How changes affect software entropy: an empirical study

Canfora, Gerardo; Cerulo, Luigi; Cimitile, Marta; Penta, Massimiliano Di

doi:10.1007/s10664-012-9214-z

Cited by 57 publications

(41 citation statements)

References 18 publications

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“…Entropy has been widely applied in software engineering for various measurement on software entities and software development activities, such as software complexity entropy [5] and software change entropy [6]. Here we borrow this concept to measure how a developer's contributions on source code are distributed over time.…”

Section: Dependent Variables (Dvs)mentioning

confidence: 99%

Distribution and Continuity of Developers' Contributions in OSS Projects: A Case Study

Wang

Perry

2016

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Open Source Software (OSS) is usually developed by geographically-distributed developers in a collaborative manner. Different developers exhibit different behaviors and make diversified contributions to OSS projects. Objective of this paper is to discover individualized characteristics and common patterns of how developers contribute to OSS projects. Continuity is used to delineate how a developer actively contributes to the project over time. Case studies on two OSS projects reveal some significant phenomena on the distribution of developers' contributions relative to absolute time and relative to the milestones (i.e., releases) of OSS projects. We have found that OSS developers' contributions exhibit the "temporal locality", and most of the releases of an OSS project are dominated by the contributions of a limited number of developers.

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Section: Dependent Variables (Dvs)mentioning

confidence: 99%

Distribution and Continuity of Developers' Contributions in OSS Projects: A Case Study

Wang

Perry

2016

International Conferences on Software Engineering and Knowledge Engineering

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“…Canfora et al [5] carried out an exploratory study on the evolution of four open source systems, namely ArgoUML, Eclipse-JDT, Mozilla, and Samba, with the aim of analyzing the relationship between source code 'change entropy' and refactoring activities (amongst others). They found that refactoring activity led to a reduction in change entropy, which can be interpreted as an improvement in maintainability.…”

Section: Does Refactoring Improve Non-functional Requirements?mentioning

confidence: 99%

Measuring refactoring benefits: a survey of the evidence

Cinnéide

Yamashita

Counsell

2016

Proceedings of the 1st International Workshop on Software Refactoring

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Refactoring has become a standard technique for software developers to use when trying to improve or evolve the design of a program. It is a key component of Agile methods, the most popular family of software development methodologies in industrial practice. Refactoring has also been the subject of much attention from researchers and many practitioner textbooks have been written on the topic. It would be natural to assume then that the benefits of refactoring would be easy agree upon, and easy to measure. In this position paper we review a selection of the empirical studies that have attempted to measure the benefits of refactoring and find the situation to be quite unclear. The evidence suggests that what motivates developers to refactor, and what benefits accrue from refactoring, are open issues that require further research.

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“…Recent studies have revealed that object-oriented software systems share some structural attributes with these complex networks. Specifically, the networks of software systems are characterized by a scale-free degree distribution [6][7][8][9][10], a small-world structure (short average path length and high clustering) [11,12] and some other features [13][14][15][16][17][18]. This therefore raises the study of software networks in recent years.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1 shows a simple example of the extraction from a software system to a software network, in which the classes in the left figure are nodes and the collaborations of such nodes are edges. For the software systems with a more complex structure, the corresponding software networks are organized to be highly functional, modularized [19] and evolvable [15]. This therefore brings some further studies on software networks, such as community detection [20,21], quality assessment [10], important unit identification [22], bug classification [23] and developer social collaboration [24,25], which are helpful to various phases in software engineering practices.…”

Section: Introductionmentioning

confidence: 99%

Multi-Level Formation of Complex Software Systems

Hao

Chen

2016

Entropy

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We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

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How changes affect software entropy: an empirical study

Cited by 57 publications

References 18 publications

Distribution and Continuity of Developers' Contributions in OSS Projects: A Case Study

Distribution and Continuity of Developers' Contributions in OSS Projects: A Case Study

Measuring refactoring benefits: a survey of the evidence

Multi-Level Formation of Complex Software Systems

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