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Silverio Martínez-Fernández

Bio: Silverio Martínez-Fernández is an academic researcher from Polytechnic University of Catalonia. The author has contributed to research in topics: Agile software development & Software quality. The author has an hindex of 9, co-authored 41 publications receiving 266 citations. Previous affiliations of Silverio Martínez-Fernández include University of Navarra & Fraunhofer Society.

Papers
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Journal ArticleDOI
TL;DR: This study identified research gaps, such as the need for more tools and guidelines, lightweight QR management strategies that fit short iteration cycles, investigations of the link between QRs challenges and technical debt, and extension of empirical validation of existing strategies to a wider context.
Abstract: Context Quality requirements (QRs) describe the desired quality of software, and they play an important role in the success of software projects. In agile software development (ASD), QRs are often ill-defined and not well addressed due to the focus on quickly delivering functionality. Rapid software development (RSD) approaches (e.g., continuous delivery and continuous deployment), which shorten delivery times, are more prone to neglect QRs. Despite the significance of QRs in both ASD and RSD, there is limited synthesized knowledge on their management in those approaches. Objective This study aims to synthesize state-of-the-art knowledge about QR management in ASD and RSD, focusing on three aspects: bibliometric, strategies, and challenges. Research method Using a systematic mapping study with a snowballing search strategy, we identified and structured the literature on QR management in ASD and RSD. Results We found 156 primary studies: 106 are empirical studies, 16 are experience reports, and 34 are theoretical studies. Security and performance were the most commonly reported QR types. We identified various QR management strategies: 74 practices, 43 methods, 13 models, 12 frameworks, 11 advices, 10 tools, and 7 guidelines. Additionally, we identified 18 categories and 4 non-recurring challenges of managing QRs. The limited ability of ASD to handle QRs, time constraints due to short iteration cycles, limitations regarding the testing of QRs and neglect of QRs were the top categories of challenges. Conclusion Management of QRs is significant in ASD and is becoming important in RSD. This study identified research gaps, such as the need for more tools and guidelines, lightweight QR management strategies that fit short iteration cycles, investigations of the link between QRs challenges and technical debt, and extension of empirical validation of existing strategies to a wider context. It also synthesizes QR management strategies and challenges, which may be useful for practitioners.

47 citations

Journal ArticleDOI
TL;DR: The potential for future adoption of quality models within software analytics tools definitely exists and practitioners are encouraged to use the presented seven challenges and seven lessons learned and adopt them in their companies.
Abstract: In the last decade, modern data analytics technologies have enabled the creation of software analytics tools offering real-time visualization of various aspects related to software development and usage. These tools seem to be particularly attractive for companies doing agile software development. However, the information provided by the available tools is neither aggregated nor connected to higher quality goals. At the same time, assessing and improving the software quality has also been the key targets for the software engineering community, yielding several proposals for standards and software quality models. Integrating such quality models into software analytics tools could close the gap by providing the connection to higher quality goals. This paper aims at understanding whether the integration of quality models into software analytics tools provides understandable, reliable, useful, and relevant information at the right level of detail about the quality of a process or product and whether practitioners intend to use it. Over the course of more than a year, four companies involved in this case study deployed such a tool to assess and improve software quality in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. We complemented the findings with debriefing sessions held at the companies. In addition, we discussed challenges and lessons learned with four practitioners leading the use of the tool. The quantitative and qualitative analyses provided positive results, i.e., the practitioners' perception with regard to the tool's understandability, reliability, usefulness, and relevance was positive. Individual statements support the statistical findings, and constructive feedback can be used for future improvements. We conclude that the potential for future adoption of quality models within software analytics tools definitely exists and encourage other practitioners to use the presented seven challenges and seven lessons learned and adopt them in their companies.

43 citations

Journal ArticleDOI
TL;DR: The results indicate that it is important for practitioners to handle `NFRs in MDD, but further research is necessary in order to lower the barrier for supporting a broad spectrum of NFRs with MDD.
Abstract: Context: Managing Non-Functional Requirements (NFRs) in software projects is challenging, and projects that adopt Model-Driven Development (MDD) are no exception. Although several methods and techniques have been proposed to face this challenge, there is still little evidence on how NFRs are handled in MDD by practitioners. Knowing more about the state of the practice may help researchers to steer their research and practitioners to improve their daily work. Objective : In this paper, we present our findings from an interview-based survey conducted with practitioners working in 18 different companies from 6 European countries. From a practitioner's point of view, the paper shows what barriers and benefits the management of NFRs as part of the MDD process can bring to companies, how NFRs are supported by MDD approaches, and which strategies are followed when (some) types of NFRs are not supported by MDD approaches. Results : Our study shows that practitioners perceive MDD adoption as a complex process with little to no tool support for NFRs, reporting productivity and maintainability as the types of NFRs expected to be supported when MDD is adopted. But in general, companies adapt MDD to deal with NFRs. When NFRs are not supported, the generated code is sometimes changed manually, thus compromising the maintainability of the software developed. However, the interviewed practitioners claim that the benefits of using MDD outweight the extra effort required by these manual adaptations. Conclusion : Overall, the results indicate that it is important for practitioners to handle `NFRs in MDD, but further research is necessary in order to lower the barrier for supporting a broad spectrum of NFRs with MDD. Still, much conceptual and tool implementation work seems to be necessary to lower the barrier of integrating the broad spectrum of NFRs in practice.

42 citations

Proceedings ArticleDOI
01 Sep 2017
TL;DR: This paper uses the concept of blocking situation to exemplify the Q-Rapids approach, which proposes the collection and analysis of data and its consolidation into a set of strategic indicators as product quality, time to market and team productivity.
Abstract: Requirements identification, specification and management are key activities in the software development process. In the last years, many approaches to these activities have emerged, based on the exploitation of huge amounts of data gathered from software repositories and system usage. The Q-Rapids project proposes the collection and analysis of such data and its consolidation into a set of strategic indicators as product quality, time to market and team productivity. These indicators are visualized through a dashboard designed to support decision-makers. In this paper, we present the ongoing research undertaken in this project. We use the concept of blocking situation to exemplify the Q-Rapids approach.

30 citations

Proceedings ArticleDOI
01 Aug 2018
TL;DR: The Q-Rapids quality model as mentioned in this paper is a quality model for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance, which can be found in Table 1.
Abstract: Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.

27 citations


Cited by
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Book
01 Jan 1988
TL;DR: In this paper, the evolution of the Toyota production system is discussed, starting from need, further development, Genealogy of the production system, and the true intention of the Ford system.
Abstract: * Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

1,793 citations

01 Jan 2016
TL;DR: Dillman and Smyth as mentioned in this paper described the Tailored design method as a "tailored design methodology" and used it in their book "The Tailored Design Method: A Manual for Personalization".
Abstract: Resena de la obra de Don A. Dillman, Jolene D. Smyth y Leah Melani Christian: Internet, Phone, Mail and Mixed-Mode Surveys. The Tailored Design Method. New Jersey: John Wiley and Sons

1,467 citations

01 Sep 2015
TL;DR: Subsequently, an agreement on technical co-operation between ISO and CEN was approved by the ISO Council resolution 18/1990 and the CEN General Assembly resolution 3/1990.
Abstract: Subsequently, an agreement on technical co-operation between ISO and CEN was approved by the ISO Council resolution 18/1990 and the CEN General Assembly resolution 3/1990. This agreement (called the Vienna Agreement) was published in June 1991. It is accompanied by common ISO-CEN “Guidelines for the TC/SC Chairmen and Secretariats for implementation”, approved in 1992 and revised in September 1998.

260 citations

01 Jan 2017
TL;DR: In this paper, the authors introduce several probabilistic techniques to classify app reviews into four types: bug reports, feature requests, user experiences, and text ratings, using review metadata such as the star rating and the tense, as well as, text classification, natural language processing, and sentiment analysis techniques.
Abstract: App stores like Google Play and Apple AppStore have over 3 million apps covering nearly every kind of software and service. Billions of users regularly download, use, and review these apps. Recent studies have shown that reviews written by the users represent a rich source of information for the app vendors and the developers, as they include information about bugs, ideas for new features, or documentation of released features. The majority of the reviews, however, is rather non-informative just praising the app and repeating to the star ratings in words. This paper introduces several probabilistic techniques to classify app reviews into four types: bug reports, feature requests, user experiences, and text ratings. For this, we use review metadata such as the star rating and the tense, as well as, text classification, natural language processing, and sentiment analysis techniques. We conducted a series of experiments to compare the accuracy of the techniques and compared them with simple string matching. We found that metadata alone results in a poor classification accuracy. When combined with simple text classification and natural language preprocessing of the text--particularly with bigrams and lemmatization--the classification precision for all review types got up to 88---92 % and the recall up to 90---99 %. Multiple binary classifiers outperformed single multiclass classifiers. Our results inspired the design of a review analytics tool, which should help app vendors and developers deal with the large amount of reviews, filter critical reviews, and assign them to the appropriate stakeholders. We describe the tool main features and summarize nine interviews with practitioners on how review analytics tools including ours could be used in practice.

96 citations

Journal Article
TL;DR: On-Line Analytical Processing systems based on multidimensional databases are essential elements of decision support, but most existing data is stored in “ordinary” relational OLTP databases, i.e., data has to be (re-) modeled as multiddimensional cubes before the advantages of OLAP tools are available.
Abstract: On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential elements of decision support. However, most existing data is stored in ordinary relational OLTP databases, i.e., data has to be (re-) modeled as multidimensional cubes before the advantages of OLAP tools are available. In this paper we present an approach for the automatic construction of multidimensional OLAP database schemas from existing relational OLTP databases, enabling easy OLAP design and analysis for most existing data sources. This is achieved through a set of practical and effective algorithms for discovering multidimensional schemas from relational databases. The algorithms take a wide range of available metadata into account in the discovery process, including functional and inclusion dependencies, and key and cardinality information.

77 citations