A holistic method for improving software product and process quality

The concept of quality in general is elusive, multi-faceted and is perceived differently by different stakeholders. Quality is difficult to define and extremely difficult to measure. Deficient software systems regularly result in failures which often lead to significant financial losses but more importantly to loss of human lives. Such systems need to be either scrapped and replaced by new ones or corrected/improved through maintenance. One of the most serious challenges is how to deal with legacy systems which, even when not failing, inevitably require upgrades, maintenance and improvement because of malfunctioning or changing requirements, or because of changing technologies, languages, or platforms. In such cases, the dilemma is whether to develop solutions from scratch or to re-engineer a legacy system. This research addresses this dilemma and seeks to establish a rigorous method for the derivation of indicators which, together with management criteria, can help decide whether restructuring of legacy systems is advisable. At the same time as the software engineering community has been moving from corrective methods to preventive methods, concentrating not only on both product quality improvement and process quality improvement has become imperative. This research investigation combines Product Quality Improvement, primarily through the re-engineering of legacy systems; and Process Improvement methods, models and practices, and uses a holistic approach to study the interplay of Product and Process Improvement. The re-engineering factor rho, a composite metric was proposed and validated. The design and execution of formal experiments tested hypotheses on the relationship of internal (code-based) and external (behavioural) metrics. In addition to proving the hypotheses, the insights gained on logistics challenges resulted in the development of a framework for the design and execution of controlled experiments in Software Engineering. The next part of the research resulted in the development of the novel, generic and, hence, customisable Quality Model GEQUAMO, which observes the principle of orthogonality, and combines a top-down analysis of the identification, classification and visualisation of software quality characteristics, and a bottom-up method for measurement and evaluation. GEQUAMO II addressed weaknesses that were identified during various GEQUAMO implementations and expert validation by academics and practitioners. Further work on Process Improvement investigated the Process Maturity and its relationship to Knowledge Sharing, resulted in the development of the I5P Visualisation Framework for Performance Estimation through the Alignment of Process Maturity and Knowledge Sharing. I5P was used in industry and was validated by experts from academia and industry. Using the principles that guided the creation of the GEQUAMO model, the CoFeD visualisation framework, was developed for comparative quality evaluation and selection of methods, tools, models and other software artifacts. CoFeD is very useful as the selection of wrong methods, tools or even personnel is detrimental to the survival and success of projects and organisations, and even to individuals. Finally, throughout the many years of research and teaching Software Engineering, Information Systems, Methodologies, I observed the ambiguities of terminology and the use of one term to mean different concepts and one concept to be expressed in different terms. These practices result in lack of clarity. Thus my final contribution comes in my reflections on terminology disambiguation for the achievement of clarity, and the development of a framework for achieving disambiguation of terms as a necessary step towards gaining maturity and justifying the use of the term “Engineering” 50 years since the term Software Engineering was coined. This research resulted in the creation of new knowledge in the form of novel indicators, models and frameworks which can aid quantification and decision making primarily on re-engineering of legacy code and on the management of process and its improvement. The thesis also contributes to the broader debate and understanding of problems relating to Software Quality, and establishes the need for a holistic approach to software quality improvement from both the product and the process perspectives

Defining and validating a multimodel approach for product architecture derivation and improvement

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-41533-3_24Software architectures are the key to achieving the non-functional requirements (NFRs) in any software project. In software product line (SPL) development, it is crucial to identify whether the NFRs for a specific product can be attained with the built-in architectural variation mechanisms of the product line architecture, or whether additional architectural transformations are required. This paper presents a multimodel approach for quality-driven product architecture derivation and improvement (QuaDAI). A controlled experiment is also presented with the objective of comparing the effectiveness, efficiency, perceived ease of use, intention to use and perceived usefulness with regard to participants using QuaDAI as opposed to the Architecture Tradeoff Analysis Method (ATAM). The results show that QuaDAI is more efficient and perceived as easier to use than ATAM, from the perspective of novice software architecture evaluators. However, the other variables were not found to be statistically significant. Further replications are needed to obtain more conclusive results.This research is supported by the MULTIPLE project (MICINN TIN2009-13838) and the Vali+D fellowship program (ACIF/2011/235).González Huerta, J.; Insfrán Pelozo, CE.; Abrahao Gonzales, SM. (2013). Defining and validating a multimodel approach for product architecture derivation and improvement. En Model-Driven Engineering Languages and Systems. Springer. 388-404. https://doi.org/10.1007/978-3-642-41533-3_24S388404Ali-Babar, M., Lago, P., Van Deursen, A.: Empirical research in software architecture: opportunities, challenges, and approaches. Empirical Software Engineering 16(5), 539–543 (2011)Ali-Babar, M., Zhu, L., Jeffery, R.: A Framework for Classifying and Comparing Software Architecture Evaluation Methods. In: 15th Australian Software Engineering Conference, Melbourne, Australia, pp. 309–318 (2004)Basili, V.R., Rombach, H.D.: The TAME project: towards improvement-oriented software environments. IEEE Transactions on Software Engineering 14(6), 758–773 (1988)Barkmeyer, E.J., Feeney, A.B., Denno, P., Flater, D.W., Libes, D.E., Steves, M.P., Wallace, E.K.: Concepts for Automating Systems Integration NISTIR 6928. National Institute of Standards and Technology, U.S. Dept. of Commerce (2003)Bosch, J.: Design and Use of Software Architectures. Adopting and Evolving Product-Line Approach. Addison-Wesley, Harlow (2000)Botterweck, G., O’Brien, L., Thiel, S.: Model-driven derivation of product architectures. In: 22th Int. Conf. on Automated Software Engineering, New York, USA, pp. 469–472 (2007)Buschmann, F., Meunier, R., Rohnert, H., Sommerlad, P., Stal, M.: Pattern-Oriented software architecture, vol. 1: A System of Patterns. Wiley (1996)Cabello, M.E., Ramos, I., Gómez, A., Limón, R.: Baseline-Oriented Modeling: An MDA Approach Based on Software Product Lines for the Expert Systems Development. In: 1st Asia Conference on Intelligent Information and Database Systems, Vietnam (2009)Carifio, J., Perla, R.J.: Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal of Social Sciences 3(3), 106–116 (2007)Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addison-Wesley, Boston (2007)Czarnecki, K., Kim, C.H.: Cardinality-based feature modeling and constraints: A progress report. In: Int. Workshop on Software Factories, San Diego-CA (2005)Datorro, J.: Convex Optimization & Euclidean Distance Geometry. Meboo Publishing (2005)Davis, F.D.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)Douglass, B.P.: Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems. Addison-Wesley, Boston (2002)Feiler, P.H., Gluch, D.P., Hudak, J.: The Architecture Analysis & Design Language (AADL): An Introduction. Tech. Report CMU/SEI-2006-TN-011. SEI, Carnegie Mellon University (2006)Gómez, A., Ramos, I.: Cardinality-based feature modeling and model-driven engineering: Fitting them together. In: 4th Int. Workshop on Variability Modeling of Software Intensive Systems, Linz, Austria (2010)Gonzalez-Huerta, J., Insfran, E., Abrahao, S.: A Multimodel for Integrating Quality Assessment in Model-Driven Engineering. In: 8th International Conference on the Quality of Information and Communications Technology (QUATIC 2012), Lisbon, Portugal, September 3-6 (2012)Gonzalez-Huerta, J., Insfran, E., Abrahao, S., McGregor, J.D.: Non-functional Requirements in Model-Driven Software Product Line Engineering. In: 4th Int. Workshop on Non-functional System Properties in Domain Specific Modeling Languages, Insbruck, Austria (2012)Guana, V., Correal, V.: Variability quality evaluation on component-based software product lines. In: 15th Int. Software Product Line Conference, Munich, Germany, vol. 2, pp. 19.1–19.8 (2011)Insfrán, E., Abrahão, S., González-Huerta, J., McGregor, J.D., Ramos, I.: A Multimodeling Approach for Quality-Driven Architecture Derivation. In: 21st Int. Conf. on Information Systems Development (ISD 2012), Prato, Italy (2012)ISO/IEC 25000:2005, Software Engineering. Software product Quality Requirements and Evaluation SQuaRE (2005)Kazman, R., Klein, M., Clements, P.: ATAM: Method for Architecture Evaluation (CMU/SEI-2000-TR-004, ADA382629). Software Engineering Institute, Carnegie Mellon University, Pittsburgh (2000), http://www.sei.cmu.edu/publications/documents/00.reports/00tr004.htmlKim, T., Ko, I., Kang, S., Lee, D.: Extending ATAM to assess product line architecture. In: 8th IEEE Int. Conference on Computer and Information Technology, Sydney, Australia, pp. 790–797 (2008)Kitchenham, B.A., Pfleeger, S.L., Hoaglin, D.C., Rosenber, J.: Preliminary Guidelines for Empirical Research in Software Engineering. IEEE Transactions on Software Engineering 28(8) (2002)Kruchten, P.B.: The Rational Unified Process: An Introduction. Addison-Wesley (1999)Martensson, F.: Software Architecture Quality Evaluation. Approaches in an Industrial Context. Ph. D. thesis, Blekinge Institute of Technology, Karlskrona, Sweden (2006)Maxwell, K.: Applied Statistics for Software Managers. Software Quality Institute Series. Prentice-Hall (2002)Olumofin, F.G., Mišic, V.B.: A holistic architecture assessment method for software product lines. Information and Software Technology 49, 309–323 (2007)Perovich, D., Rossel, P.O., Bastarrica, M.C.: Feature model to product architectures: Applying MDE to Software Product Lines. In: IEEE/IFIP & European Conference on Software Architecture, Helsinki, Findland, pp. 201–210 (2009)Robertson, S., Robertson, J.: Mastering the requirements process. ACM Press, New York (1999)Roos-Frantz, F., Benavides, D., Ruiz-Cortés, A., Heuer, A., Lauenroth, K.: Quality-aware analysis in product line engineering with the orthogonal variability model. Software Quality Journal (2011), doi:10.1007/s11219-011-9156-5Saaty, T.L.: The Analytical Hierarchical Process. McGraw- Hill, New York (1990)Taher, L., Khatib, H.E., Basha, R.: A framework and QoS matchmaking algorithm for dynamic web services selection. In: 2nd Int. Conference on Innovations in Information Technology, Dubai, UAE (2005)Wohlin, C., Runeson, P., Host, M., Ohlsson, M.C., Regnell, B., Weslen, A.: Experimentation in Software Engineering - An Introduction. Kluwer (2000

Requirements engineering for computer integrated environments in construction

A Computer Integrated Environment (CIE) is the type of innovative integrated information system that helps to reduce fragmentation and enables the stakeholders to collaborate together in business. Researchers have observed that the concept of CIE has been the subject of research for many years but the uptake of this technology has been very limited because of the development of the technology and its effective implementation. Although CIE is very much valued by both industrialists and academics, the answers to the question of how to develop and how to implement it are still not clear. The industrialists and researchers conveyed that networking, collaboration, information sharing and communication will become popular and critical issues in the future, which can be managed through CIE systems. In order for successful development of the technology, successful delivery, and effective implementation of user and industry-oriented CIE systems, requirements engineering seems a key parameter. Therefore, through experiences and lessons learnt in various case studies of CIE systems developments, this book explains the development of a requirements engineering framework specific to the CIE system. The requirements engineering process that has been developed in the research is targeted at computer integrated environments with a particular interest in the construction industry as the implementation field. The key features of the requirements engineering framework are the following: (1) ready-to-use, (2) simple, (3) domain specific, (4) adaptable and (5) systematic, (6) integrated with the legacy systems. The method has three key constructs: i) techniques for requirements development, which includes the requirement elicitation, requirements analysis/modelling and requirements validation, ii) requirements documentation and iii) facilitating the requirements management. It focuses on system development methodologies for the human driven ICT solutions that provide communication, collaboration, information sharing and exchange through computer integrated environments for professionals situated in discrete locations but working in a multidisciplinary and interdisciplinary environment. The overview for each chapter of the book is as follows; Chapter 1 provides an overview by setting the scene and presents the issues involved in requirements engineering and CIE (Computer Integrated Environments). Furthermore, it makes an introduction to the necessity for requirements engineering for CIE system development, experiences and lessons learnt cumulatively from CIE systems developments that the authors have been involved in, and the process of the development of an ideal requirements engineering framework for CIE systems development, based on the experiences and lessons learnt from the multi-case studies. Chapter 2 aims at building up contextual knowledge to acquire a deeper understanding of the topic area. This includes a detailed definition of the requirements engineering discipline and the importance and principles of requirements engineering and its process. In addition, state of the art techniques and approaches, including contextual design approach, the use case modelling, and the agile requirements engineering processes, are explained to provide contextual knowledge and understanding about requirements engineering to the readers. After building contextual knowledge and understanding about requirements engineering in chapter 2, chapter 3 attempts to identify a scope and contextual knowledge and understanding about computer integrated environments and Building Information Modelling (BIM). In doing so, previous experiences of the authors about systems developments for computer integrated environments are explained in detail as the CIE/BIM case studies. In the light of contextual knowledge gained about requirements engineering in chapter 2, in order to realize the critical necessity of requirements engineering to combine technology, process and people issues in the right balance, chapter 4 will critically evaluate the requirements engineering activities of CIE systems developments that are explained in chapter 3. Furthermore, to support the necessity of requirements engineering for human centred CIE systems development, the findings from semi-structured interviews are shown in a concept map that is also explained in this chapter. In chapter 5, requirements engineering is investigated from different angles to pick up the key issues from discrete research studies and practice such as traceability through process and product modelling, goal-oriented requirements engineering, the essential and incidental complexities in requirements models, the measurability of quality requirements, the fundamentals of requirements engineering, identifying and involving the stakeholders, reconciling software requirements and system architectures and barriers to the industrial uptake of requirements engineering. In addition, a comprehensive research study measuring the success of requirements engineering processes through a set of evaluation criteria is introduced. Finally, the key issues and the criteria are comparatively analyzed and evaluated in order to match each other and confirm the validity of the criteria for the evaluation and assessment of the requirements engineering implementation in the CIE case study projects in chapter 7 and the key issues will be used in chapter 9 to support the CMM (Capability Maturity Model) for acceptance and wider implications of the requirements engineering framework to be proposed in chapter 8. Chapter 6 explains and particularly focuses on how the requirements engineering activities in the case study projects were handled by highlighting strengths and weaknesses. This will also include the experiences and lessons learnt from these system development practices. The findings from these developments will also be utilized to support the justification of the necessity of a requirements engineering framework for the CIE systems developments. In particular, the following are addressed. • common and shared understanding in requirements engineering efforts, • continuous improvement, • outputs of requirement engineering • reflections and the critical analysis of the requirements engineering approaches in these practices. The premise of chapter 7 is to evaluate and assess the requirements engineering approaches in the CIE case study developments from multiple viewpoints in order to find out the strengths and the weaknesses in these requirements engineering processes. This evaluation will be mainly based on the set of criteria developed by the researchers and developers in the requirements engineering community in order to measure the success rate of the requirements engineering techniques after their implementation in the various system development projects. This set of criteria has already been introduced in chapter 5. This critical assessment includes conducting a questionnaire based survey and descriptive statistical analysis. In chapter 8, the requirements engineering techniques tested in the CIE case study developments are composed and compiled into a requirements engineering process in the light of the strengths and the weaknesses identified in the previous chapter through benchmarking with a Capability Maturity Model (CMM) to ensure that it has the required level of maturity for implementation in the CIE systems developments. As a result of this chapter, a framework for a generic requirements engineering process for CIE systems development will be proposed. In chapter 9, the authors will discuss the acceptance and the wider implications of the proposed framework of requirements engineering process using the CMM from chapter 8 and the key issues from chapter 5. Chapter 10 is the concluding chapter and it summarizes the findings and brings the book to a close with recommendations for the implementation of the Proposed RE framework and also prescribes a guideline as a way forward for better implementation of requirements engineering for successful developments of the CIE systems in the future

A systematic review of quality attributes and measures for software product lines

[EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. 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In XXXIV Conferencia Latinamericana de Informática (CLEI), Santa Fé, Argentina, pp. 489–498.Alves, V., Niu, N., Alves, C., & Valença, G. (2010). Requirements engineering for software product lines: A systematic literature review. Information & Software Technology, 52(8), 806–820.Bosch, J. (2000). Design and use of software architectures: Adopting and evolving a product line approach. USA: ACM Press/Addison-Wesley Publishing Co.Briand, L. C., Differing, C. M., & Rombach, D. (1996a). Practical guidelines for measurement-based process improvement. Software Process-Improvement and Practice, 2, 253–280.Briand, L. C., Morasca, S., & Basili, V. R. (1996b). Property based software engineering measurement. IEEE Transactions on Software Eng., 22(1), 68–86.Calero, C., Ruiz, J., & Piattini, M. (2005). Classifying web metrics using the web quality model. Online Information Review, 29(3): 227–248.Chen, L., Ali Babar, M., & Ali, N. (2009). 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B., Barachisio Lisboa, L., de Almeida E. S., & de Lemos Meira, S. R. (2008). Evaluating domain design approaches using systematic review. In 2nd European conference on software architecture, Cyprus, pp. 50–65.Ejiogu, L. (1991). Software engineering with formal metrics. QED Publishing.Engström, E., & Runeson, P. (2011). Software product line testing—A systematic mapping study. Information & Software Technology, 53(1), 2–13.Etxeberria, L., Sagarui, G., & Belategi, L. (2008). Quality aware software product line engineering. Journal of the Brazilian Computer Society, 14(1), Campinas Mar.Ganesan, D., Knodel, J., Kolb, R., Haury, U., & Meier, G. (2007). Comparing costs and benefits of different test strategies for a software product line: A study from Testo AG. In 11th international software product line conference, Kyoto, Japan, pp. 74–83, September 2007.Gómez, O., Oktaba, H., Piattini, M., & García, F. (2006). 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Visualization and understanding of scope change dynamics in a large-scale industrial setting. In 17th IEEE international requirements engineering conference.Yoshimura, K., Ganesan, D., & Muthig, D. (2006). Assessing merge potential of existing engine control systems into a product line. In International workshop on software engineering for automative systems, Shangai, China, pp. 61–67.Zhang, T., Deng, L., Wu, J., Zhou, Q., & Ma, C. (2008). Some metrics for accessing quality of product line architecture. In International conference on computer science and software engineering (CSSE), Wuhan, China, pp. 500–503

Data-driven and production-oriented tendering design using artificial intelligence

Construction projects are facing an increase in requirements since the projects are getting larger, more technology is integrated into the buildings, and new sustainability and CO2 equivalent emissions requirements are introduced. As a result, requirement management quickly gets overwhelming, and instead of having systematic requirement management, the construction industry tends to trust craftsmanship. One method for a more systematic requirement management approach successful in other industries is the systems engineering approach, focusing on requirement decomposition and linking proper verifications and validations. This research project explores if a systems engineering approach, supported by natural language processing techniques, can enable more systematic requirement management in construction projects and facilitate knowledge transfer from completed projects to new tendering projects.The first part of the project explores how project requirements can be extracted, digitised, and analysed in an automated way and how this can benefit the tendering specialists. The study is conducted by first developing a work support tool targeting tendering specialists and then evaluating the challenges and benefits of such a tool through a workshop and surveys. The second part of the project explores inspection data generated in production software as a requirement and quality verification method. First, a dataset containing over 95000 production issues is examined to understand the data quality level of standardisation. Second, a survey addressing production specialists evaluates the current benefits of digital inspection reporting. Third, future benefits of using inspection data for knowledge transfers are explored by applying the Knowledge Discovery in Databases method and clustering techniques. The results show that applying natural language processing techniques can be a helpful tool for analysing construction project requirements, facilitating the identification of essential requirements, and enabling benchmarking between projects. The results from the clustering process suggested in this thesis show that inspection data can be used as a knowledge base for future projects and quality improvement within a project-based organisation. However, higher data quality and standardisation would benefit the knowledge-generation process.This research project provides insights into how artificial intelligence can facilitate knowledge transfer, enable data-informed design choices in tendering projects, and automate the requirements analysis in construction projects as a possible step towards more systematic requirements management

Usability Inspection in Model-Driven Web Development: Empirical Validation in WebML

There is a lack of empirically validated usability evaluation methods that can be applied to models in model-driven Web development. Evaluation of these models allows an early detection of usability problems perceived by the end-user. This motivated us to propose WUEP, a usability inspection method which can be integrated into different model-driven Web development processes. We previously demonstrated how WUEP can effectively be used when following the Object-Oriented Hypermedia method. In order to provide evidences about WUEP’s generalizability, this paper presents the operationalization and empirical validation of WUEP into another well-known method: WebML. The effectiveness, efficiency, perceived ease of use, and satisfaction of WUEP were evaluated in comparison to Heuristic Evaluation (HE) from the viewpoint of novice inspectors. The results show that WUEP was more effective and efficient than HE when detecting usability problems on models. Also, inspectors were satisfied when applying WUEP, and found it easier to use than HE.Fernández Martínez, A.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE.; Matera, M. (2013). Usability Inspection in Model-Driven Web Development: Empirical Validation in WebML. Lecture Notes in Computer Science. 8107:740-756. doi:10.1007/978-3-642-41533-3_457407568107Abrahão, S., Iborra, E., Vanderdonckt, J.: Usability Evaluation of User Interfaces Generated with a Model-Driven Architecture Tool. In: Maturing Usability: Quality in Software, Interaction and Value, pp. 3–32. Springer (2007)Atterer, R., Schmidt, A.: Adding Usability to Web Engineering Models and Tools. In: Lowe, D.G., Gaedke, M. (eds.) ICWE 2005. LNCS, vol. 3579, pp. 36–41. Springer, Heidelberg (2005)Basili, V., Rombach, H.: The TAME Project: Towards Improvement-Oriented Software Environments. 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Design Space Exploration for Building Automation Systems

In the building automation domain, there are gaps among various tasks related to design engineering. As a result created system designs must be adapted to the given requirements on system functionality, which is related to increased costs and engineering effort than planned. For this reason standards are prepared to enable a coordination among these tasks by providing guidelines and unified artifacts for the design. Moreover, a huge variety of prefabricated devices offered from different manufacturers on the market for building automation that realize building automation functions by preprogrammed software components. Current methods for design creation do not consider this variety and design solution is limited to product lines of a few manufacturers and expertise of system integrators. Correspondingly, this results in design solutions of a limited quality. Thus, a great optimization potential of the quality of design solutions and coordination of tasks related to design engineering arises. For given design requirements, the existence of a high number of devices that realize required functions leads to a combinatorial explosion of design alternatives at different price and quality levels. Finding optimal design alternatives is a hard problem to which a new solution method is proposed based on heuristical approaches. By integrating problem specific knowledge into algorithms based on heuristics, a promisingly high optimization performance is achieved. Further, optimization algorithms are conceived to consider a set of flexibly defined quality criteria specified by users and achieve system design solutions of high quality. In order to realize this idea, optimization algorithms are proposed in this thesis based on goal-oriented operations that achieve a balanced convergence and exploration behavior for a search in the design space applied in different strategies. Further, a component model is proposed that enables a seamless integration of design engineering tasks according to the related standards and application of optimization algorithms.:1 Introduction 17 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.3 Goals and Use of the Thesis . . . . . . . . . . . . . . . . . . . . . 21 1.4 Solution Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.5 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . 24 2 Design Creation for Building Automation Systems 25 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.2 Engineering of Building Automation Systems . . . . . . . . . . . 29 2.3 Network Protocols of Building Automation Systems . . . . . . . 33 2.4 Existing Solutions for Design Creation . . . . . . . . . . . . . . . 34 2.5 The Device Interoperability Problem . . . . . . . . . . . . . . . . 37 2.6 Guidelines for Planning of Room Automation Systems . . . . . . 38 2.7 Quality Requirements on BAS . . . . . . . . . . . . . . . . . . . 41 2.8 Quality Requirements on Design . . . . . . . . . . . . . . . . . . 42 2.8.1 Quality Requirements Related to Project Planning . . . . 42 2.8.2 Quality Requirements Related to Project Implementation 43 2.9 Quality Requirements on Methods . . . . . . . . . . . . . . . . . 44 2.10 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3 The Design Creation Task 47 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.2 System Design Composition Model . . . . . . . . . . . . . . . . . 49 3.2.1 Abstract and Detailed Design Model . . . . . . . . . . . . 49 3.2.2 Mapping Model . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3 Formulation of the Problem . . . . . . . . . . . . . . . . . . . . . 53 3.3.1 Problem properties . . . . . . . . . . . . . . . . . . . . . . 54 3.3.2 Requirements on Algorithms . . . . . . . . . . . . . . . . 56 3.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4 Solution Methods for Design Generation and Optimization 59 4.1 Combinatorial Optimization . . . . . . . . . . . . . . . . . . . . . 59 4.2 Metaheuristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4.3 Examples for Metaheuristics . . . . . . . . . . . . . . . . . . . . . 62 4.3.1 Simulated Annealing . . . . . . . . . . . . . . . . . . . . . 62 4.3.2 Tabu Search . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.3.3 Ant Colony Optimization . . . . . . . . . . . . . . . . . . 65 4.3.4 Evolutionary Computation . . . . . . . . . . . . . . . . . 66 4.4 Choice of the Solver Algorithm . . . . . . . . . . . . . . . . . . . 69 4.5 Specialized Methods for Diversity Preservation . . . . . . . . . . 70 4.6 Approaches for Real World Problems . . . . . . . . . . . . . . . . 71 4.6.1 Component-Based Mapping Problems . . . . . . . . . . . 71 4.6.2 Network Design Problems . . . . . . . . . . . . . . . . . . 73 4.6.3 Comparison of Solution Methods . . . . . . . . . . . . . . 74 4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5 Automated Creation of Optimized Designs 79 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.2 Design Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.3 Component Model . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5.3.1 Presumptions . . . . . . . . . . . . . . . . . . . . . . . . . 85 5.3.2 Integration of Component Model . . . . . . . . . . . . . . 87 5.4 Design Generation . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.4.1 Component Search . . . . . . . . . . . . . . . . . . . . . . 88 5.4.2 Generation Approaches . . . . . . . . . . . . . . . . . . . 100 5.5 Design Improvement . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.5.1 Problems and Requirements . . . . . . . . . . . . . . . . . 107 5.5.2 Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 5.5.3 Application Strategies . . . . . . . . . . . . . . . . . . . . 121 5.6 Realization of the Approach . . . . . . . . . . . . . . . . . . . . . 122 5.6.1 Objective Functions . . . . . . . . . . . . . . . . . . . . . 122 5.6.2 Individual Representation . . . . . . . . . . . . . . . . . . 123 5.7 Automated Design Creation For A Building . . . . . . . . . . . . 124 5.7.1 Room Spanning Control . . . . . . . . . . . . . . . . . . . 124 5.7.2 Flexible Rooms . . . . . . . . . . . . . . . . . . . . . . . . 125 5.7.3 Technology Spanning Designs . . . . . . . . . . . . . . . . 129 5.7.4 Preferences for Mapping of Function Blocks to Devices . . 132 5.8 Further Uses and Applicability of the Approach . . . . . . . . . . 133 5.9 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 6 Validation and Performance Analysis 137 6.1 Validation Method . . . . . . . . . . . . . . . . . . . . . . . . . . 137 6.2 Performance Metrics . . . . . . . . . . . . . . . . . . . . . . . . . 137 6.3 Example Abstract Designs and Performance Tests . . . . . . . . 139 6.3.1 Criteria for Choosing Example Abstract Designs . . . . . 139 6.3.2 Example Abstract Designs . . . . . . . . . . . . . . . . . . 140 6.3.3 Performance Tests . . . . . . . . . . . . . . . . . . . . . . 142 6.3.4 Population Size P - Analysis . . . . . . . . . . . . . . . . 151 6.3.5 Cross-Over Probability pC - Analysis . . . . . . . . . . . 157 6.3.6 Mutation Probability pM - Analysis . . . . . . . . . . . . 162 6.3.7 Discussion for Optimization Results and Example Designs 168 6.3.8 Resource Consumption . . . . . . . . . . . . . . . . . . . . 171 6.3.9 Parallelism . . . . . . . . . . . . . . . . . . . . . . . . . . 172 6.4 Optimization Framework . . . . . . . . . . . . . . . . . . . . . . . 172 6.5 Framework Design . . . . . . . . . . . . . . . . . . . . . . . . . . 174 6.5.1 Components and Interfaces . . . . . . . . . . . . . . . . . 174 6.5.2 Workflow Model . . . . . . . . . . . . . . . . . . . . . . . 177 6.5.3 Optimization Control By Graphical User Interface . . . . 180 6.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 7 Conclusions 185 A Appendix of Designs 189 Bibliography 201 Index 21

A Model-Driven Approach for Business Process Management

The Business Process Management is a common mechanism recommended by a high number of standards for the management of companies and organizations. In software companies this practice is every day more accepted and companies have to assume it, if they want to be competitive. However, the effective definition of these processes and mainly their maintenance and execution are not always easy tasks. This paper presents an approach based on the Model-Driven paradigm for Business Process Management in software companies. This solution offers a suitable mechanism that was implemented successfully in different companies with a tool case named NDTQ-Framework.Ministerio de Educación y Ciencia TIN2010-20057-C03-02Junta de Andalucía TIC-578

Enterprise information security policy assessment - an extended framework for metrics development utilising the goal-question-metric approach

Effective enterprise information security policy management requires review and assessment activities to ensure information security policies are aligned with business goals and objectives. As security policy management involves the elements of policy development process and the security policy as output, the context for security policy assessment requires goal-based metrics for these two elements. However, the current security management assessment methods only provide checklist types of assessment that are predefined by industry best practices and do not allow for developing specific goal-based metrics. Utilizing theories drawn from literature, this paper proposes the Enterprise Information Security Policy Assessment approach that expands on the Goal-Question-Metric (GQM) approach. The proposed assessment approach is then applied in a case scenario example to illustrate a practical application. It is shown that the proposed framework addresses the requirement for developing assessment metrics and allows for the concurrent undertaking of process-based and product-based assessment. Recommendations for further research activities include the conduct of empirical research to validate the propositions and the practical application of the proposed assessment approach in case studies to provide opportunities to introduce further enhancements to the approach