Tarkvara käitusaja andmed: arendusteabe visualiseerimine ja integreerimine - juhtumiuuring
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2019
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Abstract
Tarkvara kvaliteet on tarkvaraarenduse protsessi üks peamisi aspekte. Kuigi tarkvaraarenduse ja kasutuse (käitusaja) protsessid toodavad erinevat tüüpi andmeid, on ettevõtetel vähe toetust, et saada õigel ajal andmete põhjal arusaadavat ja tegutsema panevat teavet. Praktikud seisavad silmitsi tarkvaraprobleemide kindlakstegemise väljakutsega varase tarkvaraarenduse etappide ajal. Magistritöö eesmärk oli pakkuda reaalajas tegutsevat teavet tarkvarasüsteemide kasutamise ajal esinevate käitusvigade ja krahhide kohta ning uurida selle integreerimist arendusteabega. See töö on tehtud projekti Q-Rapids raames Fraunhoferi Eksperimentaalse Tarkvaratehnika Instituudis (IESE). Valitud juhtum on sise-nutika küla projekt - Digitale Dörfer (DD). Uurimistöö peamisteks panusteks on: a) DD projektist saadaolevate käitusaja andmete kogumine; b) sprintide planeerimise käigus otsuste tegemiseks juhtpaneelide loomine; c) CRISP-DM meetodi rakendamine tarkvara käitusaja ja arendusteabe integreerimiseks. Pakutavad ühendused ja integratsiooni skriptid on korduvkasutatavad. Edasisteks uuringuteks võib kasutada kaudseid raskusi ja õppetunde, mis on saadud tarkvara käitusaja ja arendusteabe integreerimisest.
Software quality is one of the key aspects of the software development process. Although software development and usage (runtime) processes produce a different type of data, there is little support for companies to obtain insightful and actionable information from data at the right time. Practitioners face a challenge in identifying software problems during the early software development stages. The goal of the master thesis was to provide actionable real-time information about runtime errors and crashes during the usage of software systems and explore its integration with development data. This work has been done within the project Q-Rapids at Fraunhofer IESE. The selected case is the internal smart village project - Digitale Dörfer (DD). The main contributions of the thesis are: a) collecting available runtime data from the DD the project; b) creating dashboards to make decisions during sprint planning; c) applying CRISP-DM method to the integration of software runtime and development data. The provided connectors and integration scripts are reusable. Reported challenges and lessons learned from the integration of software runtime and development data may be used for further research.
Software quality is one of the key aspects of the software development process. Although software development and usage (runtime) processes produce a different type of data, there is little support for companies to obtain insightful and actionable information from data at the right time. Practitioners face a challenge in identifying software problems during the early software development stages. The goal of the master thesis was to provide actionable real-time information about runtime errors and crashes during the usage of software systems and explore its integration with development data. This work has been done within the project Q-Rapids at Fraunhofer IESE. The selected case is the internal smart village project - Digitale Dörfer (DD). The main contributions of the thesis are: a) collecting available runtime data from the DD the project; b) creating dashboards to make decisions during sprint planning; c) applying CRISP-DM method to the integration of software runtime and development data. The provided connectors and integration scripts are reusable. Reported challenges and lessons learned from the integration of software runtime and development data may be used for further research.