Interactive Exploration of Co-evolving Software Entities

Vanya, Adam; Premraj, Rahul; Vliet, Hans van

doi:10.1109/csmr.2010.50

Cited by 12 publications

(5 citation statements)

References 11 publications

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“…Gal et al [7] showed that the concept helps to derive useful insights about the system architecture. Other work has investigated the causes of change propagation [8]- [9], co-change prediction [10]- [11] and cochange visualization [12]- [13].…”

Section: Background a Co-change Historiesmentioning

confidence: 99%

Using Co-change Histories to Improve Bug Localization Performance

Tantithamthavorn

Ihara

Matsumoto

2013

2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed C

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A large open source software (OSS) project receives many bug reports on a daily basis. Bug localization techniques automatically pinpoint source code fragments that are relevant to a bug report, thus enabling faster correction. Even though many bug localization methods have been introduced, their performance is still not efficient. In this research, we improved on existing bug localization methods by taking into account cochange histories. We conducted experiments on two OSS datasets, the Eclipse SWT 3.1 project and the Android ZXing project. We validated our approach by evaluating effectiveness compared to the state-of-the-art approach BugLocator. In the Eclipse SWT 3.1 project, our approach reliably identified source code that should be fixed for a bug in 72.46% of the total bugs, while BugLocator identified only 51.02%. In the Android ZXing project, our approach identified 85.71%, while BugLocator identified 60%.

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Section: Background a Co-change Historiesmentioning

confidence: 99%

Using Co-change Histories to Improve Bug Localization Performance

Tantithamthavorn

Ihara

Matsumoto

2013

2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed C

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“…A number of studies [2], [11], [23], [24] were conducted on the identification of possible structural weaknesses analyzing the co-evolution of files [2], [23], [24] or system modules [11]. The underlying idea is that if two or more files from different folders co-change frequently, this might be an indication of structural weakness.…”

Section: Significance Of Our Studymentioning

confidence: 99%

“…The existing co-change visualization tools: Evolution Radar [10], CCVisu [3], Evolution Storyboard [4], interactive visualization [23] can clearly indicate file level co-changes. These tools cannot detect method level co-changes.…”

Section: Significance Of Our Studymentioning

confidence: 99%

Insight into a method co-change pattern to identify highly coupled methods: An empirical study

Mondal

Roy

Schneider

2013

2013 21st International Conference on Program Comprehension (ICPC)

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In this paper, we describe an empirical study of a unique method co-change pattern that has the potential to pinpoint design deficiency in a software system. We automatically identify this pattern by inspecting the method co-change history using reasonable constraints on method association rules. We also investigate the effect of code clones on the method co-changes identified according to the pattern, because there is a common intuition that clone fragments from the same clone class often require corresponding changes to ensure they remain consistent with each other.According to our in-depth investigation on hundreds of revisions of seven open-source software systems considering three types of clones (Type 1, Type 2, Type 3), our identified pattern helps us detect methods that are logically coupled with multiple other methods and that exhibit a significantly higher modification frequency than other methods. We call the methods detected by the pattern MMCGs (Methods appearing in Multiple Commit Groups) considering the pattern semantic. MMCGs can be considered as the candidates for restructuring in order to minimize coupling as well as to reduce the change-proneness of a software system. According to our observation, code clones have a significant effect on method co-changes as well as on MMCGs. We believe that clone refactoring can help us minimize evolutionary coupling among methods.

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“…The optimal time interval found in the study environment was 1 hour. Our evaluation has helped us choose the right set of change sets approximated from the version archives of the company, which has already performed several evolution-related studies successfully [7].…”

Section: Conclusion and Consequencesmentioning

confidence: 99%

“…A starting point to initiate the planned transition is to study and audit the composition of change sets to date and identify the causes behind cross sub-system changes. Architects can then consider maintenance activities (such as moving files from one subsystem to another) to better facilitate the evolution of the system [7].…”

Section: Introductionmentioning

confidence: 99%

Approximating Change Sets at Philips Healthcare: A Case Study

Vanya¹,

Premraj²,

Vliet³

2011

2011 15th European Conference on Software Maintenance and Reengineering

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Abstract-A single development task such as solving a bug or implementing a new feature often involves changing a number of entities, also known together as a change set. Change sets can be approximated from the version control system. They are then used by the architects and developers to take important decisions. So change sets need to be approximated carefully. It is common to assume that two entities checked-in less than a small time interval from each other, and having the same meta-data associated with them, belong to the same transaction. Transactions may be good approximations of change sets if developers commit change sets in one go and if the required meta-data is available. This is however not the case in the industrial environment (Philips Healthcare) we study. Our paper presents a case study in which we investigated how change sets can be approximated in an environment with a complex workflow and limited meta-data in the version repositories. We found that, dependent on the commit practices used, a suitable time intervals between check-in timestamps of files has to be determined and leveraged to reliably approximate change sets.

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Interactive Exploration of Co-evolving Software Entities

Cited by 12 publications

References 11 publications

Using Co-change Histories to Improve Bug Localization Performance

Using Co-change Histories to Improve Bug Localization Performance

Insight into a method co-change pattern to identify highly coupled methods: An empirical study

Approximating Change Sets at Philips Healthcare: A Case Study

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