Laws of software evolution revisited

Lehman, M. M.

doi:10.1007/bfb0017737

Cited by 355 publications

(285 citation statements)

References 3 publications

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“…In presenting the practical implications of the FEAST work to date, the paper follows the order in which the laws of software evolution [Lehman 1974[Lehman , 1997Lehman and Belady 1985;] and other concepts and principles [Lehman and Belady 1985;Lehman 1989Lehman , 1990 were formulated. This ordering has, however, only historical significance.…”

Section: Introductionmentioning

confidence: 99%

Rules and Tools for Software Evolution Planning and Management

Lehman

Fernáandez‐Ramil

2006

Software Evolution and Feedback

110

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Abstract. When first formulated in the early seventies, the laws of software evolution were, for a number of reasons, not widely accepted as relevant to software engineering practice. Over the years, however, they have gradually become recognised as providing useful inputs to understanding of the software process. Now eight in number, they have been supplemented by the software uncertainty principle and the FEAST (Feedback, Evolution And Software Technology) hypothesis. Based on all these and on the further results of the FEAST research projects this paper develops and presents some fifty rules for application in software system process planning and management and indicates tools available or that could usefully be developed to support their application. The listing is structured according to the laws that encapsulate the observed phenomena and that lead to the recommendations. Each sublist is preceded by a textual discussion providing at least some of the reasoning that has led to the recommended procedures. The references direct the interested reader to the literature that records observed behaviours, interpretations, models and metrics obtained from industrially evolved systems, and from which the recommendations were derived.

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Section: Introductionmentioning

confidence: 99%

Rules and Tools for Software Evolution Planning and Management

Lehman

Fernáandez‐Ramil

2006

Software Evolution and Feedback

110

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“…Lee et al [9] provide an overview of open source software evolution with software metrics. The authors explored the evolution of an open source software system in terms of size, coupling and cohesion, and discuss its quality change based on the Lehman's laws of evolution [4], [5], [27]. Jermakovics et al [28] propose an approach to visually identify software evolution patterns related to requirements.…”

Section: Related Workmentioning

confidence: 99%

Metrics and Software Quality Evolution: A Case Study on Open Source Software

Drouin¹,

Badri²,

Touré³

2013

IJCTE

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Abstract-This paper aims at analyzing empirically the quality evolution of an open source software using metrics. We used a control flow based metric (Quality Assurance IndicatorQi) which we proposed in a previous work. We wanted to investigate if the Qi metric can be used to observe how quality evolves along the evolution of the successive released versions of the subject software system. We addressed software quality from an internal perspective. We performed an empirical analysis using historical data on the subject system (Apache Tomcat). The collected data cover, in fact, a period of more than seven years (thirty-one versions in total). Empirical results provide evidence that the Qi metric reflects properly the quality evolution of the subject system.

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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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Laws of software evolution revisited

Cited by 355 publications

References 3 publications

Rules and Tools for Software Evolution Planning and Management

Rules and Tools for Software Evolution Planning and Management

Metrics and Software Quality Evolution: A Case Study on Open Source Software

On Analyzing Evolutionary Changes of Web Services

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