Evolution in Software Systems: Foundations of the SPE Classification Scheme

Cook, Stephen; Harrison, Rachel; Lehman, M. M.; Wernick, Paul

doi:10.1002/0470871822.ch5

Cited by 18 publications

(21 citation statements)

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“…We have found conceptual similarities between the descriptions of punctuated equilibrium and SOC, Simon's [22] research into evolution in hierarchical systems, and our own work [7] with Lehman on the foundations of SPE. In particular, we note the inherent capacity of Etype systems to evolve in unanticipated ways.…”

Section: Progressive and Punctuated Evolutionmentioning

confidence: 63%

“…In this work, we examine an approach to modelling self-organising processes that is particularly associated with Bak [1], and we consider how it can be applied to a simple model of changing evolvability in an evolving software system. Two related contributions towards a theory of software evolution are particularly relevant to this work, namely the SPE [7], [15] classification of evolving software systems and Lehman's proposed 'laws of software evolution' [17]. The SPE classification is related to evolvability in the following way:…”

Section: B Evolvability and Self-organising Processesmentioning

confidence: 99%

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A simulation model of self-organising evolvability in software systems

Cook

Harrison

Wernick

2005

IEEE International Workshop on Software Evolvability (Software-Evolvability'05)

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Abstract-The evolvability of a software artifact is its capacity for producing heritable or reusable variants; the inverse quality is the artifact's inertia or resistance to evolutionary change. Evolvability in software systems may arise from engineering and/or self-organising processes. We describe our 'Conditional Growth' simulation model of software evolution and show how it can be used to investigate evolvability from a self-organisation perspective. The model is derived from the Bak-Sneppen family of 'self-organised criticality' simulations. It shows good qualitative agreement with Lehman's 'laws of software evolution' and reproduces phenomena that have been observed empirically. The model suggests interesting predictions about the dynamics of evolvability and implies that much of the observed variability in software evolution can be accounted for by comparatively simple self-organising processes.

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Section: Progressive and Punctuated Evolutionmentioning

confidence: 63%

Section: B Evolvability and Self-organising Processesmentioning

confidence: 99%

A simulation model of self-organising evolvability in software systems

Cook

Harrison

Wernick

2005

IEEE International Workshop on Software Evolvability (Software-Evolvability'05)

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“…Operating systems such as Linux are examples of what Lehman has called E-type programs [28,11]. They are part of the infrastructure of the world in which they are used.…”

Section: Introductionmentioning

confidence: 99%

The Linux kernel as a case study in software evolution

Israeli

Feitelson

2010

Journal of Systems and Software

110

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We use 810 versions of the Linux kernel, released over a period of 14 years, to characterize the system's evolution, using Lehman's laws of software evolution as a basis. We investigate different possible interpretations of these laws, as reflected by different metrics that can be used to quantify them. For example, system growth has traditionally been quantified using lines of code or number of functions, but functional growth of an operating system like Linux can also be quantified using the number of system calls. In addition we use the availability of the source code to track metrics, such as McCabe's cyclomatic complexity, that have not been tracked across so many versions previously. We find that the data supports several of Lehman's laws, mainly those concerned with growth and with the stability of the process. We also make some novel observations, e.g. that the average complexity of functions is decreasing with time, but this is mainly due to the addition of many small functions.

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“…Of particular importance is the work of in [14] where the authors studied software changes and considered software systems as dynamic entities that change over time. Lessons can also be learned from the basic SPE classification scheme which is extensively discussed in [15] and [16].…”

Section: Related Workmentioning

confidence: 99%

On Analyzing Evolutionary Changes of Web Services

Treiber

Truong

Dustdar

2009

Service-Oriented Computing – ICSOC 2007

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Abstract. Web services evolve over their life time and change their behavior. In our work, we analyze Web service related changes and investigate interdependencies of Web service related changes. We classify changes of Web services for an analysis regarding causes and effects of such changes and utilize a dedicated Web service information model to capture the changes of Web services. We show how to put changes of Web services into an evolutionary context that allows us to develop a holistic perspective on Web services and their stakeholders in a ecosystem of Web services.

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Evolution in Software Systems: Foundations of the SPE Classification Scheme

Cited by 18 publications

References 0 publications

A simulation model of self-organising evolvability in software systems

A simulation model of self-organising evolvability in software systems

The Linux kernel as a case study in software evolution

On Analyzing Evolutionary Changes of Web Services

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