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Continuously Assessing and Improving Software Quality With Software Analytics Tools: A Case Study

 
: Martínez-Fernández, Silverio; Vollmer, Anna Maria; Jedlitschka, Andreas; Franch, Xavier; López, Lidia; Ram, Prabhat; Rodríguez, Pilar; Aaramaa, Sanja; Bagnato, Alessandra; Choraś, Michał; Partanen, Jari

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Volltext ()

IEEE access 7 (2019), S.68219-68239
ISSN: 2169-3536
European Commission EC
H2020; 732253; Q-Rapids
Quality-Aware Rapid Software Development
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IESE ()
Tools; Software quality; Companies; Real-time systems; Monitoring

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.

: http://publica.fraunhofer.de/dokumente/N-549156.html