Linda M. Wills

Automated Program Recognition

Abstract The recognition of familiar computational structures in a program can help an experienced programmer to understand a program. Automating this recognition process will facilitate many tasks that require program understanding, e.g., maintenance, translation, and debugging. This paper describes a prototype recognition system which demonstrates the feasibility of automating program recognition. The prototype system automatically identifies occurrences of stereotyped algorithmic fragments and data structures, called cliches, in programs. It does so even though the cliches may be expressed in a wide range of syntactic forms and may be in the midst of unfamiliar code. Based on the known behaviors of these cliches and the relationships between them, the system generates a hierarchical description of a plausible design of the program. It does this systematically and exhaustively, using a parsing technique. This work is built on two previous advances: a graphical, programming-language-independent representation for programs, called the Plan Calculus, and an efficient graph parsing algorithm.

Software technology for implementing reusable, distributed control systems

A tutorial overview of software innovations for implementing, and facilitating the reuse of, complex control systems. The article focuses on distributed control with multiple processors.

Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance

Automated video surveillance applications require accurate separation of foreground and background image content. Cost sensitive embedded platforms place realtime performance and efficiency demands on techniques to accomplish this task. In this paper we evaluate pixel-level foreground extraction techniques for a low cost integrated surveillance system. We introduce a new adaptive technique, multimodal mean (MM), which balances accuracy, performance, and efficiency to meet embedded system requirements. Our evaluation compares several pixel-level foreground extraction techniques in terms of their computation and storage requirements, and functional accuracy for three representative video sequences. The proposed MM algorithm delivers comparable accuracy of the best alternative (Mixture of Gaussians) with a 6X improvement in execution time and an 18% reduction in required storage.

Powers of observation in creative design

Abstract Being perceptive is a trait highly valued in scientific and engineering professions. What a scientist or engineer notices while considering a problem, evaluating alternatives, or interpreting data has a profound impact on how a problem is viewed and solved. This paper focuses on processes we believe underlie being perceptive: firstly, preparation—becoming attuned to salient or important features; secondly, assimilation-detection and exploration of patterns (invariants) as well as anomalies; and thirdly, strategic control-heuristic strategies for exploring the implications of what has been observed. These processes play an integral role in characteristic activities within creative design, including problem reformulation, the emergence of properties and constraints on the solution, and the ability to incorporate into the design experimental feedback from the environment and from experiences with prototypes and previous designs. The paper presents a computational model incorporating these ideas, implemented in a system called IMPROVISER.

Transition management for reconfigurable hybrid control systems

This article presents a framework for managing transitions between discrete states in hybrid control systems. Based on a study of how hybrid controls are designed and implemented, the authors have identified generic software patterns that are customizable yet can transparently handle common needs for component integration and reconfiguration.

An open control platform for reconfigurable, distributed, hierarchical control systems

Complex control systems for autonomous vehicles require integrating new control algorithms with a variety of different component technologies and resources. These components are often supported on different types of hardware platforms and operating systems and often must interact in a distributed environment (e.g., in communication with a groundstation, mothership, or other UAVs in a swarm). At the same time, the configuration and integration of components must be flexible enough to allow rapid online reconfiguration and adaptation to react to environmental changes and respond to unpredictable events during flight, such as avoiding a moving obstacle or recovering from vehicle equipment failures. This paper describes an open software architecture, called the open control platform, for integrating control technologies and resources. The specific driving application is supporting autonomous control of VTOL uninhabited autonomous vehicles.

On the knowledge required to understand a program

This paper is concerned with the units of knowledge used in understanding programs. A pilot study was conducted wherein a short, but complex, program was examined looking for knowledge atoms, the units from which program understanding is built. The resulting atoms were categorized along three orthogonal axes of knowledge type, design decision used, and the type of analysis required to uncover the atom. The results are discussed relative to several approaches to program understanding taken from the research literature.

Time-Varying and Multiresolution Envelope Analysis and Discriminative Feature Analysis for Bearing Fault Diagnosis

This paper presents a reliable fault diagnosis methodology for various single and multiple combined defects of low-speed rolling element bearings. This method temporally partitions an acoustic emission (AE) signal and selects a portion of the signal, which contains intrinsic information about the bearing failures. This paper then performs frequency analysis for the selected time-domain AE signal by using multilevel finite-impulse response filter banks to obtain the most informative subband signals involving abnormal symptoms of the bearing defects. It does this by using a 2-D visualization tool that represents the percentage of the Gaussian-mixture-model-based residual component-to-defect component ratios via time-varying and multiresolution envelope analysis (TVMREA). Then, fault signatures in the time and frequency domains are extracted in the informative subband signals. Since all the extracted fault features may not be equally useful for diagnosis, the proposed genetic algorithm (GA)-based discriminative feature analysis (GADFA) selects the most discriminative subset of fault signatures. In experiments, single and multiple combined bearing defects under various conditions are used to validate the effectiveness of this fault diagnosis scheme using TVMREA and GADFA. Experimental results indicate that this reliable fault diagnosis methodology accurately identifies bearing failure type across a variety of conditions. In addition, GADFA outperforms other state-of-the-art feature analysis techniques, yielding 7.3%-46.6% performance improvements in average classification accuracy.

MORALE. Mission ORiented Architectural Legacy Evolution

Software evolution is the most costly and time-consuming software development activity, yet software engineering research is predominantly concerned with initial development. MORALE is a development method specifically designed for evolving software. It features an inquiry-based approach to eliciting change requirements, a reverse engineering technique for extracting architectural information from existing code, an approach to impact assessment that determines the extent to which the existing systems architectural components can be reused in the evolved version, a reflective approach to actually perform the evolution, and a specific technique for dealing with the difficulties that arise when evolving user interfaces. MORALE is described in the context of making a specific change to an existing system: adding user-configurable viewers to Version 2.4 of the Mosaic Web browser. Issues that arise are discussed, and the Esprit de Corps tool-suite is described

An open software infrastructure for reconfigurable control systems

Recent advances in software technology have the potential to revolutionize control system design. This paper describes a new software infrastructure for complex control systems, which exploits new and emerging software technologies. It presents an open control platform (OCP) for complex systems, including those that must be reconfigured or customized in real-time for extreme-performance applications. An application of the OCP to the control system design of an autonomous aerial vehicle is described.