Browsing by Author "Uddin, M.S."

Now showing 1 - 2 of 2
  • No Thumbnail Available
    ItemMetadata only
    On the Effectiveness of Simhash for Detecting Near-Miss Clones in Large Scale Software Systems
    (IEEE, 2011) Uddin, M.S.; Roy, C.K.; Schneider, K.A.; Hindle, A.
    Clone detection techniques essentially cluster textually, syntactically and/or semantically similar code fragments in or across software systems. For large datasets, similarity identification is costly both in terms of time and memory, and especially so when detecting near-miss clones where lines could be modified, added and/or deleted in the copied fragments. The capability and effectiveness of a clone detection tool mostly depends on the code similarity measurement technique it uses. A variety of similarity measurement approaches have been used for clone detection, including fingerprint based approaches, which have had varying degrees of success notwithstanding some limitations. In this paper, we investigate the effectiveness of simhash, a state of the art fingerprint based data similarity measurement technique for detecting both exact and near-miss clones in large scale software systems. Our experimental data show that simhash is indeed effective in identifying various types of clones in a software system despite wide variations in experimental circumstances. The approach is also suitable as a core capability for building other tools, such as tools for: incremental clone detection, code searching, and clone management.
  • No Thumbnail Available
    ItemMetadata only
    SimCad: An extensible and faster clone detection tool for large scale software systems
    (IEEE, 2013) Uddin, M.S.; Roy, C.K.; Schneider, K.A.
    Code cloning is an inevitable phenomenon in evolution of software systems. To reduce the harmful effects of clones in software evolution, they need to be identified correctly as well in a time efficient way. There might be various types of clones in a software system. Earlier research shows detection of near-miss clones in large datasets appears to be costly in terms of time and memory. Among the clone detection tools available in practice, not very many of them are found effective in that regard. In this paper we present a standalone clone detection tool SimCad. It is based on a highly scalable and faster clone detection algorithm designed to detect both exact and near-miss clones in large-scale software systems. One of the potential aspects of SimCad is that its clone detection function is made more portable by packaging it into a library called SimLib. Thus, SimLib now can be used as an off-the-shelf clone detection library that can be easily integrated into other applications that are designed to work based on detected clones. For example, a standalone tool or an Integrated Development Environment (IDE) plugin can use SimLib for realtime clone detection while providing its own services like clone visualization and/or clone management functionalities. We hope that both researchers and developers would enjoy and utilize the benefit of using these tools in different aspects of detection and management of clones in software.