jCT: A Java Code Tomograph

Lumpe, Markus; Mahmud, Samiran; Goloshchapova, Olga

doi:10.1109/ase.2011.6100139

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…One example is the CKJM tool [29] for the Chidamber and Kemerer metrics [5]. Another example, that more closely resembles ours, is jCT, an extensible metrics extractor for Java 6 IL-Bytecode, introduced by Lumpe et al [23], in 2011. Like us, they evaluated their tool on Qualitas Corpus; however, because jCT works only on annotated bytecode and not on source code, the number of features that can be extracted is limited.…”

Section: Related Workmentioning

confidence: 85%

JFeature: Know Your Corpus

Riouak

Hedin

Reichenbach

et al. 2022

2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)

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Software corpora are crucial for evaluating research artifacts and ensuring repeatability of outcomes. Corpora such as DaCapo and Defects4J provide a collection of real-world opensource projects for evaluating the robustness and performance of software tools like static analysers. However, what do we know about these corpora? What do we know about their composition? Are they really suited for our particular problem? We developed JFEATURE, an extensible static analysis tool that extracts syntactic and semantic features from Java programs, to assist developers in answering these questions. We demonstrate the potential of JFEATURE by applying it to four widely-used corpora in the program analysis area, and we suggest other applications, including longitudinal studies of individual Java projects and the creation of new corpora.

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Section: Related Workmentioning

confidence: 85%

JFeature: Know Your Corpus

Riouak

Hedin

Reichenbach

et al. 2022

2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)

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“…We use jCT [29] to perform data collection. jCT is an extensible metrics extraction infrastructure for Java code that provides built-in support to traverse the Helix repository [27].…”

Section: Package Binningmentioning

confidence: 99%

On the Application of Inequality Indices in Comparative Software Analysis

Goloshchapova

Lumpe

2013

2013 22nd Australian Software Engineering Conference

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Socio-economic inequality indices, like the Gini coefficient or the Theil index, offer us a viable alternative to central tendency statistics when being used to aggregate software metrics data. The specific value of these inequality indices lies in their ability to capture changes in the distribution of metrics data more effectively than, say, average or median. Knowing whether the distribution of one metrics is more unequal than that of another one or whether its distribution becomes more or less unequal over time is the crucial element here. There are, however, challenges in the application of these indices that can result in ecological fallacies. The first issue relates to occurrences of zeros in metrics data, and not all inequality indices cope well with this event. The second problem arises from applying a macro-level inference to a micro-level analysis of a changing population. The Gini coefficient works for the former, whereas the decomposable Theil index serves the latter. Nevertheless, when used with care, and usually in combination, both indices can provide us with a powerful tool not only to analyze software, but also to assess its organizational health and maintainability over time.

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Comparing TPC-W and RUBiS via PCA

Lumpe

2017

Intelligent Information and Database Systems

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jCT: A Java Code Tomograph

Cited by 5 publications

References 6 publications

JFeature: Know Your Corpus

JFeature: Know Your Corpus

On the Application of Inequality Indices in Comparative Software Analysis

Comparing TPC-W and RUBiS via PCA

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