Data-Driven Elicitation, Assessment and Documentation of Quality Requirements in Agile Software Development

Franch, Xavier; Gómez, Cristina; Jedlitschka, Andreas; López, Lidia; Martínez‐Fernández, Silverio; Oriol, Marc; Partanen, Jari

doi:10.1007/978-3-319-91563-0_36

Cited by 19 publications

(31 citation statements)

References 33 publications

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“…Recent approaches suggest using data-driven methods to facilitate this elicitation [61] if the system already produces data. New proposals capable of automatically generating NFRs, as the one presented in [62], may change the perception of the importance of NFRs.…”

Section: What Benefits Can the Management Of Nfrs Bring To Companies mentioning

confidence: 99%

Dealing with Non-Functional Requirements in Model-Driven Development: A Survey

Ameller

Franch

Gómez

et al. 2021

IIEEE Trans. Software Eng.

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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.

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Section: What Benefits Can the Management Of Nfrs Bring To Companies mentioning

confidence: 99%

Dealing with Non-Functional Requirements in Model-Driven Development: A Survey

Ameller

Franch

Gómez

et al. 2021

IIEEE Trans. Software Eng.

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“…These quality alerts enable actionable analytics. These actions can be added to the product backlog of the next RSD cycle and, hence, increase the transparency of decision-making [10].…”

Section: Discussionmentioning

confidence: 99%

A Quality Model for Actionable Analytics in Rapid Software Development

Martínez‐Fernández

Jedlitschka

Guzmán

et al. 2018

2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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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 semistructured 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.

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“…Finally, QFs are aggregated into Strategic Indicators. More details on the Q-Rapids Quality Model and Q-Rapids approach can be found in [12,13].…”

Section: The Q-rapids Approachmentioning

confidence: 99%

Using Bayesian Networks to estimate Strategic Indicators in the context of Rapid Software Development

Manzano

Mendes

Gómez

et al. 2018

Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering

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Background: During Rapid Software Development, a large amount of project and development data can be collected from different and heterogeneous data sources. Aims: Design a methodology to process these data and turn it into relevant strategic indicators to help companies make meaningful decisions. Method: We adapt an existing methodology to create and estimate strategic indicators using Bayesian Networks in the context of Rapid Software Development, and applied it to a use case. Results: Applying the methodology in the use case, we create a model to predict product quality based on software factors and metrics, using companies' business knowledge and collected data. Conclusions: We proved the methodology's feasibility and obtained positive feedback from the company's use case. CCS CONCEPTS• Software and its engineering → Software creation and management KEYWORDS Strategic indicator, Bayesian Network, Decision Making, Rapid software development

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Data-Driven Elicitation, Assessment and Documentation of Quality Requirements in Agile Software Development

Cited by 19 publications

References 33 publications

Dealing with Non-Functional Requirements in Model-Driven Development: A Survey

Dealing with Non-Functional Requirements in Model-Driven Development: A Survey

A Quality Model for Actionable Analytics in Rapid Software Development

Using Bayesian Networks to estimate Strategic Indicators in the context of Rapid Software Development

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