Opportunistic Reuse: Lessons from Scrapheap Software Development

Kotonya, Gerald; Lock, Simon; Mariani, John

doi:10.1007/978-3-540-87891-9_20

Cited by 12 publications

(13 citation statements)

References 6 publications

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“…For example, during maintenance tasks, some programmers follow a "systemic" strategy aimed at understanding how different parts of the code interact [30,38]. In contrast, an "opportunistic" strategy aims to find only the section of code that is needed for a particular change [9,32,14,35]. In either strategy, studies suggest that programmers form a mental model of the software [36], specifically including the relationships between different sections of source code [41,34,50,51].…”

Section: Studies Of Program Comprehensionmentioning

confidence: 99%

Improving automated source code summarization via an eye-tracking study of programmers

Rodeghero

McMillan

McBurney

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

169

106

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Source Code Summarization is an emerging technology for automatically generating brief descriptions of code. Current summarization techniques work by selecting a subset of the statements and keywords from the code, and then including information from those statements and keywords in the summary. The quality of the summary depends heavily on the process of selecting the subset: a high-quality selection would contain the same statements and keywords that a programmer would choose. Unfortunately, little evidence exists about the statements and keywords that programmers view as important when they summarize source code. In this paper, we present an eye-tracking study of 10 professional Java programmers in which the programmers read Java methods and wrote English summaries of those methods. We apply the findings to build a novel summarization tool. Then, we evaluate this tool and provide evidence to support the development of source code summarization systems.

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Section: Studies Of Program Comprehensionmentioning

confidence: 99%

Improving automated source code summarization via an eye-tracking study of programmers

Rodeghero

McMillan

McBurney

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

169

106

View full text Add to dashboard Cite

show abstract

“…In this development context, systems are built in an opportunistic manner [6], considering at the same time the environment and the strategy of the organization, the components available in the marketplace (e.g., OTS marketplace, FOSS community), their capacity for being integrated into a single system and interoperate in a transparent manner, and the resources required by their adoption and integration.…”

Section: Introductionmentioning

confidence: 99%

“…This paper proposes the DHARMA method to identify the architecture of a component-based system. The generic components that form this architecture may be later substituted in an opportunistic manner (in the sense of [6]) by components of different nature and origins forming a hybrid system. Specifically, DHARMA is based on the use of the i* framework [9], exploiting its ability to represent actors, dependencies and intentions.…”

Section: Introductionmentioning

confidence: 99%

On the Use of i* for Architecting Hybrid Systems: A Method and an Evaluation Report

Carvallo

Franch

2009

Lecture Notes in Business Information Processing

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Abstract. The architectural definition of hybrid software systems is a challenging problem that demands to reconcile stakeholders' strategic needs and components marketplace, whilst defining an appropriate set of services. We have defined a method called DHARMA based on the i* framework. The goal of this paper is to present an experience report about the use of i* in large-scale projects. We provide two different viewpoints: the viewpoint of the stakeholder and the viewpoint of the modeller. Apart from general lessons learned, we also provide some insights about the use of i* in the specific context of architecting hybrid systems using DHARMA.

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“…These studies consistently show that programmers follow either a "systemic" strategy for understanding source code, or an "opportunistic" one (Ko and Myers 2005;Littman et al 1987;Brandt et al 2010;Kotonya et al 2008;Davison et al 2000;Lakhotia 1993;Holmes and Walker 2013;Ko et al 2006). The difference between these two strategies is that in a systemic strategy, programmers try to understand how the components of a program interact, while in an opportunistic strategy, programmers only seek to understand how to modify a small section of code.…”

Section: Program Comprehensionmentioning

confidence: 88%

An empirical study of the textual similarity between source code and source code summaries

McBurney

McMillan

2014

Empir Software Eng

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Source code documentation often contains summaries of source code written by authors. Recently, automatic source code summarization tools have emerged that generate summaries without requiring author intervention. These summaries are designed for readers to be able to understand the high-level concepts of the source code. Unfortunately, there is no agreed upon understanding of what makes up a "good summary." This paper presents an empirical study examining summaries of source code written by authors, readers, and automatic source code summarization tools. This empirical study examines the textual similarity between source code and summaries of source code using Short Text Semantic Similarity metrics. We found that readers use source code in their summaries more than authors do. Additionally, this study finds that accuracy of a human written summary can be estimated by the textual similarity of that summary to the source code.

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Opportunistic Reuse: Lessons from Scrapheap Software Development

Cited by 12 publications

References 6 publications

Improving automated source code summarization via an eye-tracking study of programmers

Improving automated source code summarization via an eye-tracking study of programmers

On the Use of i* for Architecting Hybrid Systems: A Method and an Evaluation Report

An empirical study of the textual similarity between source code and source code summaries

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