Software, Volume 1, Issue 2 (June 2022) – 3 articles

The Orthanc server is a light-weight open-source picture imaging and archiving system (PACS) used to store digital imaging and communications in medicine (DICOM) data. It is widely used in research environments as it is free, open-source and scalable. To enable the use of Orthanc stored radiotherapy (RT) data in data mining and machine learning tasks, the records need to be extracted, validated, linked, and presented in a usable format. This paper reports patient data collection and processing (PDCP), a set of tools created using python for extracting, transforming, and loading RT data from Orthanc PACs. PDCP enables querying, retrieving, and validating patient imaging summaries; analysing associations between patient DICOM data; retrieving patient imaging data into a local directory; preparing the records for use in various research questions; tracking the patient’s data collection process and identifying reasons behind excluding patient’s data. PDCP targeted simplifying the data preparation process in such applications, and it was made expandable to facilitate additional data preparation tasks. Full article

Practitioners perceive software productivity as one of the most important subjects of software engineering (SE) because it connects technical to social and economic aspects. Nonetheless, software processes are complex and productivity means different things to different people. In order to realize the full contribution of software productivity research to the industrial practice of SE, the analysis and synthesis of existing practitioner viewpoints and concerns are required. A systematic mapping study is developed here to investigate the existence of diverse empirical perceptions of productivity within the distinct business sectors and knowledge areas covered by the industrial practice of SE, also identifying the commonalities among them. This study adopts the DBLP and Scopus search engines to identify bibliographic references from 1987 to 2021 related to software productivity. References that do not correspond to complete not-later-subsumed articles published in peer-reviewed journals and proceedings are excluded from the analyses. Only papers reporting on empirical studies based on software industry data or that present industry practitioner viewpoints are included in these analyses. In total, 99 papers are analyzed. The mapping found great variability in study findings, particularly concerning the impacts of agile development practices on software productivity. The systematic mapping also drew methodological recommendations to help industry practitioners address this subject and develop further research. Full article

The modeling of system non-functional properties is a broad field. Among these properties, dependability is an important one for real-time and embedded systems. On the other hand, UML offers the profiling mechanism to address specific modeling domains. In particular, the DAM (dependability analysis and modeling) profile provides a modeling framework for dependability in the model-driven paradigm. This work is for practitioners to understand the basics of dependability modeling, using DAM. In this sense, the paper digests the literature to understand the concept of the UML profile, the MARTE profile and to obtain a practical guide on dependability modeling using DAM. The modeling approach is illustrated through a case study taken from the literature. Full article