Program Comprehension of Aspect-Oriented Programs

The aim of aspect-oriented development has been to address the issue of software reuse outside the domain of established object-oriented techniques within the challenging realm of similar cross-cutting concerns. By decoupling the concerns from the core functionality, aspect-oriented developed software results in a smaller code base and reduced code duplication. This decoupling though presents new challenges to the software development process. The process of separating concerns impacts the developers established engineering inclinations as well as existing, established notations, such as UML, that developers are familiar with utilizing for both designing and understanding the implemented software systems. This thesis will study the impact of aspect-oriented software development on programmers’ ability to comprehend the core system in addition to their comprehension of the aspect implementation

Quality Goal Oriented Architectural Design and Traceability for Evolvable Software Systems

Softwaresysteme werden heute z.B. aufgrund sich ändernder Geschäftsprozesse oder Technologien mit häufigen Veränderungen konfrontiert. Die Software und speziell ihre Architektur muss diese Änderungen zur dauerhaften Nutzbarkeit ermöglichen.Während der Software-Evolution können Änderungen zu einer Verschlechterung der Architektur führen, der Architekturerosion. Dies erschwert oder verhindert weitere Änderungen wegen Inkonsistenz oder fehlendem Programmverstehen. Zur Erosionsvermeidung müssen Qualitätsziele wie Weiterentwickelbarkeit, Performanz oder Usability sowie die Nachvollziehbarkeit von Architekturentwurfsentscheidungen berücksichtigt werden. Dies wird jedoch oft vernachlässigt.Existierende Entwurfsmethoden unterstützen den Übergang von Qualitätzielen zu geeigneten Architekturlösungen nur unzureichend aufgrund einer Lücke zwischen Methoden des Requirements Engineering und des Architekturentwurfs. Insbesondere gilt dies für Weiterentwickelbarkeit und die Nachvollziehbarkeit von Entwurfsentscheidungen durch explizite Modellabhängigkeiten.Diese Arbeit präsentiert ein neues Konzept, genannt Goal Solution Scheme, das Qualitätsziele über Architekturprinzipien auf Lösungsinstrumente durch explizite Abhängigkeiten abbildet. Es hilft somit, Architekturlösungen entsprechend ihrem Einfluss auf Qualitätsziele auszuwählen. Das Schema wird speziell hinsichtlich Weiterentwickelbarkeit diskutiert und ist in ein zielorientiertes Vorgehen eingebettet, das etablierte Methoden und Konzepte des Requirements Engineering und Architekturentwurfs verbessert und integriert. Dies wird ergänzt durch ein Traceability-Konzept, welches einen regelbasierten Ansatz mit Techniken des Information Retrieval verbindet. Dies ermöglicht eine (halb-) automatische Erstellung von Traceability Links mit spezifischen Linktypen und Attributen für eine reichhaltige Semantik sowie mit hoher Genauigkeit und Trefferquote.Die Realisierbarkeit des Ansatzes wird an einer Fallstudie einer Software für mobile Serviceroboter gezeigt. Das Werkzeug EMFTrace wurde als eine erweiterbare Plattform basierend auf Eclipse-Technologie implementiert, um die Anwendbarkeit der Konzepte zu zeigen. Es integriert Entwurfsmodelle von externen CASE-Tools mittels XML-Technologie in einem gemeinsamen Modell-Repository, wendet Regeln zur Linkerstellung an und bietet Validierungsfunktionen für Regeln und Links.Today software systems are frequently faced with demands for changes, for example, due to changing business processes or technologies. The software and especially its architecture has to cope with those frequent changes to permanently remain usable.During software evolution changes can lead to a deterioration of the structure of software architectures called architectural erosion, which hampers or even inhibits further changes because of inconsistencies or lacking program comprehension. To support changes and avoid erosion, especially quality goals, such as evolvability, performance, or usability, and the traceability of design decisions have to be considered during architectural design. This however often is neglected.Existing design methods do not sufficiently support the transition from the quality goals to appropriate architectural solutions because there is still a gap between requirements engineering and architectural design methods. Particularly support is lacking for the goal evolvability and for the traceability of design decisions by explicit model dependencies.This thesis presents a new concept called Goal Solution Scheme, which provides a mapping from goals via architectural principles to solution instruments by explicit dependencies. Thus it helps to select appropriate architectural solutions according to their influence on quality goals. The scheme is discussed especially regarding evolvability, and it is embedded in a goal-oriented architectural design method, which enhances and integrates established methods and concepts from requirements engineering as well as architectural design. This is supplemented by a traceability concept, which combines a rule-based approach with information retrieval techniques for a (semi-) automated establishment of links with specific link types and attributes for rich semantics and a high precision and recall.The feasibility of the design approach has been evaluated in a case study of a software platform for mobile robots. A prototype tool suite called EMFTrace was implemented as an extensible platform based on Eclipse technology to show the practicability of the thesis' concept. It integrates design models from external CASE tools in a joint model repository by means of XML technology, applies rules for link establishment, and provides validation capabilities for rules and links

A Review on Software Performance Analysis for Early Detection of Latent Faults in Design Models

Organizations and society could face major breakdown if IT strategies do not comply with performance requirements. This is more so in the era of globalization and emergence of technologies caused more issues. Software design models might have latent and potential issues that affect performance of software. Often performance is the neglected area in the industry. Identifying performance issues in the design phase can save time, money and effort. Software engineers need to know the performance requirements so as to ensure quality software to be developed. Software performance engineering a quantitative approach for building software systems that can meet performance requirements. There are many design models based on UML, Petri Nets and Product-Forms. These models can be used to derive performance models that make use of LQN, MSC, QNM and so on. The design models are to be mapped to performance models in order to predict performance of system early and render valuable feedback for improving quality of the system. Due to emerging distributed technologies such as EJB, CORBA, DCOM and SOA applications became very complex with collaboration with other software. The component based software systems, software systems that are embedded, distributed likely need more systematic performance models that can leverage the quality of such systems. Towards this end many techniques came into existence. This paper throws light into software performance analysis and its present state-of-the-art. It reviews different design models and performance models that provide valuable insights to make well informed decisions

Preserving the Quality of Architectural Tactics in Source Code

In any complex software system, strong interdependencies exist between requirements and software architecture. Requirements drive architectural choices while also being constrained by the existing architecture and by what is economically feasible. This makes it advisable to concurrently specify the requirements, to devise and compare alternative architectural design solutions, and ultimately to make a series of design decisions in order to satisfy each of the quality concerns. Unfortunately, anecdotal evidence has shown that architectural knowledge tends to be tacit in nature, stored in the heads of people, and lost over time. Therefore, developers often lack comprehensive knowledge of underlying architectural design decisions and inadvertently degrade the quality of the architecture while performing maintenance activities. In practice, this problem can be addressed through preserving the relationships between the requirements, architectural design decisions and their implementations in the source code, and then using this information to keep developers aware of critical architectural aspects of the code. This dissertation presents a novel approach that utilizes machine learning techniques to recover and preserve the relationships between architecturally significant requirements, architectural decisions and their realizations in the implemented code. Our approach for recovering architectural decisions includes the two primary stages of training and classification. In the first stage, the classifier is trained using code snippets of different architectural decisions collected from various software systems. During this phase, the classifier learns the terms that developers typically use to implement each architectural decision. These ``indicator terms\u27\u27 represent method names, variable names, comments, or the development APIs that developers inevitably use to implement various architectural decisions. A probabilistic weight is then computed for each potential indicator term with respect to each type of architectural decision. The weight estimates how strongly an indicator term represents a specific architectural tactics/decisions. For example, a term such as \emph{pulse} is highly representative of the heartbeat tactic but occurs infrequently in the authentication. After learning the indicator terms, the classifier can compute the likelihood that any given source file implements a specific architectural decision. The classifier was evaluated through several different experiments including classical cross-validation over code snippets of 50 open source projects and on the entire source code of a large scale software system. Results showed that classifier can reliably recognize a wide range of architectural decisions. The technique introduced in this dissertation is used to develop the Archie tool suite. Archie is a plug-in for Eclipse and is designed to detect wide range of architectural design decisions in the code and to protect them from potential degradation during maintenance activities. It has several features for performing change impact analysis of architectural concerns at both the code and design level and proactively keep developers informed of underlying architectural decisions during maintenance activities. Archie is at the stage of technology transfer at the US Department of Homeland Security where it is purely used to detect and monitor security choices. Furthermore, this outcome is integrated into the Department of Homeland Security\u27s Software Assurance Market Place (SWAMP) to advance research and development of secure software systems

Comparing Representations of Contribution Labels in Goal Models

Goal models have been proposed to be an effective method to support decision making in early requirements engineering. Key to using them is the concept of contribution links that represent how the satisfaction of one goal affects that of another. Multiple proposals have been offered for representing contribution; however, the degree to which users can intuitively understand the meaning behind contribution representations and utilize them appropriately has not been thoroughly studied. This work reports the results of an experimental study that compares the intuitiveness of two contribution representation approaches by measuring the performance of untrained users and exploring the role of individual differences (cognitive styles and arithmetic attitude and ability) in establishing the right intuition. Results show significant differences between the two representations as well as effects of various levels of individual factors. The results inspire further research on contribution links and support the operationalizability of intuitiveness as a criterion for evaluating conceptual modelling language designs

Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen

Software Product Line

The Software Product Line (SPL) is an emerging methodology for developing software products. Currently, there are two hot issues in the SPL: modelling and the analysis of the SPL. Variability modelling techniques have been developed to assist engineers in dealing with the complications of variability management. The principal goal of modelling variability techniques is to configure a successful software product by managing variability in domain-engineering. In other words, a good method for modelling variability is a prerequisite for a successful SPL. On the other hand, analysis of the SPL aids the extraction of useful information from the SPL and provides a control and planning strategy mechanism for engineers or experts. In addition, the analysis of the SPL provides a clear view for users. Moreover, it ensures the accuracy of the SPL. This book presents new techniques for modelling and new methods for SPL analysis

Evolving Software Systems for Self-Adaptation

There is a strong synergy between the concepts of evolution and adaptation in software engineering: software adaptation refers to both the current software being adapted and to the evolution process that leads to the new adapted software. Evolution changes for the purpose of adaptation are usually made at development or compile time, and are meant to handle predictable situations in the form of software change requests. On the other hand, software may also change and adapt itself based on the changes in its environment. Such adaptive changes are usually dynamic, and are suitable for dealing with unpredictable or temporary changes in the software's operating environment. A promising solution for software adaptation is to develop self-adaptive software systems that can manage changes dynamically at runtime in a rapid and reliable way. One of the main advantages of self-adaptive software is its ability to manage the complexity that stems from highly dynamic and nondeterministic operating environments. If a self-adaptive software system has been engineered and used properly, it can greatly improve the cost-effectiveness of software change through its lifespan. However, in practice, many of the existing approaches towards self-adaptive software are rather expensive and may increase the overall system complexity, as well as subsequent future maintenance costs. This means that in many cases, self-adaptive software is not a good solution, because its development and maintenance costs are not paid off. The situation is even worse in the case of making current (legacy) systems adaptive. There are several factors that have an impact on the cost-effectiveness and usability of self-adaptive software; however the main objective of this thesis is to make a software system adaptive in a cost-effective way, while keeping the target adaptive software generic, usable, and evolvable, so as to support future changes. In order to effectively engineer and use self-adaptive software systems, in this thesis we propose a new conceptual model for identifying and specifying problem spaces in the context of self-adaptive software systems. Based on the foundations of this conceptual model, we propose a model-centric approach for engineering self-adaptive software by designing a generic adaptation framework and a supporting evolution process. This approach is particularly tailored to facilitate and simplify the process of evolving and adapting current (legacy) software towards runtime adaptivity. The conducted case studies reveal the applicability and effectiveness of this approach in bringing self-adaptive behaviour into non-adaptive applications that essentially demand adaptive behaviour to sustain