TY - GEN A1 - Hesse, Günter A1 - Matthies, Christoph A1 - Sinzig, Werner A1 - Uflacker, Matthias T1 - Adding Value by Combining Business and Sensor Data BT - an Industry 4.0 Use Case T2 - Database Systems for Advanced Applications N2 - Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs. KW - Industry 4.0 KW - Internet of Things KW - Data integration Y1 - 2019 SN - 978-3-030-18590-9 SN - 978-3-030-18589-3 U6 - https://doi.org/10.1007/978-3-030-18590-9_80 SN - 0302-9743 SN - 1611-3349 VL - 11448 SP - 528 EP - 532 PB - Springer CY - Cham ER - TY - GEN A1 - Matthies, Christoph T1 - Agile process improvement in retrospectives T2 - 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) N2 - Working in iterations and repeatedly improving team workflows based on collected feedback is fundamental to agile software development processes. Scrum, the most popular agile method, provides dedicated retrospective meetings to reflect on the last development iteration and to decide on process improvement actions. However, agile methods do not prescribe how these improvement actions should be identified, managed or tracked in detail. The approaches to detect and remove problems in software development processes are therefore often based on intuition and prior experiences and perceptions of team members. Previous research in this area has focused on approaches to elicit a team's improvement opportunities as well as measurements regarding the work performed in an iteration, e.g. Scrum burn-down charts. Little research deals with the quality and nature of identified problems or how progress towards removing issues is measured. In this research, we investigate how agile development teams in the professional software industry organize their feedback and process improvement approaches. In particular, we focus on the structure and content of improvement and reflection meetings, i.e. retrospectives, and their outcomes. Researching how the vital mechanism of process improvement is implemented in practice in modern software development leads to a more complete picture of agile process improvement. KW - Agile KW - Scrum KW - software process improvement KW - retrospective Y1 - 2019 SN - 978-1-7281-1764-5 SN - 978-1-7281-1765-2 U6 - https://doi.org/10.1109/ICSE-Companion.2019.00063 SN - 2574-1934 SN - 2574-1926 SP - 150 EP - 152 PB - IEEE CY - New York ER - TY - GEN A1 - Matthies, Christoph T1 - Feedback in Scrum BT - Data-Informed Retrospectives T2 - 2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) N2 - Improving the way that teams work together by reflecting and improving the executed process is at the heart of agile processes. The idea of iterative process improvement takes various forms in different agile development methodologies, e.g. Scrum Retrospectives. However, these methods do not prescribe how improvement steps should be conducted in detail. In this research we investigate how agile software teams can use their development data, such as commits or tickets, created during regular development activities, to drive and track process improvement steps. Our previous research focused on data-informed process improvement in the context of student teams, where controlled circumstances and deep domain knowledge allowed creation and usage of specific process measures. Encouraged by positive results in this area, we investigate the process improvement approaches employed in industry teams. Researching how the vital mechanism of process improvement is implemented and how development data is already being used in practice in modern software development leads to a more complete picture of agile process improvement. It is the first step in enabling a data-informed feedback and improvement process, tailored to a team's context and based on the development data of individual teams. KW - agile KW - software development KW - Scrum KW - retrospective KW - software process improvement Y1 - 2019 SN - 978-1-7281-1764-5 SN - 978-1-7281-1765-2 U6 - https://doi.org/10.1109/ICSE-Companion.2019.00081 SN - 2574-1934 SN - 2574-1926 SP - 198 EP - 201 PB - IEEE CY - New York ER -