Quality-Aware Rapid Software Development Project: The Q-Rapids Project

Franch, Xavier; López, Lidia; Martínez‐Fernández, Silverio; Oriol, Marc; Rodríguez, Pilar; Trendowicz, Adam

doi:10.1007/978-3-030-29852-4_32

Cited by 5 publications

(6 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the first iteration, we demonstrated and evaluated the QR generation and documentation architecture (see Section 5), whereas in the second iteration, we demonstrated and evaluated the tool support implementation (see Section 7). The evaluation was conducted in the four companies of the Q-Rapids consortium (Franch et al 2019), which have different profiles (one large corporation, two large/medium companies, and one SME) and produce different types of systems (e.g., from modeling tools to telecommunications software).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Data-driven and tool-supported elicitation of quality requirements in agile companies

et al. 2020

Self Cite

View full text Add to dashboard Cite

Quality Requirements (QRs) are a key artifact needed to ensure the quality and success of a software system. Despite their importance, QRs rarely get the same degree of attention as their functional counterpart in Agile Software Development (ASD) projects. Moreover, crucial information that can be obtained from software development repositories (e.g., JIRA, GitHub,…) is not fully exploited, or is even neglected, in QR elicitation activities. In this work, we present a data-driven tooled approach for the semi-automatic generation and documentation of QRs in the context of ASD. The approach is based on the declaration of thresholds over quality-related issues, whose violation triggers user-defined alerts. These alerts are used to browse a catalog of QR patterns that are presented to the ASD team by means of a dashboard that implements several analysis techniques. Once selected, the patterns generate the QRs, which are documented and stored in the product backlog. The full approach is implemented via a configurable platform. Over the course of one year, four companies differing in size and profile followed this approach and deployed the platform in their premises to semi-automatically generate QRs in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. The quantitative and qualitative analyses yielded positive results; i.e., the practitioners' perception with regard to the tool's understandability, reliability, usefulness, and relevance was positive. We conclude that the results show potential for future adoption of data-driven elicitation of QRs in agile companies and encourage other practitioners to use the presented tool and adopt it in their companies.

show abstract

Section: Methodsmentioning

confidence: 99%

“…The research was conducted in the context of the Q-Rapids H2020 project (Franch et al 2019), which enabled us to elicit real scenarios based on practitioners' needs, use the tool-supported generation and documentation of QRs in different company-provided scenarios, and evaluate it based on users' experiences and perceptions.…”

Section: Introductionmentioning

confidence: 99%

Data-driven and tool-supported elicitation of quality requirements in agile companies

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…The concepts presented in this paper have been applied in the last years in several EU collaborative projects (Q-Rapids [109], SUPERSEDE [110] and OpenReq [111]) where large corporations and small-medium enterprises have adopted DDRE at some extent. Some observations arising from these projects follow:…”

Section: Lessons Learnedmentioning

confidence: 99%

Data-Driven Requirements Engineering: A Guided Tour

Franch

2021

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

Data-driven approaches are becoming dominant in almost every single software engineering activity, and requirements engineering is not the exception. The analysis of data coming from several sources may indeed become an extremely useful input to requirements elicitation and management. However, benefits do not come for free. Techniques such as natural language processing and machine learning are difficult to master and require high-quality data and specific competences from different fields, whilst their generalization remains as a challenge. This paper introduces the main concepts behind data-driven requirements engineering, provides an overview of the state of the art in the field and identifies the main challenges to be addressed.

show abstract

“…The Q-Rapids platform is an advanced data-driven platform to manage quality in Agile and Rapid Software Development. Details on the consolidated version (phase 3) are described in [2]. Q-Rapids platform assists decision makers to make informed decisions by means of:…”

Section: Achieved Outcomesmentioning

confidence: 99%

“…The current framework is completed and the summative evaluation is being reported. A detailed overview of the project is described in[2].…”

mentioning

confidence: 99%

Q-Rapids: Quality-Aware Rapid Software Development – An H2020 Project

López

Oriol

2019

Product-Focused Software Process Improvement

Self Cite

View full text Add to dashboard Cite

This work reports the objectives, current state, and outcomes of the Q-Rapids H2020 project. Q-Rapids (Quality-Aware Rapid Software Development) proposes a data-driven approach to the production of software following very short development cycles. The focus of Q-Rapids is on quality aspects, represented through quality requirements. The Q-Rapids platform, which is the tangible software asset emerging from the project, mines software repositories and usage logs to identify candidate quality requirements that may ameliorate the values of strategic indicators like product quality, time to market or team productivity. Four companies are providing use cases to evaluate the platform and associated processes.

show abstract

Quality-Aware Rapid Software Development Project: The Q-Rapids Project

Cited by 5 publications

References 18 publications

Data-driven and tool-supported elicitation of quality requirements in agile companies

Data-driven and tool-supported elicitation of quality requirements in agile companies

Data-Driven Requirements Engineering: A Guided Tour

Q-Rapids: Quality-Aware Rapid Software Development – An H2020 Project

Contact Info

Product

Resources

About