Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6885290 | Journal of Systems and Software | 2018 | 21 Pages |
Abstract
To evaluate Lascad's capability of categorizing software, we used three labeled data sets: two sets from prior work and one larger set that we created with 103 applications implemented in 19 different languages. By comparing Lascad with prior approaches on these data sets, we found Lascad to be more usable and outperform existing tools. To evaluate Lascad's capability of similar application detection, we reused our 103-application data set and a newly created unlabeled data set of 5220 applications. The relevance scores of the Top-1 retrieved applications within these two data sets were, separately, 70% and 71%. Overall, Lascad effectively categorizes and detects similar programs across languages.
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Authors
Doaa Altarawy, Hossameldin Shahin, Ayat Mohammed, Na Meng,