Srini Ramaswamy

Mining CVS Repositories to Understand Open-Source Project Developer Roles

This paper presents a model to represent the interactions of distributed open-source software developers and utilizes data mining techniques to derive developer roles. The model is then applied on case studies of two open-source projects, ORAC-DR and Mediawiki with encouraging results.

A Complete Multiagent Framework for Robust and Adaptable Dynamic Job Shop Scheduling

This paper presents a complete multiagent framework for dynamic job shop scheduling, with an emphasis on robustness and adaptability. It provides both a theoretical basis and some experimental justifications for such a framework: a job dispatching procedure for a completely reactive scheduling approach, combining real-time and predictive decision making. It resolves various disruptions as flexibly as dispatching rules while providing more stability. It is ready to be implemented in a distributed environment where agents have minimum global information thereby improving system fault tolerance. Computational experiments on dynamic job arrivals provide the experimental justification of the framework. First, a comparison of computational results on unpredictable job arrivals among the presented framework and commonly used dispatching rules is presented to show the effectiveness and robustness of the developed framework. Then, a comparison of the computational results among four cases of dynamic job arrivals is presented to demonstrate the effects of making full use of available uncertain information about disruptions using this framework for the enhancement of scheduling robustness.

Symbiosis and Software Evolvability

As software systems become more pervasive and complex and - at the same time - expensive and difficult to maintain, the R&D community has turned to biological systems to find mechanisms that support system integrity and robustness. In both biology and software development, evolvability has become a research area in its own right. To improve software evolvability, many researchers have studied biological system properties, such as self-organization, modularity, and gene duplication. Our research focuses instead on software ecosystems and symbiosis as a business strategy for multivendor software systems.

Software Evolvability: An Ecosystem Point of View

Software systems need to evolve to adapt to either a new environment or a new requirement. This position paper discusses the evolution of a software system from the viewpoint of an ecosystem and asserts that the evolution of a software system is not a standalone process but an aggregate process of other related software systems that forms a software ecosystem. This paper describes several of our ongoing projects in studying different types of symbiotic relationships between software systems and their effects on software evolution.

Multiple-parameter coupling metrics for layered component-based software

Coupling represents the degree of interdependence between two software components. Understanding software dependency is directly related to improving software understandability, maintainability, and reusability. In this paper, we analyze the difference between component coupling and component dependency, introduce a two-parameter component coupling metric and a three-parameter component dependency metric. An important parameter in both these metrics is coupling distance, which represents the relevance of two coupled components. These metrics are applicable to layered component-based software. These metrics can be used to represent the dependencies induced by all types of software coupling. We show how to determine coupling and dependency of all scales of software components using these metrics. These metrics are then applied to Apache HTTP, an open-source web server. The study shows that coupling distance is related to the number of modifications of a component, which is an important indicator of component fault rate, stability and subsequently, component complexity.

Efficient incident handling in industrial automation through collaborative engineering

We present our monitoring and decision framework for collaborative engineering for globally distributed operation, support, maintenance, and services for industrial automation. The framework provides relevant information to plant operators, engineers, staff and stakeholders to support the handling of incidents, based on semantically-appropriate factors such as personnel skills, physical location of affected equipment and dependencies between plant elements. We discuss the proposed application and present the architecture and implementation. Based on incoming events the framework selects, aggregates and displays information automatically for human processing possibly at distant control centres. For example an alarm in a manufacturing facility can trigger the display of relevant information on multiple devices such as workstations, tablets, or large control-room screens to supervisors and experts. Devices can be potentially in different locations and can comprise different visualization capabilities. The core of our framework uses semantic models and formal methods-based techniques to aggregate and process this information.

Collaborative engineering through integration of architectural, social and spatial models

We present work towards using ontological information to facilitate collaborative tasks during operation, maintenance and service of industrial automation facilities. We use semantic models as an additional layer for a collaboration framework to enable automatic reasoning, decision support and knowledge sharing among multiple parties. Documents such as texts, workflows, images, social media profiles or models of production plants can be semantically annotated to facilitate their ontological classification. Our semantic models comprise behavior and space information, as well as links between documents and from documents to external data collections, such as logs, tables and sensor data. Our semantic models can be used to check consistency, confidentiality and security properties and to support collaborative tasks.

Adaptive LQR controller for Networked Control Systems subjected to random communication delays

Control loops integrated with communication channels for information exchange among system components are called Networked Control Systems (NCSs). Introduction of communication channels induce time-varying communication delays and make the controller design complex. In this paper, an adaptive regulator (AR) that varies its gain depending on the delays in the channel is proposed. The construction of AR is based on the LQR approach. Computation of gains in AR is simplified using the first order approximation that reduces computation delays significantly thereby making the adaptation rule more suitable for higher order systems. The results are illustrated using studies conducted on Modbus over TCP/IP (Transmission Control Protocol/Internet Protocol) communication protocol and a simulation example.

Local and Global Recency Weighting Approach to Bug Prediction

Finding and fixing software bugs is a challenging maintenance task, and a significant amount of effort is invested by software development companies on this issue. In this paper, we use the Eclipse projects recorded software bug history to predict occurrence of future bugs. The history contains information on when bugs have been reported and subsequently fixed.

Categorization of common coupling in kernel based software

Common coupling is an important factor that needs to be considered in software design. It affects software dependency via the definition-use relationship of global variables. Common coupling can arise in all types of software; here we focus on issues specific to kernel-based software. In a previous paper, we described a categorization of common coupling and used it to study the maintainability of the Linux operating system. In this paper, we present a detailed description of this categorization, prove its completeness, and suggest further applications. We hope that, by this approach, we can make it easier for others to use our categorization to measure the maintainability of other kernel-based software.