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Documents authored by Zhang, Bo


Found 3 Possible Name Variants:

Zhang, Bo

Document
Software Engineering in Practice Track Paper
CoEvolve: Feedback-Driven Policy-Harness Maintenance for Industrial LLM Auditing Systems

Authors: Yiyang Peng, Gang Lv, Yifeng Gou, Qizhao Wang, Bo Zhang, Ming Zhang, Qing Xu, Xiaosong Ding, Yu Shen, Yusang Xiong, Xinyao Xiao, and Xinyu Liu

Published in: LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)


Abstract
Industrial LLM compliance-auditing systems are maintained through both expert policy and executable support chains. After deployment, changing standards, user appeals, expert reviews, and report variants expose failures in rule interpretation, parsing, evidence binding, context assembly, output contracts, and regression checks. We propose CoEvolve, a feedback-driven policy-harness maintenance workflow in which an LLM maintenance agent proposes coordinated updates, an independent verifier checks target repair, regression, stability, and semantic risks, and experts confirm releasable changes. We report a five-month industrial experience in a Chinese compliance-auditing service, covering 33 production feedback instances, 128 audited systems, 384 reports, and 24,192 checklist items. The evaluation compares four frozen workflow states formed by different maintenance organizations; it is not a controlled comparison of methods on identical maintenance inputs. On a 979-item monthly holdout benchmark, the CoEvolve replay state reached 93.5% accuracy, 4.1 percentage points above prompt/SOP maintenance at 89.4%. Manual co-maintenance reached 93.6% (916/979), while CoEvolve reached 915/979; their Wilson intervals overlap and the five-system effective sample is small. Because the replay input included visible historical manual artifacts, this result shows that CoEvolve reconstructed a comparable release state from those artifacts, not that it substituted for manual co-maintenance. Across replay tasks, CoEvolve externalized 4.97 candidate attempts per feedback instance on average. The experience supports governed policy-harness maintenance without retraining and highlights verifier-gate predicates and blocked-candidate records as transferable release-governance mechanisms.

Cite as

Yiyang Peng, Gang Lv, Yifeng Gou, Qizhao Wang, Bo Zhang, Ming Zhang, Qing Xu, Xiaosong Ding, Yu Shen, Yusang Xiong, Xinyao Xiao, and Xinyu Liu. CoEvolve: Feedback-Driven Policy-Harness Maintenance for Industrial LLM Auditing Systems. In 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 394, pp. 80:1-80:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{peng_et_al:LIPIcs.ESEM.2026.80,
  author =	{Peng, Yiyang and Lv, Gang and Gou, Yifeng and Wang, Qizhao and Zhang, Bo and Zhang, Ming and Xu, Qing and Ding, Xiaosong and Shen, Yu and Xiong, Yusang and Xiao, Xinyao and Liu, Xinyu},
  title =	{{CoEvolve: Feedback-Driven Policy-Harness Maintenance for Industrial LLM Auditing Systems}},
  booktitle =	{20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)},
  pages =	{80:1--80:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-450-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{394},
  editor =	{Feldt, Robert and Paasivaara, Maria and Mendez, Daniel and Wagner, Stefan and Bar\'{o}n, Marvin Mu\~{n}oz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.80},
  URN =		{urn:nbn:de:0030-drops-280480},
  doi =		{10.4230/LIPIcs.ESEM.2026.80},
  annote =	{Keywords: LLM auditing, policy-harness maintenance, production feedback, verifier gates, software engineering in practice}
}
Document
Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)

Authors: Bo Zhang, Filip Krikava, Romain Rouvoy, and Lionel Seinturier

Published in: DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)


Abstract
Arising with the popularity of Hadoop, optimizing Hadoop executions has grabbed lots of attention from research community. Many research contributions are proposed to elevate Hadoop performance, particularly in the domain of self-adaptive software systems. However, due to the complexity of Hadoop operation and the difficulty to reproduce experiments, the efforts of these Hadoop-related research are hard to be evaluated. To address this limitation, we propose a research acceleration platform for rapid prototyping and evaluation of self-adaptive behavior in Hadoop clusters. It provides an automated manner to quickly and easily provision reproducible Hadoop environments and execute acknowledged benchmarks. This platform is based on the state-of-the-art container technology that supports both distributed configurations as well as standalone single-host setups. We demonstrate the approach on a complete implementation of a concrete Hadoop self-adaptive case study.

Cite as

Bo Zhang, Filip Krikava, Romain Rouvoy, and Lionel Seinturier. Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact). In Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017). Dagstuhl Artifacts Series (DARTS), Volume 3, Issue 1, pp. 1:1-1:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@Article{zhang_et_al:DARTS.3.1.1,
  author =	{Zhang, Bo and Krikava, Filip and Rouvoy, Romain and Seinturier, Lionel},
  title =	{{Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)}},
  pages =	{1:1--1:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  editor =	{Zhang, Bo and Krikava, Filip and Rouvoy, Romain and Seinturier, Lionel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.3.1.1},
  URN =		{urn:nbn:de:0030-drops-71392},
  doi =		{10.4230/DARTS.3.1.1},
  annote =	{Keywords: Hadoop, Docker, Rapid Prototyping, Benchmark}
}

Zhang, Mingbo

Document
Decomposition of Differential Polynomials

Authors: Xiao-Shan Gao and Mingbo Zhang

Published in: Dagstuhl Seminar Proceedings, Volume 6271, Challenges in Symbolic Computation Software (2006)


Abstract
We present an algorithm to decompose nonlinear differential polynomials in one variable and with rational functions as coefficients. The algorithm is implemented in Maple for the {em constant field} case. The program can be used to decompose differential polynomials with more than one thousand terms effectively.

Cite as

Xiao-Shan Gao and Mingbo Zhang. Decomposition of Differential Polynomials. In Challenges in Symbolic Computation Software. Dagstuhl Seminar Proceedings, Volume 6271, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)


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@InProceedings{gao_et_al:DagSemProc.06271.9,
  author =	{Gao, Xiao-Shan and Zhang, Mingbo},
  title =	{{Decomposition of Differential Polynomials}},
  booktitle =	{Challenges in Symbolic Computation Software},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6271},
  editor =	{Wolfram Decker and Mike Dewar and Erich Kaltofen and Stephen Watt},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06271.9},
  URN =		{urn:nbn:de:0030-drops-7726},
  doi =		{10.4230/DagSemProc.06271.9},
  annote =	{Keywords: Decomposition, differential polynomial, difference polynomial}
}

Zhang, Wenbo

Document
Track B: Automata, Logic, Semantics, and Theory of Programming
Bisimulation Equivalence of Pushdown Automata Is Ackermann-Complete

Authors: Wenbo Zhang, Qiang Yin, Huan Long, and Xian Xu

Published in: LIPIcs, Volume 168, 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)


Abstract
Deciding bisimulation equivalence of two pushdown automata is one of the most fundamental problems in formal verification. Though Sénizergues established decidability of this problem in 1998, it has taken a long time to understand its complexity: the problem was proven to be non-elementary in 2013, and only recently, Jančar and Schmitz showed that it has an Ackermann upper bound. We improve the lower bound to Ackermann-hard, and thus close the complexity gap.

Cite as

Wenbo Zhang, Qiang Yin, Huan Long, and Xian Xu. Bisimulation Equivalence of Pushdown Automata Is Ackermann-Complete. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 141:1-141:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{zhang_et_al:LIPIcs.ICALP.2020.141,
  author =	{Zhang, Wenbo and Yin, Qiang and Long, Huan and Xu, Xian},
  title =	{{Bisimulation Equivalence of Pushdown Automata Is Ackermann-Complete}},
  booktitle =	{47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)},
  pages =	{141:1--141:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-138-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{168},
  editor =	{Czumaj, Artur and Dawar, Anuj and Merelli, Emanuela},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2020.141},
  URN =		{urn:nbn:de:0030-drops-125482},
  doi =		{10.4230/LIPIcs.ICALP.2020.141},
  annote =	{Keywords: PDA, Bisimulation, Equivalence checking}
}

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