Evaluation of Model Transformation Approaches for Model Refactoring

This paper provides a systematic evaluation framework for comparing model transformation approaches, based upon the ISO/IEC 9126-1 quality characteristics for software systems. We apply this framework to compare five transformation approaches (QVT-R, ATL, Kermeta, UMLRSDS and GrGen.NET) on a complex model refactoring case study: the amalgamation of apparent attribute clones in a class diagram. The case study highlights the problems with the specification and design of the refactoring category of model transformations, and provides a challenging example by which model transformation languages and approaches can be compared. We take into account a wide range of evaluation criteria aspects such as correctness, efficiency, flexibility, interoperability, reusability and robustness, which have not been comprehensively covered by other comparative surveys of transformation approaches. The results show clear distinctions between the capabilities and suitabilities of different approaches to address the refactoring form of transformation problem

Redocumentation through design pattern recovery:: an investigation and an implementation

In this thesis, two methods are developed in an aid to help users capture valuable design information and knowledge and reuse them. They are the design pattern recovery (DPR) method and pattern-based redocumentation (PBR) method. The DPR method is for matching up metrics of patterns with patterns themselves in order to capture valuable design information. Patterns are used as a container for storing the information. Two new metrics, i.e., p-value and s-value are introduced. They are obtained by analysing product metrics statistically. Once patterns have been detected from a system, the system can be redocumented using these patterns. Some existing XML (extensible Markup Language) technologies are utilised in order to realise the PRB method. Next, a case study is carried out to validate the soundness and usefulness of the DPR method. Finally, some conclusions drawn from this research are summarised, and further work is suggested for the researchers in software engineering

30 Years of Software Refactoring Research:A Systematic Literature Review

Due to the growing complexity of software systems, there has been a dramatic increase and industry demand for tools and techniques on software refactoring in the last ten years, defined traditionally as a set of program transformations intended to improve the system design while preserving the behavior. Refactoring studies are expanded beyond code-level restructuring to be applied at different levels (architecture, model, requirements, etc.), adopted in many domains beyond the object-oriented paradigm (cloud computing, mobile, web, etc.), used in industrial settings and considered objectives beyond improving the design to include other non-functional requirements (e.g., improve performance, security, etc.). Thus, challenges to be addressed by refactoring work are, nowadays, beyond code transformation to include, but not limited to, scheduling the opportune time to carry refactoring, recommendations of specific refactoring activities, detection of refactoring opportunities, and testing the correctness of applied refactorings. Therefore, the refactoring research efforts are fragmented over several research communities, various domains, and objectives. To structure the field and existing research results, this paper provides a systematic literature review and analyzes the results of 3183 research papers on refactoring covering the last three decades to offer the most scalable and comprehensive literature review of existing refactoring research studies. Based on this survey, we created a taxonomy to classify the existing research, identified research trends, and highlighted gaps in the literature and avenues for further research.Comment: 23 page

30 Years of Software Refactoring Research: A Systematic Literature Review

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd

A systematic review of protocol studies on conceptual design cognition: design as search and exploration

This paper reports findings from the first systematic review of protocol studies focusing specifically on conceptual design cognition, aiming to answer the following research question: What is our current understanding of the cognitive processes involved in conceptual design tasks carried out by individual designers? We reviewed 47 studies on architectural design, engineering design and product design engineering. This paper reports 24 cognitive processes investigated in a subset of 33 studies aligning with two viewpoints on the nature of designing: (V1) design as search (10 processes, 41.7%); and (V2) design as exploration (14 processes, 58.3%). Studies on search focused on solution search and problem structuring, involving: long-term memory retrieval; working memory; operators and reasoning processes. Studies on exploration investigated: co-evolutionary design; visual reasoning; cognitive actions; and unexpected discovery and situated requirements invention. Overall, considerable conceptual and terminological differences were observed among the studies. Nonetheless, a common focus on memory, semantic, associative, visual perceptual and mental imagery processes was observed to an extent. We suggest three challenges for future research to advance the field: (i) developing general models/theories; (ii) testing protocol study findings using objective methods conducive to larger samples and (iii) developing a shared ontology of cognitive processes in design

Demystifying the effectiveness in design of production systems - Investigating the coupling between acquisition and maintenance of equipment

The purpose of the design of production systems is to create systems that perform according to set targets. With the paradigm shift towards electrification and digitalisation, manufacturing engineers in the heavy truck powertrain industry face several unexplored challenges; in the products for which they are designing production, in the equipment they are purchasing to realise production systems, and finally, in the digitalisation impact on engineering processes. Further, there is a lack of empirical studies on the performance of production system design, measured as the performance of production systems when they are in operation. Understanding performance of design is vital in order to identify and implement correct improvement measures.\ua0 \ua0To investigate the performance of production system design, this thesis presents comparative case studies from powertrain manufacturing engineering in a large heavy truck company. The focus is on the equipment acquisition process and its impact on the performance of the purchased equipment and specifically equipment breakdown cost due to design weakness. The investigation was performed both quantitatively, comparing breakdown costs for newly acquired equipment to equipment nearing their end of life, and qualitatively, comparing the ability to prevent breakdowns in four re-purchasing acquisition projects. The thesis shows that: 1) maintenance cost per machine is increasing during the initial phase of the life cycle; 2) new machinery have higher breakdown costs than the end-of-life machines; 3) the design weakness share of maintenance problems unexpectedly only increases during the initial phase of the life cycle. The conclusion is that the engineering process studied does not become more effective over time. \ua0The main barriers to effective design of production systems are found to be connected to how knowledge flows internally and externally in the organisation, and more specifically during the organisational and individual dimensions, rather than the technological aspect. Further research in knowledge management is recommended as well as a study of how digitalisation might benefit the production system design engineering community from a socio-technological point of view

Evidence-based design utilized in hospital architecture and changing the design process: a hospital case study

As a new paradigm in healthcare design in the 21st century, evidence-based design (EBD) has played a critical role in the changing hospital architectural design process and shaping new images of hospital architecture. Evidence-based design is research informed, and its results affect not only patients' clinical outcomes but also medical facility operational efficiency and its staff retention and satisfaction. This research investigated how EBD was implemented in hospital architectural design and how traditional design process was modified to incorporate credible research evidence through a case study at Grand River Hospital in the United States. This study took a qualitative approach with grounded theory methodology. The methods used for this research were multiple sources of data collection through document reviews, observations, and interviews. Findings revealed that the investigation for EBD needs to focus on environment-behavior studies especially in the development of explanatory theory. This study also recommended a modified cyclical design process model for integrating EBD. This redefined design process model requires collaborations with all stakeholders by adding visioning sessions, multiple design charrettes, mock-ups, and the functional performance evaluation to help to implement research evidence and make design decisions to achieve the best possible outcomes