Perceived Quality of Cars. A Novel Framework and Evaluation Methodology.

The supremacy of the automotive manufacturers today is no longer driven by them achieving a superior manufacturing quality but increasingly depends on the customer’s quality perception. Average car consumers see a car’s quality as a fancy mixture of design, aesthetics, their own previous experiences and performance characteristics of the vehicle, unlike a combination of mechanical parts, software pieces, advanced materials, cutting-edge manufacturing processes, with technical knowledge, skills and high production volumes – all ingredients involved in the modern car creation. Perceived quality is one of the most critical aspects for product development that defines successful car design.Speaking of perceived quality, we are dealing with a complex, multifaceted adaptive system; a system where a human is the main agent. “Which product characteristics require the most attention for successful car design?”\ua0 This is the question engineers and designers need to answer under the pressure of shrinking product development time, available technologies, and financial limitations, not to mention that the answer is expected to be given in numbers to sustain the fierce competition in today’s automotive industry. For this reason, the perceived quality must be understood and controlled during all stages of product development. The research presented in this thesis justifies the engineering viewpoint on perceived quality as an inevitable part of new product development. The core of this research is the Perceived Quality Framework (PQF), a taxonomy structure of perceived quality attributes and the Perceived Quality Attributes Importance Ranking (PQAIR) method, a novel method for perceived quality evaluation that can be applied to a variety of products, including cars. The PQF communicates the attribute-centric engineering viewpoint on quality perception, developed through cumulative studies in the premium and luxury market segment of the automotive industry. The PQAIR method equips engineers with practical tools for perceived quality evaluation. The proposed method helps to reach the equilibrium of the product’s quality equation from the perspective of design effort, time, and costs estimations.Altogether this introduces a new paradigm of perceived quality as the inevitable element integrated into the process of engineering endeavor regarding product attributes that communicates quality to the customer

Evaluating Software Architectures: Development Stability and Evolution

We survey seminal work on software architecture evaluationmethods. We then look at an emerging class of methodsthat explicates evaluating software architectures forstability and evolution. We define architectural stabilityand formulate the problem of evaluating software architecturesfor stability and evolution. We draw the attention onthe use of Architectures Description Languages (ADLs) forsupporting the evaluation of software architectures in generaland for architectural stability in specific

Measuring Software Process: A Systematic Mapping Study

Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED

Measuring the Pro-Activity of Software Agents

Despite having well-defined characteristics, software agents do not have a developed set of measures defining their quality. Attempts at evaluating software agent quality have focused on some agent aspects, like the development process, whereas others focusing on the agent as a software product have basically adopted measures associated with other software paradigms, like procedural and object-oriented concepts. Here we propose a set of measures for evaluating software agent pro-activity, the software agent's goal-driven behavioral ability to take the initiative and satisfy its goal

Linking Quality Attributes and Constraints with Architectural Decisions

Quality attributes and constraints are among the main drivers of architectural decision making. The quality attributes are improved or damaged by the architectural decisions, while restrictions directly include or exclude parts of the architecture (for example, the logical components or technologies). We can determine the impact of a decision of architecture in software quality, or which parts of the architecture are affected by a constraint, but the difficult problem is whether we are respecting the quality requirements (requirements on quality attributes) and constraints with all the architectural decisions made. Currently, the common practice is that architects use their own experience to design architectures that meet the quality requirements and restrictions, but at the end, especially for the crucial decisions, the architect has to deal with complex trade-offs between quality attributes and juggle possible incompatibilities raised by the constraints. In this paper we present Quark, a computer-aided method to support architects in software architecture decision making

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences

To ensure sustainable software maintenance and evolution, a diverse set of activities and concepts like metrics, change impact analysis, or antipattern detection can be used. Special maintainability assurance techniques have been proposed for service- and microservice-based systems, but it is difficult to get a comprehensive overview of this publication landscape. We therefore conducted a systematic literature review (SLR) to collect and categorize maintainability assurance approaches for service-oriented architecture (SOA) and microservices. Our search strategy led to the selection of 223 primary studies from 2007 to 2018 which we categorized with a threefold taxonomy: a) architectural (SOA, microservices, both), b) methodical (method or contribution of the study), and c) thematic (maintainability assurance subfield). We discuss the distribution among these categories and present different research directions as well as exemplary studies per thematic category. The primary finding of our SLR is that, while very few approaches have been suggested for microservices so far (24 of 223, ?11%), we identified several thematic categories where existing SOA techniques could be adapted for the maintainability assurance of microservices

On the role of pre and post-processing in environmental data mining

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

Towards a Tool-based Development Methodology for Pervasive Computing Applications

Despite much progress, developing a pervasive computing application remains a challenge because of a lack of conceptual frameworks and supporting tools. This challenge involves coping with heterogeneous devices, overcoming the intricacies of distributed systems technologies, working out an architecture for the application, encoding it in a program, writing specific code to test the application, and finally deploying it. This paper presents a design language and a tool suite covering the development life-cycle of a pervasive computing application. The design language allows to define a taxonomy of area-specific building-blocks, abstracting over their heterogeneity. This language also includes a layer to define the architecture of an application, following an architectural pattern commonly used in the pervasive computing domain. Our underlying methodology assigns roles to the stakeholders, providing separation of concerns. Our tool suite includes a compiler that takes design artifacts written in our language as input and generates a programming framework that supports the subsequent development stages, namely implementation, testing, and deployment. Our methodology has been applied on a wide spectrum of areas. Based on these experiments, we assess our approach through three criteria: expressiveness, usability, and productivity

Conceptual fit: A criterion for COTS selection

COTS systems selection consists in evaluating the user requirements with respect to characteristics of candidate systems, using a set of criteria. One criterion that has received little attention is what we call conceptual fit. The criterion assesses the fit between the conceptual structure of the user requirements and that of a system. We evaluate the fit in terms of the existing misfits. We formally define the notion of conceptual misfit and we present a method that determines the conceptual misfits between the user requirements and a set of candidate systems. The method consists in defining a superschema, the mapping of the conceptual schemas of the candidate systems and of the user requirements to that superschema, and the automatic computation of the existing conceptual misfits. The method has been formalized in UML/OCL. We have conducted an exploratory experiment with the aim of evaluating the feasibility, difficulty and usefulness of the method, with positive results. We believe that the conceptual fit criterion could be taken into account by almost all existing COTS selection methods.Preprin