Toward mining "concept keywords" from identifiers in large software projects

Ohba, Masaru; Gondow, Katsuhiko

doi:10.1145/1083142.1083151

Cited by 19 publications

(8 citation statements)

References 1 publication

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“…A framework to study how the same identifiers can be trusted to represent the implementation of the same concepts was proposed in [1]. In [16] the authors proposed a method based on an improvement of the term frequency/inverted document frequency measure to mine concept keywords from identifiers in large software projects. Early work by Biggerstaff et al [4] addressed the problem of identifying human oriented concepts in a software system and associating them with their implementation instances.…”

Section: The Study Of Software Vocabulariesmentioning

confidence: 99%

On the Use of Domain Terms in Source Code

Haiduc

Marcus

2008

2008 16th IEEE International Conference on Program Comprehension

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Information about the problem domain of the software and the solution it implements is often embedded by developers in comments and identifiers. When using software developed by others or when are new to a project, programmers know little about how domain information is reflected in the source code. Programmers often learn about the domain from external sources such as books, articles, etc. Hence, it is important to use in comments and identifiers terms that are commonly known in the domain literature, as it is likely that programmers will use such terms when searching the source code. The paper presents a case study that investigated how domain terms are used in comments and identifiers. The study focused on three research questions: (1) to what degree are domain terms found in the source code of software from a particular problem domain?; (2) which is the preponderant source of domain terms: identifiers or comments?; and (3) to what degree are domain terms shared between several systems from the same problem domain? Within the studied software, we found that in average: 42% of the domain terms were used in the source code; 23% of the domain terms used in the source code are present in comments only, whereas only 11% in the identifiers alone, and there is a 63% agreement in the use of domain terms between any two software systems.

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Section: The Study Of Software Vocabulariesmentioning

confidence: 99%

On the Use of Domain Terms in Source Code

Haiduc

Marcus

2008

2008 16th IEEE International Conference on Program Comprehension

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“…This technique (even though simple) has been tried out in applying concept keywords and suitable e-documents have been extracted and provided to elearners according to their styles and interests, thus enhancing their learning performances [7]. For simple and straight forward concept extraction application (like cognitive dimension extraction), concept keywords have been recommended to use in computing term frequency (tf) & Inverse Document Frequency (IDF), for efficiently extracting documents [8]. Online tests are conducted to assess learner's achievements and to maintain such online items, it is a big task [9].…”

Section: Literature Surveymentioning

confidence: 99%

Reliable Cognitive Dimensional Document Ranking by Weighted Standard Cauchy Distribution

Vijila¹,

Nirmala²

2017

IJSC

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Categorization of cognitively uniform and consistent documents such as University question papers are in demand by e-learners. Literature indicates that Standard Cauchy distribution and the derived values are extensively used for checking uniformity and consistency of documents. The paper attempts to apply this technique for categorizing question papers according to four selective cognitive dimensions. For this purpose cognitive dimensional keyword sets of these four categories (also termed as portrayal concepts) are assumed and an automatic procedure is developed to quantify these dimensions in question papers. The categorization is relatively accurate when checked with manual methods. Hence simple and well established term frequency / inverse document frequency 'tf/ IDF' technique is considered for automating the categorization process. After the documents categorization, standard Cauchy formula is applied to rank order the documents that have the least differences among Cauchy value, (according to Cauchy theorem) so as obtain consistent and uniform documents in an order or ranked. For the purpose of experiments and social survey, seven question papers (documents) have been designed with various consistencies. To validate this proposed technique social survey is administered on selective samples of elearners of Tamil Nadu, India. Results are encouraging and conclusions drawn out of the experiments will be useful to researchers of concept mining and categorizing documents according to concepts. Findings have also contributed utility value to e-learning system designers.

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“…There are regular expression-based searching techniques such as UNIX grep, however, most current research focuses on modern information retrieval (IR) [24,31] and natural language [37] searching techniques. To make queries more effective at locating relevant code, approaches have been suggested to help find the concept words in software [27,37]. These approaches are complementary to our work to potentially discover a seed method set, which is used as input to our current approach.…”

Section: Search-based Exploration Approachesmentioning

confidence: 99%

Exploring the neighborhood with dora to expedite software maintenance

Hill

Pollock

Vijay‐Shanker

2007

Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering

102

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Completing software maintenance and evolution tasks for today's large, complex software systems can be difficult, often requiring considerable time to understand the system well enough to make correct changes. Despite evidence that successful programmers use program structure as well as identifier names to explore software, most existing program exploration techniques use either structural or lexical identifier information. By using only one type of information, automated tools ignore valuable clues about a developer's intentions-clues critical to the human program comprehension process. In this paper, we present and evaluate a technique that exploits both program structure and lexical information to help programmers more effectively explore programs. Our approach uses structural information to focus automated program exploration and lexical information to prune irrelevant structure edges from consideration. For the important program exploration step of expanding from a seed, our experimental results demonstrate that an integrated lexical-and structural-based approach is significantly more effective than a state-of-the-art structural program exploration technique.

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Toward mining "concept keywords" from identifiers in large software projects

Cited by 19 publications

References 1 publication

On the Use of Domain Terms in Source Code

On the Use of Domain Terms in Source Code

Reliable Cognitive Dimensional Document Ranking by Weighted Standard Cauchy Distribution

Exploring the neighborhood with dora to expedite software maintenance

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