An approach to analyzing the software process change impact using process slicing and simulation

Park, Seunghun; Bae, Doo‐Hwan

doi:10.1016/j.jss.2010.11.919

Cited by 20 publications

(14 citation statements)

References 33 publications

(35 reference statements)

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“…The tasks include general maintenance tasks, impact analysis, program comprehension and more encompassing tasks such as systematic reuse traceability types and reverse engineering for redevelopment [4]. Some existing studies have addressed these aspects separately such as change impact analysis rather than along with traceability [64] [65]. Hence, overall there is a lack of traceability management support to cope with the continuous integrations in DevOps practice.…”

Section: Discussionmentioning

confidence: 99%

Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey

Meedeniya¹,

Rubasinghe²,

Perera³

2019

IJACSA

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DevOps based software process has become popular with the vision of an effective collaboration between the development and operations teams that continuously integrates the frequent changes. Traceability manages the artefact consistency during a software process. This paper explores the trace-link creation and visualization between software artefacts, existing tool support, quality aspects and the applicability in a DevOps environment. As the novelty of this study, we identify the challenges that limit the traceability considerations in DevOps and suggest research directions. Our methodology consists of concept identification, state-of-practice exploration and analytical review. Despite the existing related work, there is a lack of tool support for the traceability management between heterogeneous artefacts in software development with DevOps practices. Although many existing studies have low industrial relevance, a few proprietary traceability tools have shown a high relevance. The lack of evidence of the related applications indicates the need for a generalized traceability approach. Accordingly, we conclude that the software artefact traceability is maturing and applying collaboratively in the software process. This can be extended to explore features such as artefact change impact analysis, change propagation, continuous integration to improve software development in DevOps environments.

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Section: Discussionmentioning

confidence: 99%

Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey

Meedeniya¹,

Rubasinghe²,

Perera³

2019

IJACSA

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“…One main issue is about how to assess a requirements change request before deciding either to accept or reject it for implementation [20]. The decision has to be made after impact analysis [21], [22], by which the affected elements are identified and scrutinised [23].…”

Section: Related Workmentioning

confidence: 99%

Risk Factors for Software Requirements Change Implementation

Rahman

Razali

Ismail

2019

ijacsa

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Requirements change has been regarded as a substantial risk in software development projects. The factors that contribute to the risk are identified through impact analysis, which later determine the planning of the change implementation. The analysis is however not straightforward as the risk factors that constitute requirements change implementation is currently not much explored. This paper identifies the risk factors by firstly collating them qualitatively through a review of related work and a focus group study. The factors are then confirmed quantitatively through a survey in which data is analysed by using Partial Least Squares Structural Equation Modelling (PLS-SEM). The survey comprise of 276 practitioners from software industry who are involved in the impact analysis. The results indicate that User, Project Team, Top Management, Third Party, Organisation, Identification of Change, Existing Product and Planning of Change Implementation are the significant risk factors in planning of requirements change implementation.

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“…Different slicing techniques were widely applied to change impact analysis, such as static slicing [ 2 , 17 ], dynamic slicing [ 18 ], thin slicing [ 19 ], process slicing [ 20 ], and probabilistic slicing [ 21 ]. Similarly, Bayesian Belief Network was applied by Tang et al [ 8 ] to quantify the likelihood of change impact based on the dependency information between architecture decisions and elements.…”

Section: Related Workmentioning

confidence: 99%

Network-Based Analysis of Software Change Propagation

Wang

Huang

2014

The Scientific World Journal

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The object-oriented software systems frequently evolve to meet new change requirements. Understanding the characteristics of changes aids testers and system designers to improve the quality of softwares. Identifying important modules becomes a key issue in the process of evolution. In this context, a novel network-based approach is proposed to comprehensively investigate change distributions and the correlation between centrality measures and the scope of change propagation. First, software dependency networks are constructed at class level. And then, the number of times of cochanges among classes is minded from software repositories. According to the dependency relationships and the number of times of cochanges among classes, the scope of change propagation is calculated. Using Spearman rank correlation analyzes the correlation between centrality measures and the scope of change propagation. Three case studies on java open source software projects Findbugs, Hibernate, and Spring are conducted to research the characteristics of change propagation. Experimental results show that (i) change distribution is very uneven; (ii) PageRank, Degree, and CIRank are significantly correlated to the scope of change propagation. Particularly, CIRank shows higher correlation coefficient, which suggests it can be a more useful indicator for measuring the scope of change propagation of classes in object-oriented software system.

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An approach to analyzing the software process change impact using process slicing and simulation

Cited by 20 publications

References 33 publications

Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey

Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey

Risk Factors for Software Requirements Change Implementation

Network-Based Analysis of Software Change Propagation

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