Static Techniques for Concept Location in Object-Oriented Code

Marcus, Andrian; Rajlich, Václav; Buchta, J.; Petrenko, Maksym; Sergeyev, Andrey

doi:10.1109/wpc.2005.33

Cited by 86 publications

(47 citation statements)

References 27 publications

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“…This type of question represents 5.37% of all questions asked, suggesting that this is a significant information seeking type for OS programmers maintaining large systems. Theses finding add empirical credence to Marcus et al (2005) 'Concept Location' work.…”

Section: Location Type Queriessupporting

confidence: 58%

Open Source Programmers' Information Seeking During Software Maintenance

Sharif

Mokhtar

Buckley

2011

Journal of Computer Science

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Problem statement: Several authors have proposed information seeking as an appropriate case study for studying software maintenance and evolution that have provided empirical classifications of information seeking in commercial software evolution settings. Approach: However, there is minimal research in the literature describing the information seeking behavior of Open Source programmers, even though Open Source contexts would seem to exacerbate the information seeking problems to a certain extend; where team members are typically delocalized from each other and they are often forced into asynchronous communication. Results: This study reports on an empirical study that classifies Open-Source programmers' information needs generated through open-coding of questions that appear on developers' mailing lists. Based on the generated Information Seeking Schema (ISS), details of the information sought by programmers on 6 different mailing lists over several years are analyzed and discussed. Conclusion/Recommendations: The result shows several interesting findings that describe the programmers' information needs across the mailing lists. Firstly, there are a similar pattern of information artifact and attribute across all projects. Secondly, majority of the programmers' information seeking concentrated on the systems' implementations. Thirdly, the OS programmers have also shown to be team-oriented and they tended to rely on documentation more than what have previously reported. These results suggest the applicability of the ISS in evaluating OS programmers information seeking.

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Section: Location Type Queriessupporting

confidence: 58%

Open Source Programmers' Information Seeking During Software Maintenance

Sharif

Mokhtar

Buckley

2011

Journal of Computer Science

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“…A more comprehensive overview of concept location techniques is available in [21] and static techniques are discussed in [19].…”

Section: Related Workmentioning

confidence: 99%

On the use of relevance feedback in IR-based concept location

Haiduc

Marcus

Menzies

2009

2009 IEEE International Conference on Software Maintenance

143

107

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“…[1,13,40,44]); (b) static analysis, based on static source code information, such as slicing, control or data flow graphs (e.g. [7,27,39]); and (c) textual analysis, explore natural language text found in programs like comments or documentation. This last type can be based on Information Retrieval (IR) methods (e.g.…”

Section: Related Workmentioning

confidence: 99%

Conclave: Ontology-Driven Measurement of Semantic Relatedness between Source Code Elements and Problem Domain Concepts

Carvalho

Almeida

Henriques

et al. 2014

Computational Science and Its Applications – ICCSA 2014

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Abstract. Software maintainers are often challenged with source code changes to improve software systems, or eliminate defects, in unfamiliar programs. To undertake these tasks a sufficient understanding of the system (or at least a small part of it) is required. One of the most time consuming tasks of this process is locating which parts of the code are responsible for some key functionality or feature. Feature (or concept) location techniques address this problem. This paper introduces Conclave, an environment for software analysis, and in particular the Conclave-Mapper tool that provides a feature location facility. This tool explores natural language terms used in programs (e.g. function and variable names), and using textual analysis and a collection of Natural Language Processing techniques, computes synonymous sets of terms. These sets are used to score relatedness between program elements, and search queries or problem domain concepts, producing sorted ranks of program elements that address the search criteria, or concepts. An empirical study is also discussed to evaluate the underlying feature location technique.

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Static Techniques for Concept Location in Object-Oriented Code

Abstract: Abstract

Cited by 86 publications

References 27 publications

Open Source Programmers' Information Seeking During Software Maintenance

Open Source Programmers' Information Seeking During Software Maintenance

On the use of relevance feedback in IR-based concept location

Conclave: Ontology-Driven Measurement of Semantic Relatedness between Source Code Elements and Problem Domain Concepts

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