Analyzing the Evolution of System Requirements: A case study of AUTOSAR at Volvo Car Group
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Typ
Examensarbete för masterexamen
Master Thesis
Master Thesis
Program
Software engineering and technology (MPSOF), MSc
Publicerad
2016
Författare
Corrado, Motta
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
BACKGROUND: The evolution of system requirements is an important and inevitable aspect of software development and maintenance. Being aware of the amount of changes as well as understanding how to measure them is advantageous not only for software engineering purposes but also in industrial contexts. OBJECTIVES: This thesis aims to efficiently analyse the evolution of system require-ments, by means of quantitative analysis based on a number of software metrics. Our goal is to facilitate the updates of large software systems with new features. METHOD: In this paper we perform quantitative analysis of the evolution of system requirements across multiple versions of large software systems. We rely on the design research methodology and we evaluate the results of our study in a case study con-ducted in collaboration with Volvo Car Group. RESULTS: We defined a set of metrics based on the existing studies, such as the Re-quirement maturity index, and we refined their input data by building the taxonomy of changes. Furthermore, we designed a metric, named Accuracy, for testing the reliabil-ity of the requirements. The empirical results assess the quality of the metrics and offer a way to monitor the requirements evolution considering the history of changes. CONCLUSION: We concluded that quantitative analysis of requirements evolution using the proposed metrics can help different industrial organisations in managing software evolution by facilitating the adoption of new features in large software systems. This is achieved by visualizing the extent of the requirements evolution and indicating which requirements are mostly unstable.
Beskrivning
Ämne/nyckelord
Data- och informationsvetenskap , Computer and Information Science