A graph model for software evolution

Luqi,

doi:10.1109/32.57627

Cited by 71 publications

(36 citation statements)

References 11 publications

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“…Studies have shown that early parts of the system development cycle such as requirements and design specifications are especially prone to error (Luqi, 1989). Problems originating in the early stages often have a lasting influence on the reliability, safety and cost of the system.…”

Section: The Software Process Problemmentioning

confidence: 99%

“…Software development processes such the hypergraph model for software evolution (Luqi, 1989), or the spiral model , improved the state of the art. However, all of them have a common weakness: risk assessment.…”

Section: The Risk Assessment and Estimation Problemsmentioning

confidence: 99%

“…Recently, NPS developed a formal model for risk identification and assessment for evolutionary software processes that solves the problems of automation, human dependency, and estimation (Nogueira et al 2000). This research is focused on studying software project risk assessment from a different perspective, viewing risk assessment as the prediction of success of the project given a set of characteristics, a probabilistic model based on Weibull distribution, and learning from each successive cycle on the process.…”

Section: The Risk Assessment and Estimation Problemsmentioning

confidence: 99%

“…This hypothesis is far from the reality. Today, modern software processes , (Luqi, 1989) are based on evolution and prototyping. These approaches recognize the fact that software development presents an illdefined decision problem and they fail in assessing automatically the risk.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Surfing the Edge of Chaos: Applications to Software Engineering

Nogueira¹,

Jones²

2000

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This paper discusses the problems of software engineering as the weakest link in the development of systems capable of achieving information superiority. Fast changes in technology introduce additional difficulties in terms of strategic planning, organizational structure, and engineering of software development projects. In such complex environment, a new way of thinking is required. We analyze the introduction of complex adaptive systems as an alternative for planning and change. The strategy of "competing on the edge" is analyzed showing the risks and the skills required navigating on the edge. We discuss the feasibility of using this theory in software engineering as an alternative to bureaucratic software development processes. We present also some recommendations that could help to acquire competitive advantage in software development, hence achieve information superiority.

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Section: The Software Process Problemmentioning

confidence: 99%

Section: The Risk Assessment and Estimation Problemsmentioning

confidence: 99%

Section: The Risk Assessment and Estimation Problemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Surfing the Edge of Chaos: Applications to Software Engineering

Nogueira¹,

Jones²

2000

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“…It has module composition and powerful facilities to retrieve software components [17] and to support evolution [18].…”

Section: Small Large and Huge Grain Methodsmentioning

confidence: 99%

Formal methods and social context in software development

Goguen

Luqi

1995

TAPSOFT '95: Theory and Practice of Software Development

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Rapid Prototyping

Shing

Luqi

Yeh

2002

Encyclopedia of Software Engineering

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Prototypes facilitate the requirements phase for any type of software if the requirements have changed from the previous version, which is usually the case. Prototypes can demonstrate system scenarios to the affected parties as a way to ( 1 ) collect criticisms and feedback for updated requirements, ( 2 ) detect deviations from users' expectations early, ( 3 ) trace the evolution of the requirements, ( 4 ) improve the communication and integration of the users and the development personnel, and ( 5 ) provide early warning of mismatches between proposed software architectures and the conceptual structure of requirements. The benefits of prototyping are widely accepted. The main incentive for using prototypes is economic—scale models and prototype versions of most systems are much less expensive to build than are the final versions. Prototypes should therefore be used to evaluate proposed systems if acceptance by the customer or the feasibility of development is in doubt. The need for software prototyping has become more urgent as systems being developed have grown more complex, are more likely to have requirements errors, and are more expensive to implement. Particularly, in real‐time applications where severe time constraints impose more challenges, the use of prototypes helps to describe the requirements in a clear, precise, consistent and executable format. Prototyping is a class of software development methods that use software prototypes of the envisioned system. A prototype is an executable model of a proposed system that accurately reflects a chosen subset of its properties, such as display formats, computed results, or response times. Prototypes are useful for formulating and validating requirements, resolving technical design issues, and supporting computer aided design of both software and hardware components of proposed systems. Rapid prototyping refers to the capability to create a prototype with significantly less effort than it takes to produce an implementation for operational use. Rapid prototyping usually implies some degree of automated code generation.

show abstract

A graph model for software evolution

Cited by 71 publications

References 11 publications

Surfing the Edge of Chaos: Applications to Software Engineering

Surfing the Edge of Chaos: Applications to Software Engineering

Formal methods and social context in software development

Rapid Prototyping

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