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Progressing problems from requirements to specifications in problem frames
One of the problems with current practice in software development is that often customer requirements are not well captured, understood and analysed, and there is no clear traceable path from customer requirements to software specifications. This often leads to a mismatch between what the customer needs and what the software developer understands the customer needs.
In addition to capturing, understanding and analysing requirements, requirements engineering (RE) aims to provide methods to allow software development practitioners to derive software specifications from requirements. Although work exists towards this aim, the systematic derivation of specifications from requirements is still an open problem.
This thesis provides practical techniques to implement the idea of problem progression as the basis for transforming requirements into specifications. The techniques allow us to progress a software problem towards identifying its solution by carefully investigating the problem context and re-expressing the requirement statement until a specification is reached. We develop two classes of progression techniques, one formal, based on Hoare’s Communicating Sequential Processes (CSP), and one semi-formal, based on a notion of causality between events. The case studies in this thesis provide some validation for the techniques we have developed
Deriving Product Line Requirements: the RED-PL Guidance Approach
Product lines (PL) modeling have proven to be an effective approach to reuse
in software development.Several variability approaches were developed to plan
requirements reuse, but only little of them actuallyaddress the issue of
deriving product requirements.This paper presents a method, RED-PL that intends
to support requirements derivation. The originality ofthe proposed approach is
that (i) it is user-oriented, (ii) it guides product requirements elicitation
andderivation as a decision making activity, and (iii) it provides systematic
and interactive guidance assistinganalysts in taking decisions about
requirements. The RED-PL methodological process was validatedin an industrial
setting by considering the requirement engineering phase of a product line of
blood analyzers
A Value-Driven Framework for Software Architecture
Software that is not aligned with the business values of the organization for which it
was developed does not entirely fulfill its raison d’etre. Business values represent what
is important in a company, or organization, and should influence the overall software
system behavior, contributing to the overall success of the organization. However, approaches
to derive a software architecture considering the business values exchanged
between an organization and its market players are lacking. Our quest is to address this
problem and investigate how to derive value-centered architectural models systematically.
We used the Technology Research method to address this PhD research question.
This methodological approach proposes three steps: problem analysis, innovation, and
validation. The problem analysis was performed using systematic studies of the literature
to obtain full coverage on the main themes of this work, particularly, business value
modeling, software architecture methods, and software architecture derivation methods.
Next, the innovation step was accomplished by creating a framework for the derivation
of a software reference architecture model considering an organization’s business values.
The resulting framework is composed of three core modules: Business Value Modeling,
Agile Reference Architecture Modeling, and Goal-Driven SOA Architecture Modeling.
While the Business value modeling module focuses on building a stakeholder-centric
business specification, the Agile Reference Architecture Modeling and the Goal-Driven
SOA Architecture Modeling modules concentrate on generating a software reference architecture
aligned with the business value specification. Finally, the validation part of
our framework is achieved through proof-of-concept prototypes for three new domain
specific languages, case studies, and quasi-experiments, including a family of controlled
experiments. The findings from our research show that the complexity and lack of rigor
in the existing approaches to represent business values can be addressed by an early requirements
specification method that represents the value exchanges of a business. Also,
by using sophisticated model-driven engineering techniques (e.g., metamodels, model
transformations, and model transformation languages), it was possible to obtain source
generators to derive a software architecture model based on early requirements value
models, while assuring traceability throughout the architectural derivation process. In conclusion, despite using sophisticated techniques, the derivation process of a software
reference architecture is helped by simple to use methods supported by black box
transformations and guidelines that facilitate the activities for the less experienced software
architects. The experimental validation process used confirmed that our framework
is feasible and perceived as easy to use and useful, also indicating that the participants
of the experiments intend to use it in the future
Automated analysis of feature models: Quo vadis?
Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186
On systematic approaches for interpreted information transfer of inspection data from bridge models to structural analysis
In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. However, the knowledge gain results from processing this information in a structural context, i.e. relating the damage artifacts to building components. This way, transformation to structural analysis is enabled. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies
Context for goal-level product line derivation
Product line engineering aims at developing a family of products and facilitating the derivation of product variants from it. Context can be a main factor in determining what products to derive. Yet, there is gap in incorporating context with variability models. We advocate that, in the first place, variability originates from human intentions and choices even before software systems are constructed, and context influences variability at this intentional level before the functional one. Thus, we propose to analyze variability at an early phase of analysis adopting the intentional ontology of goal models, and studying how context can influence such variability. Below we present a classification of variation points on goal models, analyze their relation with context, and show the process of constructing and maintaining the models. Our approach is illustrated with an example of a smarthome for people with dementia problems. 1
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