Using structural and textual information to capture feature coupling in object-oriented software

Revelle, Meghan; Gethers, Malcom; Poshyvanyk, Denys

doi:10.1007/s10664-011-9159-7

Cited by 50 publications

(41 citation statements)

References 92 publications

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“…That is, a file is typically much "bigger" than a method. Previous works on the application of information retrieval techniques in software engineering have observed a similar sensitivity trend with respect to the size of the document and the accuracy of the intended tasks (Revelle et al 2011). For the evolutionary couplings, only the co-change information in commits was utilized for evolutionary couplings.…”

Section: Rq2: Does the Choice Of Granularity (Ie File Vs Method) mentioning

confidence: 73%

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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Section: Rq2: Does the Choice Of Granularity (Ie File Vs Method) mentioning

confidence: 73%

Integrating conceptual and logical couplings for change impact analysis in software

2012

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“…Kuhn et al (2007) proposed the use of IR techniques to exploit linguistic information found in source code, such as identifiers (i.e., class or method) names and comments. Revelle et al (2011) define new feature coupling metrics based on structural and textual source code information. Kagdi et al (2013) in their study on integrating conceptual and logical coupling metrics for change impact analysis suggest that measurement of conceptual metrics is better employed at the class level than at the method level.…”

Section: Related Workmentioning

confidence: 99%

An empirical study on the interplay between semantic coupling and co-change of software classes

2017

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Software systems continuously evolve to accommodate new features and interoperability relationships between artifacts point to increasingly relevant software change impacts. During maintenance, developers must ensure that related entities are updated to be consistent with these changes. Studies in the static change impact analysis domain have identified that a combination of source code and lexical information outperforms using each one when adopted independently. However, the extraction of lexical information and the measure of how loosely or closely related two software artifacts are, considering the semantic information embedded in their comments and identifiers has been carried out using somewhat complex information retrieval (IR) techniques. The interplay between software semantic and change relationship strengths has also not been extensively studied. This work aims to fill both gaps by comparing the effectiveness of measuring semantic coupling of OO software classes using (i) simple identifier based techniques and (ii) the word corpora of the entire classes in a software system. Afterwards, we empirically investigate the interplay between semantic and change coupling. The empirical results show that: (1) identifier based methods have more computational efficiency but cannot always be used interchangeably with corpora-based methods of computing semantic coupling of classes and (2) there is no correlation between semantic and change coupling. Furthermore we found that (3) there is a directional relationship between the two, as over 70% of the semantic dependencies are also linked by change coupling but not vice versa.

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“…There are also other sources like the software documentation, web search engines, source code examples or programming tutorials. Developers can seek for source code to find files or code locations for further modifications [34] or look for a code description to better understand the part of the code they need to edit based on a similar situation or a problem.…”

Section: Task Relevant Information Sourcesmentioning

confidence: 99%

“…Revelle et al [34] inspected a set of coupling metrics on the structural and the semantic level where the developers answered that feature couplings on a higher level of abstraction than classes are useful. Bavota et al [4] explored the developers' perceptions of software couplings.…”

Section: Related Workmentioning

confidence: 99%

How Do Coupled File Changes Influence How Developers Seek Help During Maintenance Tasks?

Ramadani

Wagner

2017

2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)

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Abstract-Software repositories contain a lot of information that can be transformed into suggestions other files they need to modify during maintenance tasks (so-called "coupled changes"). Existing studies however ignore developer feedback and their influence on the developer strategy for getting help during maintenance tasks. We used the Grounded Theory approach to investigate screen capture videos from an experiment to find which information sources developers use to find help and what is their relevance. We compared the frequency as well as the sequence patterns of used information sources both for the developers using coupled change suggestions and those not using them. We found a set of information sources where the developers seek for help and identified two categories of relevance. Also, we discovered that for the tasks using coupled change suggestions, the developers used mostly the internal IDE elements as an information source whereby the developers not using coupled change suggestions often used external sources like the documentation or the web. Coupled change suggestions influence the strategy how the developers seek for help by reducing the search for information on external locations which makes the process of solving maintenance tasks more compact.

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Using structural and textual information to capture feature coupling in object-oriented software

Cited by 50 publications

References 92 publications

Integrating conceptual and logical couplings for change impact analysis in software

Integrating conceptual and logical couplings for change impact analysis in software

An empirical study on the interplay between semantic coupling and co-change of software classes

How Do Coupled File Changes Influence How Developers Seek Help During Maintenance Tasks?

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