A Formal Definition of Complex Software

Aiguier, Marc; Gall, Pascale Le; Mabrouki, Mbarka

doi:10.1109/icsea.2008.59

Cited by 12 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A complex system is characterized by emergence of global properties that are very difficult, if not impossible, to anticipate just from a complete knowledge of component behaviors. 7 Emergence, hierarchical organization, and numerosity are some of the characteristics of complex systems. 27 The perspective of complexity used in this paper is with respect to the degree of difficulty in accurately predicting the future behavior.…”

Section: Complexitymentioning

confidence: 99%

Section: Related Work and Challenges In Architecting Complex Systems mentioning

confidence: 99%

“…Complex systems are characterized by emergence of global properties that are very difficult, if not impossible, to anticipate just from a complete knowledge of component behaviors. 7 Architecting such modern complex systems and SoS poses challenges due to the significant uncertainty and perceptions associated with making architecture design decisions. This decision-making spans multiple functional disciplines and knowledge areas.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Decision learning framework for architecture design decisions of complex systems and system‐of‐systems

Raman

D’Souza

2019

Systems Engineering

View full text Add to dashboard Cite

Architecting complex systems and complex system‐of‐systems (SoS) have evinced keen interest recently. Architectural design decisions have a significant bearing on the operational measures of success, referred to as Measures of Effectiveness (MOEs), of the systems and SoS. Architecting complex systems and SoS involves making architecture design decisions despite uncertainty (due to knowledge gaps) on the implications associated with the decisions. The learning of whether the decision is optimal or not, and the impact on the MOEs and the emergent behavior of the SoS, often occur later, resulting in Learning Cycles. This paper proposes an integrated decision learning framework for architecture design decisions for complex systems and SoS. The proposed framework adopts a decision oriented view that factors the uncertainty associated with architectural decisions and the learning cycles and feedback loops experienced. The framework enables leverage of machine learning approaches to learn from the decision learning cycles experienced and factor it into the uncertainty assessments of the decisions. By inculcating various aspects such as knowledge gaps and learning cycles, by building models such as Learning Cycle Model and Uncertainty Model, and by incorporating deployment approaches such as codification of decision attributes and decision uncertainty assessments, the proposed framework enables progressive maturity of the architectural knowledge base and aids robustness in architecture design decisions.

show abstract

Section: Complexitymentioning

confidence: 99%

Section: Related Work and Challenges In Architecting Complex Systems mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Decision learning framework for architecture design decisions of complex systems and system‐of‐systems

Raman

D’Souza

2019

Systems Engineering

View full text Add to dashboard Cite

show abstract

“…In a general sense, the adjective "complex" describes a system or component that by design or function or both is difficult to understand and verify. A complex system is characterized by emergence of global properties which are very difficult, if not impossible, to anticipate just from a complete knowledge of component behaviors (Aiguier et al, 2008). Emergence, hierarchical organization and numerosity are some of the characteristics of complex systems (Ladyman et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

An Approach for Formal Verification of Machine Learning based Complex Systems

Raman

Jeppu

2019

INCOSE International Symp

View full text Add to dashboard Cite

A complex system is characterized by emergence of global properties which are very difficult, if not impossible, to anticipate just from complete knowledge of component behaviors. Emergence, hierarchical organization and numerosity are some of the characteristics of complex systems. With increasing system complexity, achieving confidence in systems becomes increasingly difficult. With the recent trend towards significant footprint of complex system's functionality being governed by machine learning based models and algorithms, there is a need to ensure that emergent behavior associated with such systems are well analyzed and understood. Traditional verification and validation approaches are often inadequate to bring in the nuances of potential emergent behavior, which may be positive or negative. This paper describes a novel approach towards application of formal methods for analyzing and evaluating emergent behavior of complex systems that are governed by machine learning models. The proposed approach involves developing a machine learning classifier model that learns on potential negative and positive emergent behaviors, and leveraging the classifier in a formal verification model checking environment to assert negative emergent behavior. The approach is illustrated through an example of a pitch control system of an aircraft. The effectiveness and performance of the approach are quantified.

show abstract

“…This is referred to as use complexity: that part of task complexity that originates from the software rather than from other elements in the task environment, including the user. Unlike design complexity, which is the degree to which a program exhibits emergent behavior [1], use complexity is a measure of the learning requirements (and therefore the documentation requirements) for a particular software system.…”

Section: Introductionmentioning

confidence: 99%

Assessing Use Complexity of Software: A Tool for Documentation Designers

Loggem

2012

Human-Centered Software Engineering

View full text Add to dashboard Cite

One way to support end users of software is to provide documentation materials such as user manuals and online Help. As not all software is equally difficult to master, documentation designers need to determine the quality and quantity of the information to be included in the user documentation. A first step towards this end would be to assess the complexity of the software from the user's point of view. This paper suggests one approach to such an assessment, based on the idea of use complexity as a multidimensional construct. A consideration of width, depth and height of use complexity can help designers determine documentation requirements.

show abstract

A Formal Definition of Complex Software

Cited by 12 publications

References 14 publications

Decision learning framework for architecture design decisions of complex systems and system‐of‐systems

Decision learning framework for architecture design decisions of complex systems and system‐of‐systems

An Approach for Formal Verification of Machine Learning based Complex Systems

Assessing Use Complexity of Software: A Tool for Documentation Designers

Contact Info

Product

Resources

About