In this paper we analyze how a proposed Swedish Road User Charging (RUC) system for differentiated distance based taxation affects the corporate confidentiality of haulers. Each hauler needs to equip all their vehicles with an On-Board Unit (OBU) that continuously send position readings back to a central server, which then is used to calculate the taxation. The fact that the system gather, process, and store information about where the vehicles travel introduce threats to the haulers’ corporate confidentiality, e.g. if the position data leak to competitors. We describe threats to various parts of the RUC system, together with protective measures. In the end of the paper we discuss the impact on corporate confidentiality if such a RUC system is introduced, e.g. how would the leakage of position data affect transports conveying sensitive goods such as medical drugs or consumer electronics.

In this paper, we discuss various types of spyware programs, their behaviour, how they typically infect computers, and the propagation of new varieties of spyware programs. In two experiments, we investigate the occurrence and impact of spyware programs found in popular P2P applications. Based on the findings from the empirical investigations, we try to lift the perspective to a more general view on spyware deriving from the theory of (virtual) network effects. In a model, we categorize in what ways spyware might decrease the utility of belonging to a large virtual network. Here, the baseline is that spyware programs intrude systems and networks, but since they profit from user data they also intrude user privacy. In the model, the intrusions are classified as moderate, severe or disastrous. We found that spyware has the potential to overthrow the positive aspects of belonging to a large network, and network owners should therefore be very careful about permitting such programs in applications and on networks.

Privacy-invasive software, loosely labeled spyware, is an increasingly common problem for today’s computer users, one to which there is no absolute cure. Most of the privacy-invasive software are positioned in a legal gray zone, as the user accepts the malicious behaviour when agreeing to the End User License Agreement. This paper proposes the use of a specialized reputation system to gather and share information regarding software behaviour between community users. A client application helps guide the user at the point of executing software on the local computer, displaying other users’ feedback about the expected behaviour of the software. We discuss important aspects to consider when constructing such a system, and propose possible solutions. Based on the observations made, we implemented a client/server based proof-of-concept tool, which allowed us to demonstrate how such a system would work. We also compare this solution to other, more conventional, protection methods such as anti-virus and anti-spyware software.

A recent study has shown that more than every fourth person in Sweden feels that they have poor knowledge and control over their energy use, and that four out of ten would like to be more aware and to have better control over their consumption [5]. A solution is to provide the householders with feedback on their energy consumption, for instance, through a smart home automation system [10]. Studies have shown that householders can reduce energy consumption with up to 20% when gaining such feedback [5] [10]. Home automation is a prime example of a smart environment built on various types of cyber-physical systems generating volumes of diverse, heterogeneous, complex, and distributed data from a multitude of applications and sensors. Thereby, home automation is also an example of an Internet of Things (IoT) scenario, where a communication network extends the present Internet by including everyday items and sensors [22]. Home automation is attracting more and more attention from commercial actors, such as, energy suppliers, infrastructure providers, and third party software and hardware vendors [8] [10]. Among the non-commercial stake-holders, there are various governmental institutions, municipalities, as well as, end-users.

The amount of spyware increases rapidly over the Internet and it is usually hard for the average user to know if a software application hosts spyware. This paper investigates the hypothesis that it is possible to detect from the End User License Agreement (EULA) whether its associated software hosts spyware or not. We generated a data set by collecting 100 applications with EULAs and classifying each EULA as either good or bad. An experiment was conducted, in which 15 popular default-configured mining algorithms were applied on the data set. The results show that 13 algorithms are significantly better than random guessing, thus we conclude that the hypothesis can be accepted. Moreover, 2 algorithms also perform significantly better than the current state-of-the-art EULA analysis method. Based on these results, we present a novel tool that can be used to prevent the installation of spyware.

Peer-to-Peer (P2P) tools are used exclusively when their users are connected to the Internet, thus constituting a good foundation for online commercials to help finance further tool development. Although software that displays ads (adware) is very common, activity monitoring or information collecting software that spies on the users (spyware) may be installed together with the P2P tool. This paper will present a method for examining P2P tool installations and present test results from a few of the most common P2P tools. It will also discuss whether these tools, with their bundled software, make any privacy intrusions. Finally, the method itself will be evaluated and suggestions of refinements will be proposed.

Context: Cloud computing is an emerging and growing field in an IT industry. Cost minimization, fast processing, easy accessibility and scalability are found to be the main attracting features of cloud computing. Cloud computing is known to be as robust authentication and enhanced security provider technology and it is increasing its scope in many sensitive areas like health sectors where data privacy and security hold the key position. Some of the issues when applying cloud solution is; trust of the new system, data confidentiality, security, storage and most importantly data sharing between different data centers locating in different geographical locations. Objectives: The aim of this thesis is to explore the limitations and find the opportunities and barriers between cloud computing and e-Health and finally suggest guidelines for adoption of cloud computing in an e-Health based sectors based on associates concerns. In the context of this research work, the authors have studied issues involved in the deployment of cloud computing, associates concerns and factors regarding adoption of cloud computing in e-Health and finally suggestion of future of cloud computing in e-Health. Methods: In order to identify and to get a deeper understanding of those issues, the author performed literature review, conducted interview with health care personnel and cloud computing associates and finally backed up with a web-based survey from the associates of cloud computing and e-Health. Results: Finally after the completion of entire analysis authors purposed suitable deployment model and guidelines for adoption of cloud computing in e-Health. Conclusions: Authors concluded that most people’s concerns can be due to lack of knowledge about cloud computing and the trust of vendor. However, authors also observed that people are facing problems with data security, data integrity and too much dependency to the technology and vendors.

You are walking in the Sweetwater Creek State Park near Atlanta and using the Augmented Reality (AR) Trail Guide, a mobile application designed by Isaac Kulka for the Argon Browser (Figure 1). The application offers two views: a now familiar Google-style map, with points of interest marked on its surface, and an AR view, which shows these points located in space. You see the map view when you hold the screen parallel to the ground; when you turn the phone up to look at the world, you get the AR view with the points of interest floating in space in front of you. This simple gesture of raising the phone changes your relationship to the information. You pass from a fully symbolic form of representation to a form of perceiving symbolic information as part of your visual environment. The AR Trail Guide, developed in the Augmented Environments Lab at Georgia Tech [1], illustrates a new realm in AR design that goes beyond current commercial applications. In this article, we discuss some of these new areas, such as designing for experiences in cultural heritage, personal expression, and entertainment. At the same time, we want to address a larger issue. ACM interactions has often been a place for exploring new paradigms and the relevance for interaction design of unusual approaches from other disciplines. In that spirit, we pose the question: Can the humanistic discipline of media studies play a useful role in interaction design? Media studies looks at the history of media and their relationship to culture, and we will focus here on digital media and their relationship to other media, both present and past. Looking at digital media in a historical context is relevant because of the dynamic relationship between "traditional" media (film, television, radio, print) and their digital remediations. How can media studies be made to contribute to the productive work of interaction design? We believe one answer lies in using the historical understanding gained through media studies to develop a kind of media aesthetics that can guide designers as they explore new forms of digital media such as the mobile augmented reality application described above.

Eight European Workshop on Modelling Autonomous Agents in a Multi-Agent World

Law enforcement agencies regularly collect crime scene information. There exists, however, no detailed, systematic procedure for this. The data collected is affected by the experience or current condition of law enforcement officers. Consequently, the data collected might differ vastly between crime scenes. This is especially problematic when investigating volume crimes. Law enforcement officers regularly do manual comparison on crimes based on the collected data. This is a time-consuming process; especially as the collected crime scene information might not always be comparable. The structuring of data and introduction of automatic comparison systems could benefit the investigation process. This thesis investigates descriptive and predictive models for automatic comparison of crime scene data with the purpose of aiding law enforcement investigations. The thesis first investigates predictive and descriptive methods, with a focus on data structuring, comparison, and evaluation of methods. The knowledge is then applied to the domain of crime scene analysis, with a focus on detecting serial residential burglaries. This thesis introduces a procedure for systematic collection of crime scene information. The thesis also investigates impact and relationship between crime scene characteristics and how to evaluate the descriptive model results. The results suggest that the use of descriptive and predictive models can provide feedback for crime scene analysis that allows a more effective use of law enforcement resources. Using descriptive models based on crime characteristics, including Modus Operandi, allows law enforcement agents to filter cases intelligently. Further, by estimating the link probability between cases, law enforcement agents can focus on cases with higher link likelihood. This would allow a more effective use of law enforcement resources, potentially allowing an increase in clear-up rates.

To identify series of residential burglaries, detecting linked crimes performed by the same constellations of criminals is necessary. Comparison of crime reports today is difficult as crime reports traditionally have been written as unstructured text and often lack a common information-basis. Based on a novel process for collecting structured crime scene information, the present study investigates the use of clustering algorithms to group similar crime reports based on combined crime characteristics from the structured form. Clustering quality is measured using Connectivity and Silhouette index (SI), stability using Jaccard index, and accuracy is measured using Rand index (RI) and a Series Rand index (SRI). The performance of clustering using combined characteristics was compared with spatial characteristic. The results suggest that the combined characteristics perform better or similar to the spatial characteristic. In terms of practical significance, the presented clustering approach is capable of clustering cases using a broader decision basis.

A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. The aim of this work is to investigate to what extent it is possible to use geographic route estimations and behavioral data to detect serial offenders. Experiments were conducted using behavioral data from authentic burglary reports to investigate if it was possible to find crime routes with high similarity. Further, the use of burglary reports from serial offenders to investigate to what extent it was possible to detect serial offender crime routes. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. Sets of crimes with high similarity, but without a known offender would be interesting for law enforcement to investigate further. The algorithm is also evaluated on 9 crime series containing a maximum of 20 crimes per series. The results suggest that it is possible to detect crime series with high similarity using analysis of both geographic routes and behavioral data recorded at crime scenes.

A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. The aim of this work is to investigate to what extent it is possible to use geographic route estimations and behavioral data to detect serial offenders. Experiments were conducted using behavioral data from authentic burglary reports to investigate if it was possible to find crime routes with high similarity. Further, the use of burglary reports from serial offenders to investigate to what extent it was possible to detect serial offender crime routes. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. Sets of crimes with high similarity, but without a known offender would be interesting for law enforcement to investigate further. The algorithm is also evaluated on 9 crime series containing a maximum of 20 crimes per series. The results suggest that it is possible to detect crime series with high similarity using analysis of both geographic routes and behavioral data recorded at crime scenes.

Spyware detection can be achieved by using machinelearning techniques that identify patterns in the End User License Agreements (EULAs) presented by application installers. However, solutions have required manual input from the user with varying degrees of accuracy. We have implemented an automatic prototype for extraction and classification and used it to generate a large data set of EULAs. This data set is used to compare four different machine learning algorithms when classifying EULAs. Furthermore, the effect of feature selection is investigated and for the top two algorithms, we investigate optimizing the performance using parameter tuning. Our conclusion is that feature selection and performance tuning are of limited use in this context, providing limited performance gains. However, both the Bagging and the Random Forest algorithms show promising results, with Bagging reaching an AUC measure of 0.997 and a False Negative Rate of 0.062. This shows the applicability of License Agreement Categorization for realizing informed software installation.

According to the Swedish National Council for Crime Prevention, law enforcement agencies solved approximately three to five percent of the reported residential burglaries in 2012. Internationally, studies suggest that a large proportion of crimes are committed by a minority of offenders. Law enforcement agencies, consequently, are required to detect series of crimes, or linked crimes. Comparison of crime reports today is difficult as no systematic or structured way of reporting crimes exists, and no ability to search multiple crime reports exist. This study presents a systematic data collection method for residential burglaries. A decision support system for comparing and analysing residential burglaries is also presented. The decision support system consists of an advanced search tool and a plugin-based analytical framework. In order to find similar crimes, law enforcement officers have to review a large amount of crimes. The potential use of the cut-clustering algorithm to group crimes to reduce the amount of crimes to review for residential burglary analysis based on characteristics is investigated. The characteristics used are modus operandi, residential characteristics, stolen goods, spatial similarity, or temporal similarity. Clustering quality is measured using the modularity index and accuracy is measured using the rand index. The clustering solution with the best quality performance score were residential characteristics, spatial proximity, and modus operandi, suggesting that the choice of which characteristic to use when grouping crimes can positively affect the end result. The results suggest that a high quality clustering solution performs significantly better than a random guesser. In terms of practical significance, the presented clustering approach is capable of reduce the amounts of cases to review while keeping most connected cases. While the approach might miss some connections, it is also capable of suggesting new connections. The results also suggest that while crime series clustering is feasible, further investigation is needed.

A majority of E-mail is suspected to be spam. Traditional spam detection fails to differentiate between user needs and evolving social relationships. Online Social Networks (OSNs) contain more and more social information, contributed by users. OSN information may be used to improve spam detection. This paper presents a method that can use several social networks for detecting spam and a set of metrics for representing OSN data. The paper investigates the impact of using social network data extracted from an E-mail corpus to improve spam detection. The social data model is compared to traditional spam data models by generating and evaluating classifiers from both model types. The results show that accurate spam detectors can be generated from the low-dimensional social data model alone, however, spam detectors generated from combinations of the traditional and social models were more accurate than the detectors generated from either model in isolation.

Virtual environments where users can interact with each other as well as with the environment are today used in many application areas ranging from military simulations to massive multiplayer online games. But no matter the application area, as soon as the number of users reaches a certain threshold, hosting a virtual environment on a single machine can become problematic. Speed and quality of the network connection will limit the number of concurrently connected users in terms of acceptable visual quality and hardware requirements of the server will be strict. With a single point of failure, system reliability could easily be compromised by means of network or host failure. Distribution of the virtual environment therefore seems a reasonable approach in order to address this problem. Hardware and network requirements would not be so critical and it would increase reliability by having no single point of failure. Unfortunately distribution introduces new problems dealing with synchronization of the world state within the distribution network. A possible solution to these problems with the focus on reliability will be presented in this thesis. The solution uses a peer to peer platform that is able to adapt to changes in the network infrastructure as a base for all communication. To improve synchronization efficiency the network will be dynamically divided into multicast groups based on synchronization needs. The solution will be tested for performance with the network fully functioning and in a number of more of less broken states to determine the reliability. The results from the tests conclude that the system is able to perform with what must be seen as acceptable performance levels even in very problematic network environments. The scalability of the system did also meet the expectations but the results would have benefited from more experimentation with larger user populations.

Utförandet av projektet har varit att implementera två stycken fightingspels Artificiell Intelligens (kommer att förkortas AI). En oadaptiv och mer deterministisk AI och en adaptiv dynamisk AI som använder reinforcement learning. Detta har utförts med att skripta beteendet av AI:n i en gratis 2D fightingsspels motor som heter ”MUGEN”. AI:n använder sig utav skriptade sekvenser som utförs med MUGEN’s egna trigger och state system. Detta system kollar om de skriptade specifierade kraven är uppfyllda för AI:n att ska ”trigga”, utföra den bestämda handlingen. Den mer statiska AI:n har blivit uppbyggd med egen skapade sekvenser och regler som utförs delvis situationsmässigt och delvis slumpmässigt. För att försöka uppnå en reinforcement learning AI så har sekvenserna tilldelats en variabel som procentuellt ökar chansen för utförandet av handlingen när handlingen har givit något positivt och det motsatta minskar när handlingen har orsakat något negativt.

This thesis provides an overview of Web Services technology. The concept of Web Services and Service Oriented Architecture are explained. The thesis focuses on the mechanisms for transporting and addressing messages in web services, especially SOAP. It presents the development history of SOAP, an overview of the SOAP 1.2 specification, and the differences between SOAP in version 1.1 and 1.2. Further, the thesis presents two web servers for development and deployment of web services using Java and .NET technology, i.e. Bea Weblogic Server 9.2 and Internet Information Services 7.0. The web server implementations are evaluated both in terms of conformance to the SOAP specifications as well as their performance (response time and throughput). The results showed that the servers performed very similar both for SOAP 1.2 and SOAP 1.1 messages. The response times and throughput are similar for both servers in most cases. There are, however, situations when Weblogic perform significantly worse than IIS, and when IIS is noticeable worse than Weblogic. The thesis presents also general security aspects of sending messages.

The requirements on real-time systems are changing. Traditionally, reliability and predictability of, especially hard, real-time systems were the main requirements. This lead to systems that were stand-alone, embedded and static. Future real-time systems, but also current systems, still require reliability and predictability, but also distribution of the real-time system, integration with non real-time systems and the ability to dynamically change the components of the system at runtime. Traditional approaches to real-time system development have difficulties in addressing these additional requirements. Therefore, new ways of constructing real-time systems have to be explored. In this article, we develop a real-time object-oriented model that facilitates the requirements of flexibility without sacrificing the predictability, integration and dynamicity aspects.

Measurement systems are of increasing importance for manufacturing, due to high automation level of production processes. Although most measurement systems have much in common and are expensive to construct, these systems are often developed from scratch, hardly reusing the available designs and implementations. To address this, we have designed and implemented an object-oriented framework for the domain of measurement systems that can be used as the core of measurement systems. Evaluations of the framework show that it captures the main concepts in the domain and that the required extensions for individual applications are limited. In this paper, a number of example framework instantiations are presented. The lessons we learned during the framework design and an evaluation of the object-oriented modelling paradigm are presented.

The work done concerning object oriented frameworks is in its beginning and most of it tend to concentrate on object oriented frameworks that has been built and how these were built and documented. But there is one question that remains unsatisfactorily answered, i.e. what is a object oriented framework? This is still one of the most common questions and there still exists no answer that is generally agreed on. In this paper some important characteristics of object oriented frameworks are presented, existing definitions discussed and an improved definition is suggested.

Design patterns have proven to be useful for the design of object-oriented systems. The power of a design pattern lies in its ability to provide generic solutions that can be specialised for particular situations. The implementation of design patterns has received only little attention and we have identified two relevant problems associated with the implementation. First, the traceability of a design pattern in the implementation is often insufficient; often the design pattern is `lost'. Second, implementing design patterns may present significant implementation overhead for the software engineer. Often, a, potentially large, number of simple methods has to be implemented with trivial behaviour, e.g. forwarding a message to another object. In this paper, the layered object model (LayOM) is presented. LayOM provides language support for the explicit representation of design patterns in the programming language. LayOM is an extended object-oriented language in that it contains several components that are not part of the conventional object model, such as states, categories and layers. Layers are used to represent design patterns at the level of the programming language and example layer types for four design patterns are presented. LayOM is supported by a development environment that translates LayOM code into C++. The generated C++ code can be used as any C++ code for the development of applications. An important aspect of LayOM is that the language itself is extensible. This allows new design patterns to be added to the language model.

Large object-oriented systems have, at least, four characteristics that complicate object communication, i.e the system is distributed and contains large numbers, e.g. thousands, of objects, objects need to be reallocated at run-time and objects can be replaced by other objects in order to adapt to the dynamic changes in the system. Traditional object communication is based on sending a message to a receiver object known to the sender of the message. At linking or instantiation time, an object establishes its acquaintances through name/class-based binding and uses these objects through its life time. If this is too rigid, the software engineer has to implement the binding of objects manually using pointers. In our experiments we found the traditional acquaintance communication semantics too limited and we identified several problems, related to the reusability of objects and selection mechanisms, understandability and expressiveness. We recognised that it is important to separate a class or object's requirements on its acquaintances from the way an object selects and binds its acquaintances in actual systems. Based on this observation, we studied the required expressiveness for acquaintance handling and identified four relevant aspects: type and duration of binding, conditions for binding, number of selected objects and selection region for binding. To implement these aspects, we defined acquaintance layers as part of the layered object model. Acquaintance layers uniformly extend the traditional object-oriented acquaintance handling semantics and allow for the first-class representation of acquaintance selection and binding, thereby increasing traceability and reusability.

Reuse of software has been one of the main goals of software engineering for decades. Reusing software is not simple and most efforts resulted in small reusable, black-box components. With the emergence of the object-oriented paradigm, the enabling technology for reuse of larger components became available and resulted in the definition of object-oriented frameworks. Frameworks attracted attention from many researchers and software engineers and frameworks have been defined for a large variety of domains. The claimed advantages of frameworks are, among others, increased reusability and reduced time to market for applications. Although several examples have shown these advantages to exist, there are problems and hindrances associated with frameworks that may not appear before their usage in real projects. The authors have been involved in the design, maintenance and usage of several object-oriented frameworks and based on the experiences from these projects, a number of problems related to frameworks are descr ibed. The problems are organised according to four categories, i.e. framework development, usage, composition and maintenance. For each category, the most relevant problems and experiences are presented. This paper may help software engineers to avoid the described problems, whereas researchers may try to address these topics in their research.

Programming languages and software engineering methods are highly related in that both are images of an underlying paradigm. In this paper we investigate the role of the paradigm, the language model and the software development method and define requirements on each of the three concepts. Subsequently, we describe the {\em layered object model}, an extended object model which allows for first-class representation of relations between objects and constraints on the behaviour of an object, and discuss how it achieves {\em paradigm extensibility}, i.e. extensibility of the paradigm and the supporting language model.

Conventional grammar specification and parsing is generally done in a monolithic manner, i.e. the syntax and semantics of a grammar are specified in one large specification. Although this might be sufficient in static environments, a modular approach is required in situations where the syntax or semantics of a grammar specification are subject to frequent changes. The problems with monolithic grammars are related to (1) dealing with the complexity, (2) extensibility and (3) reusability. We propose the concept of {\em parser delegation} as a solution to these problems. Parser delegation allows one to modularise and reuse grammar specifications. To achieve this, the notion of a production rule is specialised into (1) overriding, (2) extending and (3) delegating production rule types. To experiment with parser delegation, we have developed D-yacc, a graphical tool for defining grammars. Parser delegation has been applied for constructing a translator for an experimental language and is currently applied in other domains.

Although object-oriented methods make extensive use of relations between objects, these relations, other than inheritance and part-of, can not directly be represented by the conventional object-oriented model. This means that relations which are identified during analysis and design have to be implemented on top of the object model, i.e. by using method code and message passing, rather than by expressing relations directly within in the model. It would be beneficial if the object-oriented model would support the specification of all relevant types of relations within the model, including application-domain specific relation types. Therefore, we propose a mechanism, implemented in LayOM -- an extended object model, that supports the specification of all types of relations between objects within the model as components of the object model. In addition, an approach for identifying and specifying application-domain relation types is presented.

The report is the result of a course for PhD students on software architecture. An overview of the state of the art is presented. Discussed topics include describing, evaluating and designing architectures, product-line architectures, object-oriented frameworks and component-based software engineering.

In this paper, a number of problems of conventional automated software engineering support environments are described. These problems are related to the functional approach these environments take, the lack of initiative these systems exhibit and the causal connection gap between design information and the operational entity. As an alternative, we suggest an autonomous agent approach. Each artifact is modelled as an autonomous agent that is responsible for its own development. Artifacts are organised in specialisation hierarchies which can be traversed by agents. As a consequence, the methodology needs to be inverted, i.e. specified from the artifact's perspective rather than from the software engineer's perspective.

Object-oriented software architectures, such as design patterns and frameworks, have Sound extensive use in software industry. Their implementation in traditional object-oriented programming languages, however, is often difficult, since no support for the explicit specification of software architectures is provided. In. this paper, we develop the notion of architectural fragments, i.e. reusable architectural specifications that describe a design pattern, or a framework architecture. An architectural fragment describes the structure of an architecture in terms of its components (roles), the architect architecture-specific behaviour of the components and the architecture-specific interaction between the components. Fragments can be composed with each other and with reusable components. To illustrate the use of fragments, we describe the role and architecture language constructs in the layered object model ((LOM)-O-AY) and present examples.

Object-oriented software architectures, such as design patterns and frameworks, have found extensive use in software industry. As a design technique, these architectural structures have proven themselves very valuable. Their implementation in traditional object-oriented programming languages, however, is often difficult, since these languages provide no support for the explicit specification of software architectures. In this paper, we develop the notion of architectural fragments, i.e. reusable architectural specifications that describe a design pattern or a framework architecture. An architectural fragment describes the structure of an architecture in terms of its components (roles), the architecture-specific behaviour of the components and the architecture-specific interaction between the components. Fragments can be composed with each other and with reusable components. To illustrate the use of fragments, we describe the role and architecture language constructs in the layered object model (LayOM) and present examples.

During the last years, one can recognise a development towards application domain languages and extensible language models. Due to their extended expressiveness, these language models have considerable advantages over rigid general purpose languages. However, a complicating factor in the use of extensible language models are the conventional compiler construction techniques. Compilers constructed using these techniques often are large entities that are highly complex, difficult to maintain and hard to reuse. As we have experienced, these characteristics clearly complicate extending existing compilers. As a solution to this, we developed an alternative approach to compiler construction is proposed, based on object-oriented principles. The approach is based on delegating compiler objects (dcos) that provide a structural decomposition of compilers in addition to the conventional functional decomposition. The dco approach supports modularisation and reuse of compiler specifications, such as lexer and parser speci fications. We constructed an integrated tool set, letos, implementing the functionality of delegating compiler objects.

During the last years, one can recognise a development towards application domain languages and extensible language models. Due to their extended expressiveness, these language models have considerable advantages over rigid general purpose languages. However, a complicating factor in the use of extensible language models are the conventional compiler construction techniques. Compilers constructed using these techniques often are large entities that are highly complex, difficult to maintain and hard to reuse. As we have experienced, these characteristics clearly complicate extending existing compilers. As a solution to this, we developed an alternative approach to compiler construction is proposed, based on object-oriented principles. The approach is based on delegating compiler objects (DCOs) that provide a structural decomposition of compilers in addition to the conventional functional decomposition. The DCO approach supports modularisation and reuse of compiler specifications, such as lexer and parser specifications. We constructed an integrated tool set, LETOS, implementing the functionality of delegating compiler objects.

Software architecture research is receiving increased amounts of attention in academia as well as in industry. Therefore, in 1997 the initiative was taken by the University of Karlskrona/Ronneby to start a network of academic and industrial partners, SARIS, interested in various aspects of software architecture. The intention of the SARIS (Software Architecture Research in Sweden) network is to bring together partners with common interests, exchange experiences through the mailing list and regular meetings and to develop cooperation wherever possible. The term software architecture is somewhat overloaded, but most experts agree that it primarily refers to the top-level decomposition of a system into its main components and the interaction between these components. A second aspect is that software architecture design is primarily concerned with the non-functional requirements (also properties or quality attributes) of software systems, rather than their functionality. Attributes can be categorized into operational attributes, such as efficiency, reliability, robustness and cor-rectness, and development attributes, such as maintainability, flexibility and reusability. The architecture structures the functionality required from a system such that the non-functional requirements are fulfilled.

When modelling complex computer systems, four primary modelling techniques are available to the software engineer, i.e. abstraction, composition, functional decomposition and multiple client interfaces (views). Abstraction and composition can directly be expressed in traditional object-oriented models and functional decomposition can often be expressed using subsystems. However, traditional object models provide no expressiveness for multiple client interfaces. This forces designers to either model all different views on a conceptual object as a large, complex implementation object or to model each view as an object and relate the different view objects. Both approaches suffer from problems of complexity, maintainability and reusability. As a solution, we propose the layered object model that allows for the expressive, flexible and extensible definition of multiple client interfaces. To illustrate the problems associated with views and our proposed solution, the domain of industrial control systems is used.

The requirements on real-time systems are changing. Traditionally, reliability and predictability of hard, real-time systems in particular were the main requirements. This lead to systems that were stand-alone, embedded and static. Future real-time systems, but even current systems, still require reliability and predictability, but also distribution of the real-time system, integration with non real-time systems and the ability to change dynamically the components of the system at run-time. Traditional approaches to real-time system development have difficulty in addressing these additional requirements. New ways of constructing real-time systems must therefore be explored. In this article, we develop a real-time object-oriented model that facilitates the requirements of flexibility without sacrificing the predictability, integration and dynamicity aspects.