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Documents authored by Ding, Chen

Found 2 Possible Name Variants:

Ding, Chen

Document
DOI: 10.4230/DagRep.15.8.1
Software Performance Engineering (Dagstuhl Seminar 25341)

Authors: Chen Ding, Charles E. Leiserson, Yihan Sun, and Bruce Hoppe

Published in: Dagstuhl Reports, Volume 15, Issue 8 (2026)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25341 on software performance engineering. This seminar convened researchers from diverse intellectual communities across computer science to synthesize a collective understanding of this fragmented discipline and advance software performance engineering as a rigorous and principled scientific field in its own right. With connections established by this seminar, we are creating a unique arena for computer science researchers to cross-fertilize by sharing performance-engineering tools, techniques, opportunities, challenges, and open problems in their own domains of expertise. The major activities included 29 talks on recent research, five working groups that discussed topics like tools, community-building, education, and LLMs, and three "world cafe" sessions with in-depth conversations among participants on guiding questions for advancing software performance engineering.
Cite as

Chen Ding, Charles E. Leiserson, Yihan Sun, and Bruce Hoppe. Software Performance Engineering (Dagstuhl Seminar 25341). In Dagstuhl Reports, Volume 15, Issue 8, pp. 1-28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{ding_et_al:DagRep.15.8.1,
  author =	{Ding, Chen and Leiserson, Charles E. and Sun, Yihan and Hoppe, Bruce},
  title =	{{Software Performance Engineering (Dagstuhl Seminar 25341)}},
  pages =	{1--28},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2026},
  volume =	{15},
  number =	{8},
  editor =	{Ding, Chen and Leiserson, Charles E. and Sun, Yihan and Hoppe, Bruce},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.8.1},
  URN =		{urn:nbn:de:0030-drops-257759},
  doi =		{10.4230/DagRep.15.8.1},
  annote =	{Keywords: applications, productivity tools, software performance engineering, theory and practice}
}
Document
DOI: 10.4230/LIPIcs.CPM.2021.24
AWLCO: All-Window Length Co-Occurrence

Authors: Joshua Sobel, Noah Bertram, Chen Ding, Fatemeh Nargesian, and Daniel Gildea

Published in: LIPIcs, Volume 191, 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)

Abstract
Analyzing patterns in a sequence of events has applications in text analysis, computer programming, and genomics research. In this paper, we consider the all-window-length analysis model which analyzes a sequence of events with respect to windows of all lengths. We study the exact co-occurrence counting problem for the all-window-length analysis model. Our first algorithm is an offline algorithm that counts all-window-length co-occurrences by performing multiple passes over a sequence and computing single-window-length co-occurrences. This algorithm has the time complexity O(n) for each window length and thus a total complexity of O(n²) and the space complexity O(|I|) for a sequence of size n and an itemset of size |I|. We propose AWLCO, an online algorithm that computes all-window-length co-occurrences in a single pass with the time complexity of O(n) and space complexity of O(√{n|I|}), assuming perfect hashing. Following this, we generalize our use case to patterns in which we propose an algorithm that computes all-window-length co-occurrence with time complexity O(n|I|), assuming perfect hashing, with an additional pre-processing step and space complexity O(√{n|I|}+|I|), plus the overhead of the Aho-Corasick algorithm [Aho and Corasick, 1975].
Cite as

Joshua Sobel, Noah Bertram, Chen Ding, Fatemeh Nargesian, and Daniel Gildea. AWLCO: All-Window Length Co-Occurrence. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 24:1-24:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{sobel_et_al:LIPIcs.CPM.2021.24,
  author =	{Sobel, Joshua and Bertram, Noah and Ding, Chen and Nargesian, Fatemeh and Gildea, Daniel},
  title =	{{AWLCO: All-Window Length Co-Occurrence}},
  booktitle =	{32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
  pages =	{24:1--24:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-186-3},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{191},
  editor =	{Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.24},
  URN =		{urn:nbn:de:0030-drops-139759},
  doi =		{10.4230/LIPIcs.CPM.2021.24},
  annote =	{Keywords: Itemsets, Data Sequences, Co-occurrence}
}

Chen, Dingding

Document
DOI: 10.4230/LIPIcs.CP.2022.39
Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs

Authors: Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, and Junsong Gao

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Tree-based backtracking search is an important technique to solve Distributed Constraint optimization Problems (DCOPs), where agents cooperatively exhaust the search space by branching on each variable to divide subproblems and reporting the results to their parent after solving each subproblem. Therefore, effectively reusing the historical search results can avoid unnecessary resolutions and substantially reduce the overall overhead. However, the existing caching schemes for asynchronous algorithms cannot be applied directly to synchronous ones, in the sense that child agent reports the lower and upper bound rather than the precise cost of exploration. In addition, the existing caching scheme for synchronous algorithms has the shortcomings of incompleteness and low cache utilization. Therefore, we propose a new caching scheme for tree-based synchronous backtracking search, named Retention Scheme (RS). It utilizes the upper bounds of subproblems which avoid the reuse of suboptimal solutions to ensure the completeness, and deploys a fine-grained cache information unit targeted at each child agent to improve the cache-hit rate. Furthermore, we introduce two new cache replacement schemes to further improve performance when the memory is limited. Finally, we theoretically prove the completeness of our method and empirically show its superiority.
Cite as

Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, and Junsong Gao. Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{wang_et_al:LIPIcs.CP.2022.39,
  author =	{Wang, Jie and Chen, Dingding and Chen, Ziyu and Liu, Xiangshuang and Gao, Junsong},
  title =	{{Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{39:1--39:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.39},
  URN =		{urn:nbn:de:0030-drops-166685},
  doi =		{10.4230/LIPIcs.CP.2022.39},
  annote =	{Keywords: DCOP, Cache, Any-space Algorithms, Complete Search Algorithms}
}
Document
DOI: 10.4230/LIPIcs.CP.2021.41
A Bound-Independent Pruning Technique to Speeding up Tree-Based Complete Search Algorithms for Distributed Constraint Optimization Problems

Authors: Xiangshuang Liu, Ziyu Chen, Dingding Chen, and Junsong Gao

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
Complete search algorithms are important methods for solving Distributed Constraint Optimization Problems (DCOPs), which generally utilize bounds to prune the search space. However, obtaining high-quality lower bounds is quite expensive since it requires each agent to collect more information aside from its local knowledge, which would cause tremendous traffic overheads. Instead of bothering for bounds, we propose a Bound-Independent Pruning (BIP) technique for existing tree-based complete search algorithms, which can independently reduce the search space only by exploiting local knowledge. Specifically, BIP enables each agent to determine a subspace containing the optimal solution only from its local constraints along with running contexts, which can be further exploited by any search strategies. Furthermore, we present an acceptability testing mechanism to tailor existing tree-based complete search algorithms to search the remaining space returned by BIP when they hold inconsistent contexts. Finally, we prove the correctness of our technique and the experimental results show that BIP can significantly speed up state-of-the-art tree-based complete search algorithms on various standard benchmarks.
Cite as

Xiangshuang Liu, Ziyu Chen, Dingding Chen, and Junsong Gao. A Bound-Independent Pruning Technique to Speeding up Tree-Based Complete Search Algorithms for Distributed Constraint Optimization Problems. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 41:1-41:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{liu_et_al:LIPIcs.CP.2021.41,
  author =	{Liu, Xiangshuang and Chen, Ziyu and Chen, Dingding and Gao, Junsong},
  title =	{{A Bound-Independent Pruning Technique to Speeding up Tree-Based Complete Search Algorithms for Distributed Constraint Optimization Problems}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{41:1--41:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.41},
  URN =		{urn:nbn:de:0030-drops-153324},
  doi =		{10.4230/LIPIcs.CP.2021.41},
  annote =	{Keywords: DCOP, complete algorithms, search}
}
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