Continuously assessing and improving software quality with software analytics tools: a case study
Silverio Martínez-Fernández, Anna Maria Vollmer, Andreas Jedlitschka, Xavier Franch, Lidia López, Prabhat Ram, Pilar Rodríguez, Sanja Aaramaa, Alessandra Bagnato, Michał Choraś and Jari Partanen
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 software quality has also been a key target 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 study 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 one year, the 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. 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 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.
This year I'm organising the International Workshop of i* jointly to Joao Pimentel and Juan Pablo Carvallo. You can find the workshop details at iStar18 website.
This is the first time the workshop will be co-located to the The International Conference on Conceptual Modeling (ER'19).
OSSMMOsIs, an Open Innovation
Maturity Model oriented to Open
Source Software Adoption
Lucia Mendez, Lidia Lopez, Juan P. Carvallo, Claudia P. Ayala and Catalina Peña
Abstract. Nowadays, is well-known that Open Source Software (OSS) offer attractive benefits (like time-to-market reduction, good software solutions, contributions to knowledge, among others), capable to generate competitive advantages but at the same time, high impact on business model, goals, processes, and risks. The main impact is related to innovations that come from both external and internal stakeholders. Therefore, the way in which an organization manages its internal innovation and opens to the external, constitutes a critical success factor for OSS adoption. We identify a lack of support in organizations to know (in terms of business goals reached) its readiness level to carry out OSS adoption projects in the environment of Open Innovation. In response, the present work proposes an Open Innovation Maturity Model oriented to Open Source Software adoption, OSSMMOsIs1, like a business support tool that facilitates this identification task in early adoption stages.
How
Practitioners Manage Quality Requirements in Rapid Software Development: A
Survey
Lidia López, Jari Partanen, Pilar Rodríguez, Silverio Martínez-Fernández
Abstract.Software quality is an essential competitive factor for the success of software companies today. Increasing software quality levels of software products and services requires an adequate integration of quality requirements (QRs) in the software life-cycle, which is still scarcely supported in current rapid software development (RSD) approaches. One of the goals of the Q-Rapids (Quality-aware Rapid Software Development) approach is to provide tool support to decision-makers for QRs management in RSD. As an initial step, we conducted a survey to explore how software development organizations using RSD manage QRs in their development process. The survey focuses on: (a) how data is gathered for assessing quality, (b) how QRs are managed, and (c) the considered QRs in their products. We received 30 answers, from these answers we can conclude that most of the companies gather data both automatically and manually for monitoring quality; QRs are managed together with functional requirements, sometimes or very often functionality gets priority over quality; and, the most reported QRs are reliability, performance, and security.
If you have experience developing in agile/rapid developments, you can help us answering the survey or helping us in its dissemination: