Empirical Analysis of the Complexity Evolution in Open-Source Software Systems

Alenezi, Mamdouh; Mellouli, Khaled; Arabia, Saudi

doi:10.14257/ijhit.2015.8.2.24

Cited by 21 publications

(20 citation statements)

References 39 publications

(30 reference statements)

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“…As software complexity is the result of implementation details, design decisions, and algorithm choices, it can be used to predict various characteristics of software quality, e.g. maintainability [16,1]. An example can be taken from the case of highly complex modules that are found to be more vulnerable to faults [25].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, it is highly imperative to monitor and control any software in order to successfully complete the project. It was showed by the research conducted in the field of software engineering that the presence of documentation in a software development project assures the quality of the code of complex functions and the design [1].…”

Section: Introductionmentioning

confidence: 99%

“…Many developers face difficulty in understanding the complicated structures of software units. What makes this problem more difficult is that the complexity level can be varying even in the solution of the same problem, depending on the variation of the implementations [1]. The software also continuously evolves according to user requirement and for this, the software has to be updated on a regular basis which consequently increases the complexity of the software [1].…”

Section: Introductionmentioning

confidence: 99%

“…What makes this problem more difficult is that the complexity level can be varying even in the solution of the same problem, depending on the variation of the implementations [1]. The software also continuously evolves according to user requirement and for this, the software has to be updated on a regular basis which consequently increases the complexity of the software [1]. Whereas, in order to ensure a smooth update process for additional features and bug fixes, it is highly important to keep the complexity of the system to the minimum level [1].…”

Section: Introductionmentioning

confidence: 99%

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On the Relationship between Software Complexity and Security

Alenezi¹,

Zarour²

2020

IJSEA

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This work aims at discussing the complexity aspect of software while demonstrating its relationship with security. Complexity is an essential part of software; however, numerous studies indicate that they increase the vulnerability of the software systems and introduce bugs in the program. Many developers face difficulty when trying to understand the complex components of software. Complexity in software increases when objects in the software are used to design a more complex object while creating a hierarchical complexity in the system. However, it is necessary for the developers to strive for minimum complexity, as increased complexity introduces security risks in the software, which can cause severe monetary and reputational damage to a government or a private organization. It even causes bodily harm to human beings with various examples found in previous years where security breaches led to severe consequences. Hence it is vital to maintain low complexity and simple design of structure. Various developers tend to introduce deliberate complexities in the system so that they do not have to write the same program twice; however, it is getting problematic for the software organizations as the demands of security are continually increasing.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the Relationship between Software Complexity and Security

Alenezi¹,

Zarour²

2020

IJSEA

Self Cite

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“…A recent study on software evolution is given in [1], in which the authors studied the complexity evolution of five open-source projects. Other research on software evolution is given in [2]- [12] and references there.…”

Section: Introductionmentioning

confidence: 99%

Linux Kernel Evolution: Analysis of Versions 3.0 and 3.2

Koren¹,

Perel²

2017

IJSEIA

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Evolution of internal dimensions in object‐oriented software–A time series based approach

Sousa,

Bigonha,

Ferreira

et al. 2024

Softw Pract Exp

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SummarySoftware evolution is the process of adapting, maintaining, and updating a software system. This process concentrates the most significant part of the software costs. Many works have studied software evolution and found relevant insights, such as Lehman's laws. However, there is a gap in how software systems evolve from an internal dimensions point of view. For instance, the literature has indicated how systems grow, for example, linearly, sub‐linearly, super‐linearly, or following the Pareto distribution. However, a well‐defined pattern of how this phenomenon occurs has not been established. This work aims to define a novel method to analyze and predict software evolution. We based our strategy on time series analysis, linear regression techniques, and trend tests. In this study, we applied the proposed model to investigate how the internal structure of object‐oriented software systems evolves in terms of four dimensions: coupling, inheritance hierarchy, cohesion, and class size. Applying the proposed method, we identify the functions that better explain how the analyzed dimensions evolve. Besides, we investigate how the relationship between dimension metrics behave over the systems' evolution and the set of classes existing in the systems that affect the evolution of these dimensions. We mined and analyzed data from 46 Java‐based open‐source projects. We used eight software metrics regarding the dimensions analyzed in this study. The main results of this study reveal ten software evolution properties, among them: coupling, cohesion, and inheritance evolve linearly; a relevant percentage of classes contributes to coupling and size evolution; a small percentage of classes contributes to cohesion evolution; there is no relation between the software internal dimensions' evolution. The results also indicate that our method can accurately predict how the software system will evolve in short‐term and long‐term predictions.

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Empirical Analysis of the Complexity Evolution in Open-Source Software Systems

Abstract: Abstract

Cited by 21 publications

References 39 publications

On the Relationship between Software Complexity and Security

On the Relationship between Software Complexity and Security

Linux Kernel Evolution: Analysis of Versions 3.0 and 3.2

Evolution of internal dimensions in object‐oriented software–A time series based approach

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