Evolution of Feature-Oriented Software: How to Stay on Course and Avoid the Cliffs of Modularity Drift

Olszak, Andrzej; Lazarova-Molnar, Sanja; Jôrgensen, Bo Nørregaard

doi:10.1007/978-3-319-25579-8_11

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Though these projects are two wellknown systems, and are actively maintained. Olszak et al (2015) look at the drift of feature oriented modularity of an application from its ideal/ optimal modularity as it evolves. Feature oriented modularity of a software system is calculated with the help of two metrics -feature scattering, and feature tangling, that measure how it implements user observable features of the application.…”

Section: Modularity Analysismentioning

confidence: 99%

Open Source Software Evolution

Chahal

Saini

2016

International Journal of Open Source Software and Processes

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Due to the dominance of Open Source Software (OSS) in IT and the IT enabled services industry, various stakeholders are keen to understand the OSS evolution process. Several studies have been conducted in the past in this regard. There are various techniques used in the past for understanding OSS evolution process from different perspectives. This paper reports a systematic literature review on the topic in order to understand its current state and to identify opportunities for future. This research identified 190 studies, selected against a set of questions, for discussion. It categorizes the research studies into nine categories. We report the review results in a set of two papers. This paper discusses the research results of the techniques used for OSS evolution analysis only i.e. one out of the nine categories. A subsequent paper carries discussion on the remaining categories. Based on the results obtained from the systematic review, there is evidence of shift in the metrics and methods for OSS evolution analysis over the period of time. OSS systems were found to grow at a super linear rate in the initial studies. But later studies revealed that branches of an OSS system grow at different rates. However, more number of studies should be carried out using a repeatable methodology in order to obtain well-formed and generalizable results.

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Section: Modularity Analysismentioning

confidence: 99%

Open Source Software Evolution

Chahal

Saini

2016

International Journal of Open Source Software and Processes

View full text Add to dashboard Cite

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Recommending Features of Mobile Applications for Developer

Lian

Yang

et al. 2016

Advanced Data Mining and Applications

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A Systematic Review of Attributes and Techniques for Open Source Software Evolution Analysis

Saini

Chahal

2018

Advances in Systems Analysis, Software Engineering, and High Performance Computing

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Many studies have been conducted to understand the evolution process of Open Source Software (OSS). The researchers have used various techniques for understanding the OSS evolution process from different perspectives. This chapter reports a meta-data analysis of the systematic literature review on the topic in order to understand its current state and to identify opportunities for the future. This research identified 190 studies, selected against a set of questions, for discussion. It categorizes the research studies into nine categories. Based on the results obtained from the systematic review, there is evidence of a shift in the metrics and methods for OSS evolution analysis over the period of time. The results suggest that there is a lack of a uniform approach to analyzing and interpreting the results. There is need of more empirical work using a standard set of techniques and attributes to verify the phenomenon governing the OSS projects. This will help to advance the field and establish a theory of software evolution.

show abstract

Evolution of Feature-Oriented Software: How to Stay on Course and Avoid the Cliffs of Modularity Drift

Cited by 5 publications

References 22 publications

Open Source Software Evolution

Open Source Software Evolution

Recommending Features of Mobile Applications for Developer

A Systematic Review of Attributes and Techniques for Open Source Software Evolution Analysis

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