Conflicting changes are a major challenge in branch-based development and modeling. State-of-the-art research proposes continuous analysis via attempted three-way merges to find potential merge conflicts early on. The...
详细信息
ISBN:
(纸本)9798400706226
Conflicting changes are a major challenge in branch-based development and modeling. State-of-the-art research proposes continuous analysis via attempted three-way merges to find potential merge conflicts early on. These approaches are computation-heavy due to the necessity of comparing all variant combinations, ideally for each change. This work proposes a conflict approximation algorithm (oracle) for quick feedback. The oracle approximates conflicts using critical pair analysis on tracked delta sequences, providing a quick feedback loop. The oracle is paired with a classical slow-but-precise full model comparison algorithm, which is run occasionally to validate the oracle's results. This work contributes the Sketch-based Critical Pair Analysis (SCPA) approach for fast merge conflict estimation. SCPA's runtime depends only on the number of changes and not the model size. We evaluate SCPA against EMFCompare in different simulated model evolution scenarios. We found that for the investigated model sizes, SCPA is faster by a magnitude while the number of found conflicts strongly correlates with EMFCompare.
There has been an exponential growth in social networking and online shopping with the internet revolution in the recent past. Viral marketing, exploiting social networks to promote various products, has proved succes...
详细信息
ISBN:
(纸本)9781509049974
There has been an exponential growth in social networking and online shopping with the internet revolution in the recent past. Viral marketing, exploiting social networks to promote various products, has proved successful in influencing the public compared to other media. One well known task in this area is to choose the best nodes that maximize the overall influence propagated in the social network. t-Influence Maximization problem has been addressed in this paper which can be defined as maximizing the overall influence in a social network by selecting seeds for the given t products with their seed requirements. Constraints are set on number of products to be recommended for any single user (to avoid spamming) and total number of seeds to be selected for a particular product (budget constraint). The technique we have used, a greedy algorithm to the aforementioned t-influence maximization problem. It not only allocates seeds with maximum total influence, but also ensures that any one product doesn't dictate the overall influence and a fair selection is done. An efficient algorithm is designed for calculating the approximate influence of the selected nodes which is important in practical situations. Effectiveness and scalability of the algorithm is analyzed and verified using simulations on real-life facebook data.
This letter proposes a distributed alternating mixed discrete-continuous (DAMDC) algorithm to approach the oracle algorithm based on the diffusion strategy for parameter and spectrum estimation over sensor networks. A...
详细信息
This letter proposes a distributed alternating mixed discrete-continuous (DAMDC) algorithm to approach the oracle algorithm based on the diffusion strategy for parameter and spectrum estimation over sensor networks. A least mean squares (LMS) type algorithm that obtains the oracle matrix adaptively is developed and compared with the existing sparsity-aware and conventional algorithms. The proposed algorithm exhibits improved performance in terms of mean square deviation and power spectrum estimation accuracy. Numerical results show that the DAMDC algorithm achieves excellent performance.
In the last years, decomposition techniques have seen an increasing application to the solution of problems from operations research and combinatorial optimization, in particular in network theory and graph theory. Th...
详细信息
暂无评论