The impact analysis task in software maintenance: a model and a case study

Queille,; Voidrot,; Wilde,; Munro,

doi:10.1109/icsm.1994.336771

Cited by 47 publications

(29 citation statements)

References 9 publications

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“…The contribution of Queille et al [111] is twofold. First, they separate the definition of impact analysis from program comprehension.…”

Section: ) Execution Tracesmentioning

confidence: 99%

A taxonomy for software change impact analysis

Lehnert

2011

Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Softwar

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Abstract-Change impact analysis is required for constantly evolving systems to support the comprehension, implementation, and evaluation of changes. A lot of research effort has been spent on this subject over the last twenty years, and many approaches were published likewise. However, there has not been an extensive attempt made to summarize and review published approaches as a base for further research in the area. Therefore, we present the results of a comprehensive investigation of software change impact analysis, which is based on a literature review and a taxonomy for impact analysis. The contribution of this review is threefold. First, approaches proposed for impact analysis are explained regarding their motivation and methodology. They are further classified according to the criteria of the taxonomy to enable the comparison and evaluation of approaches proposed in literature. We perform an evaluation of our taxonomy regarding the coverage of its classification criteria in studied literature, which is the second contribution. Last, we address and discuss yet unsolved problems, research areas, and challenges of impact analysis, which were discovered by our review to illustrate possible directions for further research.

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“…The contribution of Queille et al [111] is twofold. First, they separate the definition of impact analysis from program comprehension.…”

Section: ) Execution Tracesmentioning

confidence: 99%

A taxonomy for software change impact analysis

Lehnert

2011

Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Softwar

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“…Various dependency-analysis methods based on call graphs, program slicing (Gallagher and Lyle 1991), hidden dependency analysis (Rajlich 1997;Chen and Rajlich 2001;Yu and Rajlich 2001), lightweight static analysis approaches (Moonen 2002;Petrenko and Rajlich 2009), concept analysis (Tonella 2003), dynamic analysis (Law and Rothermel 2003;Orso et al 2004;Ren et al 2004), hypertext systems, documentation systems, UML models (Briand et al 2002), and Information Retrieval (Antoniol et al 2000;) are already investigated in the literature. Queille et al (Queille et al 1994) proposed an interactive process in which the programmer, guided by dependencies among program components (i.e., classes, functions), inspects components one-by-one and identifies the ones that are going to change -this process involves both searching and browsing activities. This interactive process was supported via a formal model, based on graph rewriting rules (Chen and Rajlich 2000).…”

Section: Software Change Impact Analysis (Ia)mentioning

confidence: 99%

Integrating conceptual and logical couplings for change impact analysis in software

2012

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The paper presents an approach that combines conceptual and evolutionary techniques to support change impact analysis in source code. Conceptual couplings capture the extent to which domain concepts and software artifacts are related to each other. This information is derived using Information Retrieval based analysis of textual software artifacts that are found in a single version of software (e.g., comments and identifiers in a single snapshot of source code). Evolutionary couplings capture the extent to which software artifacts were co-changed. This information is derived from analyzing patterns, relationships, and relevant information of source code changes mined from multiple versions in software repositories. The premise is that such combined methods provide improvements to the accuracy of impact sets compared to the two individual approaches.A rigorous empirical assessment on the changes of the open source systems Apache httpd, ArgoUML, iBatis, KOffice, and jEdit is also reported. The impact sets are evaluated at the file and method levels of granularity for all the software systems considered in the empirical evaluation.The results show that a combination of conceptual and evolutionary techniques, across several cutoff points and periods of history, provides statistically significant improvements in accuracy over either of the two techniques used independently. Improvements in F-measure values of up to 14%(from 3% to 17%) over the conceptual technique in ArgoUML at the method granularity, and up to 21% over the evolutionary technique in iBatis (from 9% to 30%) at the file granularity were reported.

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“…Based on the characterisation provided by Queille et al [13], we can expect an impact analysis method to have the following basic components :…”

Section: Data-level Impacts From Brsmentioning

confidence: 99%

“…Software change impact analysis (SCIA) tools attempt to address this problem by exploiting the exhaustive search capabilities of software to identify the components affected by a proposed change [1,13]. Such tools come in many varieties, depending on the kinds of software life cycle objects that they can reason over and the types of proposed change they can work with.…”

Section: Software Change Impact Analysismentioning

confidence: 99%