Systematic construction of goal-oriented COTS taxonomies

The use of Commercial Off-The-Shelf (COTS) components is becoming a strategic need because they offer the possibility to build systems at reduced costs and within shorter development time. Having efficient and reliable COTS components selection methods is a key issue not only for exploiting the potential benefits of this technology, but also for facing the problems and risks involved. Searching COTS components requires overcoming several obstacles: the growing size and evolvability of the COTS marketplace, the dependencies from the components to be selected with others, and the type of descriptions currently available for those components. The main goal of this thesis is to provide support for a reliable and comprehensive structuring of a reuse infrastructure for the COTS components marketplace. With this aim, we propose a method for the construction and maintenance of goal-oriented COTS taxonomies based on a solid domain analysis; guiding the gathering of sources of information, modeling requirements and dependency relationship among domains, and organizing knowledge in any segment of the COTS marketplace.Peer ReviewedPostprint (author’s final draft

Construction of a taxonomy for requirements engineering commercial-off-the-shelf components

This article presents a procedure for constructing a taxonomy of COTS products in the field of Requirements Engineering (RE). The taxonomy and the obtained information reach transcendental benefits to the selection of systems and tools that aid to RE-related actors to simplify and facilitate their work. This taxonomy is performed by means of a goal-oriented methodology inspired in GBRAM (Goal-Based Requirements Analysis Method), called GBTCM (Goal-Based Taxonomy Construction Method), that provides a guide to analyze sources of information and modeling requirements and domains, as well as gathering and organizing the knowledge in any segment of the COTS market. GBTCM claims to promote the use of standards and the reuse of requirements in order to support different processes of selection and integration of components.Peer ReviewedPostprint (published version

Assessing what Information Quality means in OTS selection processes

OTS selection plays a crucial role in the deployment of software systems. One of its main current problems is how to deal with the vast amount of unstructured, incomplete, evolvable and widespread information that highly increases the risks of taking a wrong decision. The goal of our research is to tackle these information quality problems for facilitating the collection, storage, retrieval, analysis and reuse of OTS related information. An essential issue in this endeavor is to assess what OTS selectors mean by Information Quality and their needs to perform an informed selection. Therefore, we are putting forward an on-line survey to get empirical data supporting our approach.Peer ReviewedPostprint (published version

How do software architects consider non-functional requirements: an exploratory study

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Dealing with non-functional requirements (NFRs) has posed a challenge onto software engineers for many years. Over the years, many methods and techniques have been proposed to improve their elicitation, documentation, and validation. Knowing more about the state of the practice on these topics may benefit both practitioners' and researchers' daily work. A few empirical studies have been conducted in the past, but none under the perspective of software architects, in spite of the great influence that NFRs have on daily architects' practices. This paper presents some of the findings of an empirical study based on 13 interviews with software architects. It addresses questions such as: who decides the NFRs, what types of NFRs matter to architects, how are NFRs documented, and how are NFRs validated. The results are contextualized with existing previous work.Peer ReviewedPostprint (author’s final draft

A software service supporting software quality forecasting

Software repositories such as source control, defect tracking systems and project management tools, are used to support the progress of software projects. The exploitation of such data with techniques like forecasting is becoming an increasing need in several domains to support decision-making processes. However, although there exist several statistical tools and languages supporting forecasting, there is a lack of friendly approaches that enable practitioners to exploit the advantages of creating and using such models in their dashboard tools. Therefore, we have developed a modular and flexible forecasting service allowing the interconnection with different kinds of databases/data repositories for creating and exploiting forecasting models based on methods like ARIMA or ETS. The service is open source software, has been developed in Java and R and exposes its functionalities through a REST API. Architecture details are provided, along with functionalities’ description and an example of its use for software quality forecasting.Peer ReviewedPostprint (author's final draft

Selection of third party software in Off-The-Shelf-based software development: an interview study with industrial practitioners

The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.Peer ReviewedPostprint (author's final draft

Towards guidelines for building a business case and gathering evidence of software reference architectures in industry

Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges. Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain. Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices. Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version

A reuse-based economic model for software reference architectures

The growing size and complexity of software systems, together with critical time-to-market needs, demand new software engineering approaches for software development. To remain competitive, organizations are challenged to make informed and feasible value-driven design decisions in order to ensure the quality of the systems. However, there is a lack of support for evaluating the economic impact of these decisions with regard to software reference architectures. This damages the communication among architects and management, which can result in poor decisions. This paper aims at opening a path in this direction by presenting a pragmatic preliminary economic model to perform cost-benefit analysis on the adoption of software reference architectures as key asset for optimizing architectural decision-making. A preliminary validation based on a retrospective study showed the ability of the model to support a cost-benefit analysis presented to the management of an IT consulting company.Preprin

DOGO4ML: Development, operation and data governance for ML-based software systems

Machine Learning based Software Systems (MLSS) are becoming increasingly pervasive in today’s society and can be found in virtually every domain. Building MLSS is challenging due to their interdisciplinary nature. MLSS engineering encompasses multiple disciplines, of which Data Engineering and Software Engineering appear as most relevant. The DOGO4ML project aims at reconciling these two disciplines for providing a holistic end-to-end framework to develop, operate and govern MLSS and their data. It proposes to combine and intertwine two software cycles: the DataOps and the DevOps lifecycles. The DataOps lifecycle manages the complexity of dealing with the big data needed by ML models, while the DevOps lifecycle is in charge of building the system that embeds these models. In this paper, we present the main vision and goals of the project as well as its expected contributions and outcomes. Although the project is in its initial stage, the progress of the research undertaken so far is detailed.This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

Dealing with goal models complexity using topological metrics and algorithms

The inherent complexity of business goal-models is a challenge for organizations that has to analyze and maintaining them. Several approaches are developed to reduce the complexity into manageable limits, either by providing support to the modularization or designing metrics to monitor the complexity levels. These approaches are designed to identify an unusual complexity comparing it among models. In the present work, we expose two approaches based on structural characteristics of goal-model, which do not require these comparisons. The first one ranksthe importance of goalsto identify a manageable set of them that can be considered as a priority; the second one modularizes the model to reduce the effort to understand, analyze and maintain the model.Peer ReviewedPostprint (published version