Causal Mechanism Graph ─ A new notation for capturing cause-effect knowledge in software dependability. (February 2017)

• Record Type: Journal Article
• Authors: Huang, Fuqun; Smidts, Carol
• Is Part Of: Reliability engineering & system safety. Volume 158(2017)
• Page Start: 196
• Page End: 212
• Publication Date: 2017-02
• Subjects: Causal mechanism -- Software dependability -- Causal mechanism graph -- Dependability assessment -- Expert opinion elicitation -- Cognitive map; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2016.08.020
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: Understanding cause-effect relations between concepts in software dependability engineering is fundamental to various research or industrial activities. Cognitive maps are traditionally used to elicit and represent such knowledge; however they seem incapable of accurately representing complex causal mechanisms in dependability engineering. This paper proposes a new notation called Causal Mechanism Graph (CMG) to elicit and represent the cause-effect domain knowledge embedded in experts' minds or described in the literature. CMG contains a new set of symbols elicited from domain experts to capture the recurring interaction mechanisms between multiple concepts in software dependability engineering. Furthermore, compared to major existing graphic methods, CMG is particularly robust and suitable for mental knowledge elicitation: it allows one to represent the full range of cause-effect knowledge, accurately or fuzzily as one sees fit depending on the depth of knowledge he/she has. This feature combined with excellent reliability and validity poses CMG as a promising method that has the potential to be used in various areas, such as software dependability requirement elicitation, software dependability assessment and dependability risk control. Highlights: A new notation CMG for capturing cause-effect conceptual knowledge in software dependability. CMG is particularly robust and suitable for mental knowledge representation. CMG is a visual representation that bridges mental knowledge, natural and mathematical language. CMG possesses excellent representation capability, validity and inter-coder reliability. CMG is a fundamental method for various areas in dependability engineering.