Paul Iglinski

User Interface Reverse Engineering in Support of Interface Migration to the Web

Legacy systems constitute valuable assets to the organizations that own them, and today, there is an increased demand to make them accessible through the World Wide Web to support e-commerce activities. As a result, the problem of legacy-interface migration is becoming very important. In the context of the CELLEST project, we have developed a new process for migrating legacy user interfaces to web-accessible platforms. Instead of analyzing the application code to extract a model of its structure, the CELLEST process analyzes traces of the system-user interaction to model the behavior of the applications user interface. The produced state-transition model specifies the unique legacy-interface screens (as states) and the possible commands leading from one screen to another (as transitions between the states). The interface screens are identified as clusters of similar-in-appearance snapshots in the recorded trace. Next, the syntax of each transition command is extracted as the pattern shared by all the transition instances found in the trace. This user-interface model is used as the basis for constructing models of the tasks performed by the legacy-application users; these task models are subsequently used to develop new web-accessible interface front ends for executing these tasks. In this paper, we discuss the CELLEST method for reverse engineering a state-transition model of the legacy interface, we illustrate it with examples, we discuss the results of our experimentation with it, and we discuss how this model can be used to support the development of new interface front ends.

An object-oriented SGML/HyTime compliant multimedia database management system

We describe the design of an object-oriented multimedia database management system that can store and manage SGML/HyTime compliant multimedia documents. The system is capable of storing, within one database, different types o f documents by accommodating multiple document type definitions (DTDs). This is accomplished by dynamically creating object types according to element definitions in each DTD. The system also has tools to automatically insert markedup documents into the database. We discuss the system architecture, design issues and the system features.

Prediction of protein folding rates from primary sequences using hybrid sequence representation

The ability to predict protein folding rates constitutes an important step in understanding the overall folding mechanisms. Although many of the prediction methods are structure based, successful predictions can also be obtained from the sequence. We developed a novel method called prediction of protein folding rates (PPFR), for the prediction of protein folding rates from protein sequences. PPFR implements a linear regression model for each of the mainstream folding dynamics including two‐, multi‐, and mixed‐state proteins. The proposed method provides predictions characterized by strong correlations with the experimental folding rates, which equal 0.87 for the two‐ and multistate proteins and 0.82 for the mixed‐state proteins, when evaluated with out‐of‐sample jackknife test. Based on in‐sample and out‐of‐sample tests, the PPFRs predictions are shown to be better than most of other sequence only and structure‐based predictors and complementary to the predictions of the most recent sequence‐based QRSM method. We show that simultaneous incorporation of several characteristics, including the sequence, physiochemical properties of residues, and predicted secondary structure provides improved quality. This hybridized prediction model was analyzed to reveal the complementary factors that can be used in tandem to predict folding rates. We show that bigger proteins require more time for folding, higher helical and coil content and the presence of Phe, Asn, and Gln may accelerate the folding process, the inclusion of Ile, Val, Thr, and Ser may slow down the folding process, and for the two‐state proteins increased β‐strand content may decelerate the folding process. Finally, PPFR provides strong correlation when predicting sequences with low similarity.

Modeling the system-user dialog using interaction traces

It is generally the case that some user interface (UI) reverse engineering is needed for every non-trivial reengineering project. Typically, this is done through code analysis, which can be very difficult and/or expensive. When code analysis is not a must, as for wrapping purposes, system-user interaction can be an alternative input for the reverse engineering process. In the CelLEST project, we have developed a prototype, called LeNDI (Legacy Navigation Domain Identifier), to test this idea. LeNDI records traces of the legacy screen snapshots and user actions, while the user interacts with the legacy system. Then, it extracts a set of features for every snapshot and employs artificial intelligence methods to build a model of the legacy UI, called the state-transition graph. LeNDI uses two clustering methods to group similar snapshots together as one system screen modeled by one node on the graph. LeNDI uses the user actions recorded in traces to model the behavior of the legacy screens as the graph arcs. Evaluation results of this process are encouraging. The state-transition graph is used to classify each individual snapshot forwarded by the legacy system to the user while he interacts with it and is a main input to the forward engineering phase of the project.

VisualMOQL: the DISIMA visual query language

Multimedia data are now available to a variety of users ranging from naive to sophisticated. To make querying easy, visual query languages have been proposed. Most of these languages have a low expressive power and have their own query processors. Efforts have been made to design query languages with proper semantics to facilitate query optimization and processing in existing database systems. The majority of multimedia database systems are built on top of object or object-relational database systems with the underlying query facilities inherited. The DISIMA system is being built on top of a commercial OODBMS and we have chosen to extend the standard object oriented query language OQL with some multimedia functionalities. The resulting language is called MOQL. This paper presents VisualMOQL, a visual query language implementing the image component of MOQL.

Enabling technology for distributed multimedia applications

In September 1993, the Canadian Institute for Telecommunications Research, in collaboration with the IBM Toronto Laboratory Centre for Advanced Studies, initiated a major project on broadband services. The goal of this major project is to provide the software technologies required for the development of distributed multimedia applications. Of particular interest are “presentational“ applications where multimedia documents, stored in database servers, are retrieved by remote users over a broadband network. Emphasis is placed on efficiency and service flexibility. By efficiency, we mean the ability to support many users and many multimedia documents. By service flexibility, we mean that the application is able to support a wide range of quality-of-service requirements from the users, adapt to changing network conditions, and support multiple document types. The research program consists of six constituent projects: multimedia data management, continuous media file server, quality-of-service negotiation and adaptation, scalable video encoding, synchronization of multimedia data, and project integration. These projects are investigated by a multidisciplinary team from eight institutions across Canada. Multimedia news has been selected as a target application for development, and the results from the various projects have been integrated into a multimedia news prototype. In this paper, the system architecture, research results, and the prototyping effort are presented.

DISIMA: an object-oriented approach to developing an image database system

Most image database prototypes and products focus mainly on similarity searches over syntactic features of images. DISIMA aims at providing querying on both syntactic and semantic features of images. The content of an image is viewed as a set of salient objects (regions of interest). Salient objects are organized into two levels: physical salient objects that store syntactic features and logical salient objects that give the semantics. DISIMA integrates a declarative query language (MOQL) and a visual query language (VisualMOQL).

DISIMA: a distributed and interoperable image database system

DISIMA (Distributed Image Database Management System) is a research project under development at the University of Alberta. DISIMA implements a database approach to developing an image database system. Image contents are modeled using objectoriented paradigms while a declarative query language and a corresponding visual query language allow queries over syntactic and semantic features of images. The distributed and interoperable architecture is designed using common facilities as defined in the Object Management Architecture (OMA).

Similarity queries in the DISIMA image DBMS

In the DISIMA system, an image is composed of salient objects that are regions of interest in the image. A salient object has some syntactic properties (shape, color, textures) on which some similarity searches are defined. In addition, a global multi-precision image similarity based on multi-scale color histograms allows similarity queries on images and sub-images.

Foundation of the DISIMA Image Query Languages

Because digital images are not meaningful by themselves, images are often coupled with some descriptive or qualitative data in an image database. These data, divided into syntactic (color, shape, and texture) and semantic (meaningful real word object or concept) features, necessitate novel querying techniques. Most image systems and prototypes have focussed on similarity searches based upon the syntactic features. In the DISIMA system, we proposed an object-oriented image data model that introduces two main types: image (that represents an image and its descriptive properties) and salient object (that represents the semantics of an image). We further defined operations on the images and the salient objects as new joins. This approach is necessary in order to envision a declarative query language for images. This paper summarizes the querying facilities implemented for the DISIMA system and gives their theoretical foundation: the data model and the complementary algebraic operations, the textual query language (MOQL) and its visual counterpart (VisualMOQL) based on an image calculus. Both languages are declarative and allow the combination of semantic and similarity queries.