Aerospace-proven software development processes and tools in automotive environments: experience, challenges and opportunities in model-based design (Abstract only) opportunities in model-based design

Background: With the advancement in the field of software development, software poses threats and risks to customers’ data and privacy. Most of these threats are persistent because security is mostly considered as a feature or a non-functional requirement, not taken into account during the software development life cycle (SDLC). Introduction: In order to evaluate the security performance of a software system, it is necessary to integrate the security metrics during the SDLC. The appropriate security metrics adopted for each phase of SDLC aids in defining the security goals and objectives of the software as well as quantify the security in the software. Methods: This paper presents systematic review and catalog of security metrics that can be adopted during the distinguishable phases of SDLC, security metrics for vulnerability and risk assessment reported in the literature for secure development of software. The practices of these metrics enable software security experts to improve the security characteristics of the software being developed. The critical analysis of security metrics of each phase and their comparison are also discussed. Results: Security metrics obtained during the development processes help to improve the confidentiality, integrity, and availability of software. Hence, it is imperative to consider security during the development of the software, which can be done with the use of software security metrics. Conclusion: This paper reviews the various security metrics that are meditated in the copious phases during the progression of the SDLC in order to provide researchers and practitioners with substantial knowledge for adaptation and further security assessment.

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Establishing key performance indicators for measuring software-development processes at a large organization

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering ◽

10.1145/3368089.3417057 ◽

2020 ◽

Author(s):

Cem Sürücü ◽

Bianying Song ◽

Jacob Krüger ◽

Gunter Saake ◽

Thomas Leich

Keyword(s):

Software Development ◽

Performance Indicators ◽

Key Performance Indicators ◽

Large Organization ◽

Development Processes

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Recommender systems in model-driven engineering

Software & Systems Modeling ◽

10.1007/s10270-021-00905-x ◽

2021 ◽

Author(s):

Lissette Almonte ◽

Esther Guerra ◽

Iván Cantador ◽

Juan de Lara

Keyword(s):

Recommender Systems ◽

Information Filtering ◽

Research Work ◽

Model Driven Engineering ◽

Video Broadcasting ◽

Model Driven ◽

Challenges And Opportunities ◽

Mapping Review ◽

Development Processes ◽

Systematic Mapping Review

AbstractRecommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research.

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