by Chi-keung Luk. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 169-174). / Preface --- p.xi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Programming Languages --- p.2 / Chapter 1.2 --- Programming Paradigms --- p.2 / Chapter 1.2.1 --- What is a programming paradigm --- p.2 / Chapter 1.2.2 --- Which came first? Languages or paradigms? --- p.2 / Chapter 1.2.3 --- Overview of some paradigms --- p.4 / Chapter 1.2.4 --- A spectrum of paradigms --- p.6 / Chapter 1.2.5 --- Mulitparadigm systems --- p.7 / Chapter 1.3 --- The Objectives of this research --- p.8 / Chapter 2 --- "Studies of the object-oriented, the logic and the functional paradigms" --- p.10 / Chapter 2.1 --- The Object-Oriented Paradigm --- p.10 / Chapter 2.1.1 --- Basic components --- p.10 / Chapter 2.1.2 --- Motivations --- p.11 / Chapter 2.1.3 --- Some related issues --- p.12 / Chapter 2.1.4 --- Computational models for object-oriented programming --- p.16 / Chapter 2.2 --- The Functional Paradigm --- p.18 / Chapter 2.2.1 --- Basic concepts --- p.18 / Chapter 2.2.2 --- Lambda calculus --- p.20 / Chapter 2.2.3 --- The characteristics of functional programs --- p.21 / Chapter 2.2.4 --- Practicality of functional programming --- p.25 / Chapter 2.3 --- The Logic Paradigm --- p.28 / Chapter 2.3.1 --- Relations --- p.28 / Chapter 2.3.2 --- Logic programs --- p.29 / Chapter 2.3.3 --- The opportunity for parallelism --- p.30 / Chapter 2.4 --- Summary --- p.31 / Chapter 3 --- A survey of some existing multiparadigm languages --- p.32 / Chapter 3.1 --- Logic + Object-Oriented --- p.33 / Chapter 3.1.1 --- LogiC++ --- p.33 / Chapter 3.1.2 --- Intermission --- p.34 / Chapter 3.1.3 --- Object-Oriented Programming in Prolog (OOPP) --- p.36 / Chapter 3.1.4 --- Communication Prolog Unit (CPU) --- p.37 / Chapter 3.1.5 --- DLP --- p.37 / Chapter 3.1.6 --- Representing Objects in a Logic Programming Language with Scoping Constructs (OLPSC) --- p.39 / Chapter 3.1.7 --- KSL/Logic --- p.40 / Chapter 3.1.8 --- Orient84/K --- p.41 / Chapter 3.1.9 --- Vulcan --- p.42 / Chapter 3.1.10 --- The Bridge approach --- p.43 / Chapter 3.1.11 --- Discussion --- p.44 / Chapter 3.2 --- Functional + Object-Oriented --- p.46 / Chapter 3.2.1 --- PROOF --- p.46 / Chapter 3.2.2 --- A Functional Language with Classes (FLC) --- p.47 / Chapter 3.2.3 --- Common Lisp Object System (CLOS) --- p.49 / Chapter 3.2.4 --- FOOPS --- p.50 / Chapter 3.2.5 --- Discussion --- p.51 / Chapter 3.3 --- Logic + Functional --- p.52 / Chapter 3.3.1 --- HOPE --- p.52 / Chapter 3.3.2 --- FUNLOG --- p.54 / Chapter 3.3.3 --- F* --- p.55 / Chapter 3.3.4 --- LEAF --- p.56 / Chapter 3.3.5 --- Applog --- p.57 / Chapter 3.3.6 --- Discussion --- p.58 / Chapter 3.4 --- Logic + Functional + Object-Oriented --- p.61 / Chapter 3.4.1 --- Paradise --- p.61 / Chapter 3.4.2 --- LIFE --- p.62 / Chapter 3.4.3 --- UNIFORM --- p.63 / Chapter 3.4.4 --- G --- p.64 / Chapter 3.4.5 --- FOOPlog --- p.66 / Chapter 3.4.6 --- Logic and Objects (L&O) --- p.66 / Chapter 3.4.7 --- Discussion --- p.67 / Chapter 4 --- The design of a multiparadigm language I --- p.70 / Chapter 4.1 --- An Object-Oriented Framework --- p.71 / Chapter 4.1.1 --- A hierarchy of classes --- p.71 / Chapter 4.1.2 --- Program structure --- p.71 / Chapter 4.1.3 --- Parametric classes --- p.72 / Chapter 4.1.4 --- Inheritance --- p.73 / Chapter 4.1.5 --- The meanings of classes and methods --- p.75 / Chapter 4.1.6 --- Objects and messages --- p.75 / Chapter 4.2 --- The logic Subclasses --- p.76 / Chapter 4.2.1 --- Syntax --- p.76 / Chapter 4.2.2 --- Distributed inference --- p.76 / Chapter 4.2.3 --- Adding functions and expressions to logic programs --- p.77 / Chapter 4.2.4 --- State modelling --- p.79 / Chapter 4.3 --- The functional Subclasses --- p.80 / Chapter 4.3.1 --- The syntax of functions --- p.80 / Chapter 4.3.2 --- Abstract data types --- p.81 / Chapter 4.3.3 --- Augmented list comprehensions --- p.82 / Chapter 4.4 --- The Semantic Foundation of I Programs --- p.84 / Chapter 4.4.1 --- T1* : Transform functions into Horn clauses --- p.84 / Chapter 4.4.2 --- T2*: Transform object-oriented features into pure logic --- p.85 / Chapter 4.5 --- Exploiting Parallelism in I Programs --- p.89 / Chapter 4.5.1 --- Inter-object parallelism --- p.89 / Chapter 4.5.2 --- Intra-object parallelism --- p.92 / Chapter 4.6 --- Discussion --- p.96 / Chapter 5 --- An implementation of a prototype of I --- p.99 / Chapter 5.1 --- System Overview --- p.99 / Chapter 5.2 --- I-to-Prolog Translation --- p.101 / Chapter 5.2.1 --- Pass 1 - lexical and syntax analysis --- p.101 / Chapter 5.2.2 --- Pass 2 - Class Table Construction and Semantic Checking --- p.101 / Chapter 5.2.3 --- Pass 3 - Determination of Multiple Inheritance Precedence --- p.105 / Chapter 5.2.4 --- Pass 4 - Translation of the directive part --- p.110 / Chapter 5.2.5 --- Pass 5 - Creation of Prolog source code for an I object --- p.110 / Chapter 5.2.6 --- Using expressions in logic methods --- p.112 / Chapter 5.3 --- I-to-LML Translation --- p.114 / Chapter 5.4 --- The Run-time Handler --- p.117 / Chapter 5.4.1 --- Object Management --- p.118 / Chapter 5.4.2 --- Process Management and Message Passing --- p.121 / Chapter 6 --- Some applications written in I --- p.125 / Chapter 6.1 --- Modeling of a State Space Search --- p.125 / Chapter 6.2 --- A Solution to the N-queen Problem --- p.129 / Chapter 6.3 --- Object-Oriented Modeling of a Database --- p.131 / Chapter 6.4 --- A Simple Expert System --- p.133 / Chapter 6.5 --- Summary --- p.138 / Chapter 7 --- Conclusion and future work --- p.139 / Chapter 7.1 --- Conclusion --- p.139 / Chapter 7.2 --- Future Work --- p.141 / Chapter A --- Language manual --- p.146 / Chapter A.1 --- Introduction --- p.146 / Chapter A.2 --- Syntax --- p.146 / Chapter A.2.1 --- The lexical specification --- p.146 / Chapter A.2.2 --- The syntax specification --- p.149 / Chapter A3 --- Classes --- p.152 / Chapter A.4 --- Object Creation and Method Invocation --- p.153 / Chapter A.5 --- The logic Subclasses --- p.155 / Chapter A.6 --- The functional Subclasses --- p.156 / Chapter A.7 --- Types --- p.158 / Chapter A.8 --- Mutable States --- p.158 / Chapter B --- User's guide --- p.160 / Chapter B.1 --- System Calls --- p.160 / Chapter B.2 --- Configuration Parameters --- p.162 / Chapter B.3 --- Errors --- p.163 / Chapter B.4 --- Implementation Limits --- p.164 / Chapter B.5 --- How to install the system --- p.164 / Chapter B.6 --- How to use the system --- p.164 / Chapter B.7 --- How to recompile the system --- p.166 / Chapter B.8 --- Directory arrangement --- p.167 / Chapter C --- List of publications --- p.168 / Bibliography --- p.169

by Kei-Fu Mak. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 103-108). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Flynn's Classification --- p.1 / Chapter 1.2 --- Parallel Computation Approaches --- p.2 / Chapter 1.3 --- Architecture Issues --- p.2 / Chapter 1.4 --- Communications --- p.3 / Chapter 1.5 --- Object Oriented Models --- p.4 / Chapter 1.6 --- Parallel Objects --- p.5 / Chapter 1.7 --- Related Works --- p.6 / Chapter 1.7.1 --- Actor Model --- p.6 / Chapter 1.7.2 --- Nested Object --- p.7 / Chapter 1.7.3 --- Nested Transaction --- p.7 / Chapter 1.7.4 --- C++* --- p.8 / Chapter 1.8 --- Summary --- p.8 / Chapter 2 --- Design Issues --- p.10 / Chapter 2.1 --- Goals --- p.11 / Chapter 2.1.1 --- Parallel Model --- p.11 / Chapter 2.1.2 --- Portability --- p.11 / Chapter 2.1.3 --- Class Extension --- p.12 / Chapter 2.2 --- Arguments --- p.12 / Chapter 2.2.1 --- Single versus Multiple Thread Objects --- p.12 / Chapter 2.2.2 --- Active versus Passive Objects --- p.13 / Chapter 2.2.3 --- Synchronous versus Asynchronous Communications --- p.13 / Chapter 2.2.4 --- Architecture Dependence versus Independence --- p.13 / Chapter 2.3 --- Class Structure --- p.14 / Chapter 2.3.1 --- Kernel Class --- p.14 / Chapter 2.3.2 --- Concurrent Class --- p.15 / Chapter 2.3.3 --- Share Class --- p.15 / Chapter 3 --- Execution Model --- p.17 / Chapter 3.1 --- Parallel Objects --- p.19 / Chapter 3.1.1 --- Initialization Phase --- p.19 / Chapter 3.1.2 --- Communication System --- p.21 / Chapter 3.1.3 --- Phase Transition --- p.22 / Chapter 3.1.4 --- Outstanding Requests --- p.24 / Chapter 3.2 --- Concurrent Object --- p.25 / Chapter 3.2.1 --- Service Methods --- p.26 / Chapter 3.2.2 --- Immutable Methods --- p.26 / Chapter 3.2.3 --- Urgent Methods --- p.27 / Chapter 3.2.4 --- Phase Transitional Methods --- p.28 / Chapter 3.2.5 --- Phase Immutable Methods --- p.29 / Chapter 3.3 --- Share Object --- p.30 / Chapter 3.3.1 --- Concurrency Control --- p.31 / Chapter 3.3.2 --- Ticket System --- p.33 / Chapter 3.4 --- Summary --- p.34 / Chapter 4 --- Kernel and Implementation --- p.37 / Chapter 4.1 --- Kernel Components --- p.37 / Chapter 4.1.1 --- Functionality --- p.38 / Chapter 4.1.2 --- Kernel Structure --- p.42 / Chapter 4.1.3 --- Kernel Interface --- p.43 / Chapter 4.1.4 --- Kernel Composition --- p.44 / Chapter 4.2 --- Implementation Issues --- p.46 / Chapter 4.2.1 --- Precompiler --- p.46 / Chapter 4.2.2 --- Object Manager --- p.49 / Chapter 4.2.3 --- Communication System --- p.51 / Chapter 4.2.4 --- Method Invocation --- p.52 / Chapter 4.2.5 --- Restrictions --- p.55 / Chapter 4.3 --- Summary --- p.55 / Chapter 5 --- Evaluation --- p.58 / Chapter 5.1 --- Case Study I --- p.58 / Chapter 5.2 --- Case Study II --- p.63 / Chapter 5.3 --- Overall Evaluation --- p.66 / Chapter 5.4 --- Summary --- p.70 / Chapter 6 --- Conclusion --- p.72 / Chapter A --- ACCEL Header Files --- p.78 / Chapter A.1 --- OBJID.H --- p.78 / Chapter A.2 --- OBJKERN.H --- p.80 / Chapter A.3 --- OBJCONC.H --- p.83 / Chapter A.4 --- OBJSHARE.H --- p.84 / Chapter B --- Case Studies --- p.87 / Chapter B.1 --- Gaussian Elimination --- p.87 / Chapter B.2 --- One Open End Tube --- p.96 / Bibliography --- p.103

In recent years there has been great interest in implementing object recognition frame work on mobile phones. This has stemmed from the fact the advances in object recognition algorithm and mobile phone capabilities have built a congenial ecosystem. Application developers on mobile platforms are trying to utilize the object recognition technology to build better human computer interfaces. This approach is in the nascent phase and proper application framework is required. In this thesis, we propose a framework to overcome design challenges and provide an evaluation methodology to assess the system performance. We use the emerging Android mobile platform to implement and test the framework. We performed a case study using the proposal and reported the test result. This assessment will help developers make wise decisions about their application design. Furthermore, the Android API developers could use this information to provide better interfaces to the third party developers. The design and evaluation methodology could be extended to other mobile platforms for a wider consumer base. / by Vivek Kumar Tyagi. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

The object-oriented community is paying increasing attention to techniques for object instance encapsulation and alias protection. Formal techniques for modular verification of programs at the level of objects are being developed hand in hand with type systems and static analysis techniques for restricting the structure of runtime object graphs. Ownership type systems have provided a sound basis for such structural restrictions by being able to statically represent an extensible object ownership hierarchy. However, such structural restrictions may potentially have limitations on cases when more flexible reference structures are desired. In this thesis, we present a different encapsulation technique, called Effect Encapsulation, which confines side effects rather than object references. With relaxed restriction on reference structure, it is able to express certain common object-oriented patterns which cannot be expressed in Ownership Types. From this basis, we also describe a model of Object Validity --- a framework for reasoning about object invariants. Such a framework can track the effect and dependency of method calls on object invariants within an ownership-based type system, even in the presence of re-entrant calls. Moreover, we present an access control technique for protecting object instances. Combined with context variance, the resulting type system allows for a more flexible and useful access control policy, hence is capable of expressing more object-oriented patterns.

There are many tools and techniques to help developers debug and test their programs. Dynamic data flow analysis is such a technique. Existing approaches for performing dynamic data flow analysis for object oriented programs have tended to be data focused and procedural in nature. An approach to dynamic data flow analysis that used object oriented principals would provide a more natural solution to analysing object oriented programs. Dynamic data flow analysis approaches consist of two primary aspects; a model of the data flow information, and a method for collecting action information from a running program. The model for data flow analysis presented in this thesis uses a meta-level object oriented approach. To illustrate the application of this meta-level model, a model for the Java programming language is presented. This provides an instantiation of the meta-level model provided. Finally, several methods are presented for collecting action information from Java programs. The meta-level model contains elements to represent both data items and scoping components (i.e. methods, blocks, objects, and classes). At runtime the model is used to create a representation of the executing program that is used to perform dynamic data flow analysis. The structure of the model is created in such a way that locating the appropriate meta-level entity follows the scoping rules of the language. In this way actions that are reported to the meta-model are routed through the model to their corresponding meta-level elements. The Java model presented contains classes that can be used to create the runtime representation of the program under analysis. Events from the program under analysis are then used to update the model. Using this information developers are able to locate where data items are incorrectly used within their programs. Methods for collecting action information from Java programs include source code instrumentation, as used in earlier approaches, and approaches that use Java byte code transformation, and the facilities of the Java Platform Debugger Architecture. While these approaches aimed to achieve a comprehensive analysis, there are several issues that could not be resolved using the approaches covered. Of the approaches presented byte code transformation is the most practical.

Object - oriented ecosystem modelling was introduced in the early of 1990s ( Silvert, 1992 ). From that time on, ecosystem models using object - oriented programming ( OOP ) has earned significant achievements with increasing upgraded information technology. The common purposes of ecosystem modellers are to build a model with flexible structure, which allow continuous modifications on the model content. In last decade, ecosystem modellers have put a large number of efforts to practice the OOP approaches in order to implement a true object - oriented ecosystem model. However, these previous work have not fully take advantage of object - orientation because of misusing more or less this technique. This paper explains the shortcoming of these previous endeavours therewith points out a practical solution that using the methodology of object - oriented software engineering and some relative novel information techniques. A case study SALMO - OO will be presented in this paper to prove Silvert ' s assumption that OOP play an important role on ecosystem modelling approaches. Moreover, the results of SALMO - OO convince that object - oriented ecosystem modelling can be achieved by using object - oriented software engineering associating with a true object - oriented programming language ( Java in this case ). / Thesis (M.Sc.)--School of Earth and Environmental Sciences, 2006.

<p>This thesis describes initial language extensions to the Modelica language to define a more general language called PDEModelica, with built-in support for modeling with partial differential equations (PDEs). Modelica® is a standardized modeling language for objectoriented, equation-based modeling. It also supports component-based modeling where existing components with modified parameters can be combined into new models. The aim of the language presented in this thesis is to maintain the advantages of Modelica and also add partial differential equation support.</p><p>Partial differential equations can be defined using a coefficient-based approach, where a predefined PDE is modified by changing its coefficient values. Language operators to directly express PDEs in the language are also discussed. Furthermore, domain geometry description is handled and language extensions to describe geometries are presented. Boundary conditions, required for a complete PDE problem definition, are also handled.</p><p>A prototype implementation is described as well. The prototype includes a translator written in the relational meta-language, RML, and interfaces to external software such as mesh generators and PDE solvers, which are needed to solve PDE problems. Finally, a few examples modeled with PDEModelica and solved using the prototype are presented.</p> / Report code: LiU-Tek-Lic-2002:63.

One of the commonly used simulation approaches is process orientation. This is based on the use of nodes (or blocks) that perform functions in series. In spite of the compactness and ease of learning that characterize process-based simulation, many languages are somewhat complex, primarily the result of the large number of nodes that users have to deal with and the considerable gulf between a user's abstract notion of the model and the details required to implement it. This paper describes a process-based simulation system that integrates object-oriented programming, visual interactive simulation and graphical model specification. Object-oriented programming techniques and simulation seem to be a natural match. The process classes are represented as network blocks or network nodes, and the process as a network diagram or directed graph. Arcs connect the nodes and specify the next step in the process. Each block type has its own icon. Developing an application model requires selecting a set of nodes, connecting them, and specifying the parameters (such as activity durations and random number streams) of the nodes through dialog boxes or inspection panels. Nodes have been designed to accomplish the major requirements in simulation modeling, including creation and termination of entities, attribute assignment, branching, queues and resources, activity specification and statistics collection and display. Additional system features include: statistics manipulation for steady state results, execution trace utilities, and limited animation capabilities. The system has been implemented for the NeXT programming environment using Objective-C. The NeXT includes an extensive object-oriented user interface library, relatively powerful hardware, and a modern multi-tasking and virtual memory operating system. Objective-C allows object-oriented concepts such as inheritance and subclassing while adding only a few constructs to that of the C language. The system modeling environment developed in this research enhances the applicability and usability of high level modeling tools. The program also provides a platform for further work on the distribution of the modeling process over several cooperating, communicating applications. / Graduation date: 1992

S3 (Softwood Sawmill Simulator) is a sawmill simulation system for modeling the operations of Pacific Northwest softwood lumber mills. S3 consists of three main parts. The first part is the framework for construction of the sawmill layout. The second part focuses on individual machine centers, their process and down times, and their interconnections. The third part consists of databases for raw material and final products. S3 inputs process logic from external data files. All parts are integrated in an object-oriented framework. The system was developed using the object-oriented environment, Actor. All data input and output are through database files in dBASE IV format. S3 can model a sawmill represented by the machine center and connection types defined in S3. The size of the model is controlled by the Actor programming environment. The construction of a sawmill model is demonstrated. / Graduation date: 1993

Science and Technology (S and T) information presents a rich resource, essential for managing research and development (R and D) programs. Management of R and D has long been a labor-intensive process, relying extensively on the accumulated knowledge of experts within the organization. Furthermore, the rapid pace of S and T growth has increased the complexity of R and D management significantly. Fortunately, the parallel growth of information and of analytical tools offers the promise of advanced decision aids to support R and D management more effectively. Information retrieval, data mining and other information-based technologies are receiving increased attention. In this thesis, a framework based on text mining techniques is proposed to discover useful intelligence implicit in large bodies of electronic text sources. This intelligence is a prime requirement for successful R and D management. This research extends the approach called Technology Opportunities Analysis (developed by the Technology Policy and Assessment Center, Georgia Institute of Technology, in conjunction with Search Technology, Inc.) to create the proposed framework. The commercialized software, called VantagePoint, is mainly used to perform basic analyses. In addition to utilizing functions in VantagePoint, this thesis also implements a novel text association rule mining algorithm for gathering related concepts among text data. Two algorithms based on text association rule mining are also implemented. The first algorithm called tree-structured networks is used to capture important aspects of both parent-child (hierarchical structure) and sibling relations (non-hierarchical structure) among related terms. The second algorithm called concept-grouping is used to construct term thesauri for data preprocessing. Finally, the framework is applied to Thai S and T publication abstracts toward the objective of improving R and D management. The results of the study can help support strategic decision-making on the direction of S and T programs in Thailand.