable. Ironically, the need for these approaches increases with the size of the system. In the Osiris project, we are looking at approaches and tools for automatic/semi-automatic generation of concerns models from source code for better comprehension of large software systems.