Relation of Code Clones and Change Couplings

Geiger, Reto; Fluri, Beat; Gall, Harald; Pinzger, Martin

doi:10.1007/11693017_31

Cited by 57 publications

(55 citation statements)

References 19 publications

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“…Instead, we are primarily interested in identifying the evolution patterns of a set of clones detected in the software system (in a release) and relating the evolution pattern with other variables (clone radius, clone granularity, cloned code fault-proneness). By excluding new clone classes (or just new clone fragments) 21 occurring in future snapshots, we limit the age difference of clones we are considering in the study. is a free version of the SSH connectivity tools implemented in ANSI C and used to provide a secure channel between network connections.…”

Section: Contextmentioning

confidence: 99%

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An empirical study on the maintenance of source code clones

et al. 2009

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Code cloning has been very often indicated as a bad software development practice. However, many studies appearing in the literature indicate that this is not always the case. In fact, either changes occurring in cloned code are consistently propagated, or cloning is used as a sort of templating strategy, where cloned source code fragments evolve independently. This paper (i) proposes an automatic approach to classify the evolution of source code clone fragments, and (ii) reports a fine-grained analysis of clone evolution in four different Java and C software systems, aimed at investigating to what extent clones are consistently propagated or they evolve independently. Also, the paper investigates the relationship between the presence of clone evolution patterns and other characteristics such as clone raSuresh Thummalapenta North Carolina State University, Raleigh, USA E-mail: sthumma@ncsu.edu Luigi Cerulo, Lerina Aversano, Massimiliano Di Penta Department of Engineering -University of Sannio, Benevento, Italy E-mail: lcerulo@unisannio.it, aversano@unisannio.it, dipenta@unisannio.it 2 dius, clone size and the kind of change the clones underwent, i.e., corrective maintenance or enhancement.

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Section: Contextmentioning

confidence: 99%

“…The relationship between clones and change couplings has been examined by Geiger et al [21]. They proposed a framework to examine code clones and relate them to change couplings taken from release history analysis.…”

Section: Clone Genealogy and Tracingmentioning

confidence: 99%

An empirical study on the maintenance of source code clones

et al. 2009

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“…Geiger et al showed some relations between code clones and logical couplings [32]. Since code clones cannot be fully captured by call dependencies and data dependencies, some parts of logical couplings are not covered by ImpactScale.…”

Section: Threats To Validitymentioning

confidence: 99%

ImpactScale: Quantifying change impact to predict faults in large software systems

Kobayashi

Matsuo

Inoue

et al. 2011

2011 27th IEEE International Conference on Software Maintenance (ICSM)

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Abstract-In software maintenance, both product metrics and process metrics are required to predict faults effectively. However, process metrics cannot be always collected in practical situations. To enable accurate fault prediction without process metrics, we define a new metric, ImpactScale. ImpactScale is the quantified value of change impact, and the change propagation model for ImpactScale is characterized by probabilistic propagation and relation-sensitive propagation. To evaluate ImpactScale, we predicted faults in two large enterprise systems using the effort-aware models and Poisson regression. The results showed that adding ImpactScale to existing product metrics increased the number of detected faults at 10% effort (LOC) by over 50%. ImpactScale also improved the predicting model using existing product metrics and dependency network measures.

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“…Historical data on the changes of open-source systems allowed researchers to empirically investigate on the evolution of various software entities, such as clones [10,14] or design motifs [2]. Some studies considered changes between releases, i.e., stable snapshots released after some amount of changes, while others exploited the historical data available in versioning systems, such as CVS or SVN.…”

Section: Related Workmentioning

confidence: 99%