A survey of code‐based change impact analysis techniques

Li, Bixin; Sun, Xiaobing; Leung, Hareton; Zhang, Sai

doi:10.1002/stvr.1475

Cited by 152 publications

(146 citation statements)

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“…Many criteria have been proposed in literature for classifying existing impact analysis techniques (e.g., [23,[30][31][32][33]). These techniques addressed, in fact, various specific tasks of software maintenance.…”

Section: Related Workmentioning

confidence: 99%

“…These techniques addressed, in fact, various specific tasks of software maintenance. Existing impact analysis techniques can be static and/or dynamic (e.g., [17,20,23,[34][35][36]), based on the source code of the program and/or on models (e.g., [34], [35]). Static impact analysis techniques include structural static analysis, textual analysis, and historical data analysis [33], [35], [37], [38].…”

Section: Related Workmentioning

confidence: 99%

“…Retrospective impact analysis techniques are used after a change has been implemented. These techniques aim mainly at supporting the correction of potential errors that are introduced by changes, and regression testing (e.g., [23], [24], [28], [29], [42]). …”

Section: Related Workmentioning

confidence: 99%

“…Impact analysis may, in fact, have some false positives (elements in the impact set that aren't really impacted) and false negatives (elements really impacted that aren't identified in the impact analysis) [23]. In the evaluation, we obtained three types of results: the number of actual impacts due to a change, the number of impacts predicted by a model and the number of impacts correctly predicted by a model.…”

Section: Metricsmentioning

confidence: 99%

“…Abdi et al [45] proposed an approach based on Bayesian networks to analyze and predict change impact in OOS. Li et al [23] proposed a Framework for characterizing code-based impact analysis techniques. The Framework includes seven main properties including the objective of the impact analysis, the type of the supported analysis, the language support, and so forth.…”

Section: Related Workmentioning

confidence: 99%

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Towards a Change Impact Analysis Model for Java Programs: An Empirical Evaluation

Badri¹,

Badri²,

Joly³

2015

JSW

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Software change impact analysis (or impact analysis) plays a crucial role in software maintenance and evolution. Impact analysis aims at identifying the possible effects of a source code modification. It is often used to evaluate the effects of a change after its implementation. However, more proactive approaches use impact analysis to predict the effects of a change before it is implemented. In this way, impact analysis provides useful information that can be used, among others, to guide the implementation of the change and to support regression tests selection. This paper aims at proposing a change impact analysis model for Java programs. The model was designed to support predictive impact analysis. It includes several impact rules based on the Java language constructs. We performed an empirical evaluation of the model using several Java programs. In order to assess the model prediction quality, we used two measures (precision and recall). The reported results show that the model is able to achieve high accuracy.Key words: Software maintenance, software evolution, change, ripple effect, impact analysis, predictive analysis, model, impact rules, and empirical analysis. IntroductionAs software systems are used for a long period of time, software evolution is inevitable. Indeed, software systems need to continually evolve for various reasons including: adding new features to satisfy user requirements, changing business needs, introducing novel technologies, correcting faults, improving quality, and so forth. So, as software evolves, the changes made to the software must be carefully managed. It is particularly important to ensure that modified software still verifies its specification and whether new errors were introduced inadvertently [1]- [3]. It is, therefore, crucial to find where changes occur and to identify parts of the software that are possibly affected by the changes, parts that must be correctly retested. Indeed, for obvious reasons, retesting all the software after instantiating a change is inefficient, costly, and unacceptable in practice [4].Software evolution faces many challenges [5]- [8]. Software maintenance is, in this context, a vital activity [9]. It is, however, costly [10], [11]. Several experts agree that two of the most important activities of software maintenance are: understanding the software and evaluating the potential effects of a change [12]-[16]. The second activity is closely related to the first one. Indeed, to understand the effects of a given change, it is necessary to understand the system beforehand [17]. The software design, particularly the dependencies between its components, can make this task difficult. A change to a system, however minor, can lead to several unintended effects (ripple-effect). One effective way to deal with this important issue is to develop models (and techniques) that can be used to support the evaluation of the potential effects of a change. This can be used to Software change impact analysis (or impact analysis) plays a crucial role in s...

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Metricsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Towards a Change Impact Analysis Model for Java Programs: An Empirical Evaluation

Badri¹,

Badri²,

Joly³

2015

JSW

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Impact analysis in the presence of dependence clusters using Static Execute After in WebKit

Schrettner

Jász

Gergely

et al. 2013

J Software Evolu Process

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Abstract-Impact analysis based on code dependence can be an integral part of software quality assurance by providing opportunities to identify those parts of the software system that are affected by a change. Because changes usually have far reaching effects in programs, effective and efficient impact analysis is vital, which has different applications including change propagation and regression testing. Static Execute After (SEA) is a relation on program elements (procedures) that is efficiently computable and accurate enough to be a candidate for use in impact analysis in practice. To assess the applicability of SEA in terms of capturing real defects, we present results on integrating it into the build system of WebKit, a large, open source software system, and on related experiments. We show that a large number of real defects can be captured by impact sets computed by SEA, albeit many of them are large. We demonstrate that this is not an issue in applying it to regression test prioritization, but generally it can be an obstacle in the path to efficient use of impact analysis. We believe that the main reason for large impact sets is the formation of dependence clusters in code. As apparently dependence clusters cannot be easily avoided in the majority of cases, we focus on determining the effects these clusters have on impact analysis.

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Effort estimation in agile software development: Case study and improvement framework

Tanveer

Guzmán

Engel

2017

J Software Evolu Process

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Effort estimation is more challenging in an agile context, as instead of exerting strict control over changes in requirements, dynamism is embraced. Current practice relies on expert judgment, where the accuracy of estimates is sensitive to the expertise of practitioners and prone to bias. To improve the effectiveness of the effort estimation process, the goal of this research is to investigate and understand the estimation process with respect to its accuracy in the context of agile software development from the perspective of agile development teams. Using case study research, 2 observations and eleven interviews were conducted with 3 agile development teams at SAP SE, a German multinational software corporation. The results reveal that factors such as the developer's knowledge, experience, and the complexity and impact of changes on the underlying system affect the magnitude as well as estimation accuracy. Furthermore, there is a need for a tool that incorporates expert knowledge, enables explicit consideration of cost drivers by experts and visualizes this information to improve the effectiveness of the effort estimation. On the basis of the findings of the case study, a framework, inspired by the quality improvement paradigm is proposed to improve effort estimation in agile development

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A survey of code‐based change impact analysis techniques

Cited by 152 publications

References 105 publications

Towards a Change Impact Analysis Model for Java Programs: An Empirical Evaluation

Towards a Change Impact Analysis Model for Java Programs: An Empirical Evaluation

Impact analysis in the presence of dependence clusters using Static Execute After in WebKit

Effort estimation in agile software development: Case study and improvement framework

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