Advertisement

Frontiers of Computer Science in China

, Volume 2, Issue 1, pp 1–11 | Cite as

Basic research in computer science and software engineering at SKLCS

  • Jian ZhangEmail author
  • Wenhui Zhang
  • Naijun Zhan
  • Yidong Shen
  • Haiming Chen
  • Yunquan Zhang
  • Yongji Wang
  • Enhua Wu
  • Hongan Wang
  • Xueyang Zhu
Review Article

Abstract

The State Key Laboratory of Computer Science (SKLCS) is committed to basic research in computer science and software engineering. The research topics of the laboratory include: concurrency theory, theory and algorithms for real-time systems, formal specifications based on context-free grammars, semantics of programming languages, model checking, automated reasoning, logic programming, software testing, software process improvement, middleware technology, parallel algorithms and parallel software, computer graphics and human-computer interaction. This paper describes these topics in some detail and summarizes some results obtained in recent years.

Keywords

concurrency theory real-time system automated reasoning formal specification parallel algorithms software process middleware computer graphics human-computer interaction 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lin H M. Complete inference systems for weak bisimulation equivalences in the π-calculus. Information and Computation, 2003, 180(1): 1–29zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Lin H M, Wang Y. Axiomatising timed automata. Acta Informatica, 2002, 38(4): 277–305zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Jiao L, Huang H J, Cheung T Y. Property-preserving composition by place merging. Journal of Circuits, Systems and Computers, 2005, 14(4): 793–812CrossRefGoogle Scholar
  4. 4.
    Huang H J, Jiao L, Cheung T Y. Property-preserving subnet reductions for designing manufacturing systems with shared resources. Theoretical Computer Science, 2005, 332(1–3): 461–485zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Jiao L, Cheung T Y, Lu WM. Handling synchronization problem in Petri-net-based system design by property-preserving transition-reduction. The Computer Journal, 2005, 48(6): 692–701CrossRefGoogle Scholar
  6. 6.
    Jiao L, Cheung T Y. Compositional verification for workflow nets. Journal of Circuits, Systems and Computers, 2006, 15(4): 551–570CrossRefGoogle Scholar
  7. 7.
    Zhang W H. Combining static analysis and case-based search space partitioning for reducing peak memory in model checking. Journal of Computer Science and Technology, 2003, 18(6): 762–770zbMATHMathSciNetCrossRefGoogle Scholar
  8. 8.
    Lv Y, Lin H M, Pan H. Computing invariants for parameter abstraction. In: Schneider K, Hoe J, eds. Proceedings of MEMOCODE. Nice: IEEE Press, 2007, 29–38Google Scholar
  9. 9.
    Wu P, Lin H M. Model-based testing of concurrent programs with predicate sequencing constrains. International Journal of Software Engineering and Knowledge Engineering, 2006, 16(5): 727–746CrossRefGoogle Scholar
  10. 10.
    Lin H M. A predicate mu-calculus for mobile ambients. Journal of Computer Science and Technology, 2004, 20(1): 95–104CrossRefGoogle Scholar
  11. 11.
    Lin H M. A predicate spatial logic and model checking for mobile processes. In: Liu Z M, Araki K, eds. Proceedings of ICTAC. Berlin: Springer, 2004, 36Google Scholar
  12. 12.
    Zhan N J, Majster-Cederbaum M. Deriving non-determinism from conjunction and disjunction. In: Wang F, ed. Proceedings of FORTE. Berlin: Springer, 2005, 351–365Google Scholar
  13. 13.
    Zhan N J, Wu J. Compositionality of fixpoint logic with chop. In: Hung D V, Wirsing M, eds. Proceedings of ICTAC. Berlin: Springer, 2005, 136–150Google Scholar
  14. 14.
    Zhang WH. Model checking with SAT-based characterization of ACTL formulas. In: Proceedings of ICFEM. Berlin: Springer, 2007, 191–211Google Scholar
  15. 15.
    Zhou C C, Hoare C A R, Ravn A. A calculus of durations. Information Processing Letters, 1991, 40(5): 269–276zbMATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Damm W, Hungar H, Olderog E-R. Verification of cooperating traffic agents. International Journal of Control, 2006, 79(5): 395–421zbMATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Zhou C C, Hansen MR. Duration calculus: a formal approach to real-time systems. EATCS Series of Monographs in Theoretical Computer Science. Berlin: Springer, 2004Google Scholar
  18. 18.
    Xu QW, Zhan N J. Formalizing scheduling theories with duration calculus. Nordic Journal of Computing, to appearGoogle Scholar
  19. 19.
    Liu C L, Layland J W. Scheduling algorithms for multiprogramming in a hard real-time environment. Journal of ACM, 1973, 20(1): 46–61zbMATHCrossRefMathSciNetGoogle Scholar
  20. 20.
    Li GY, Tang Z S. Modeling real-time systems with continuous-time temporal logic. In: George C, Miao H, eds. Proceedings of ICFEM. Berlin: Springer, 2002, 231–236Google Scholar
  21. 21.
    Tang Z S. A program development support environment based on temporal logic. In: Proceedings of PLSD. North Hollland, 1983Google Scholar
  22. 22.
    Li GY, Tang Z S. Translating a continuous-time temporal logic into timed automata. In: Ohori A, ed. Proceedings of APLAS. Berlin: Springer, 2003, 322–338Google Scholar
  23. 23.
    Yan R J, Li G Y, Tang Z S. Symbolic model checking of finite precision timed automata. In: Hung D V, Wirsing M, eds. Proceedings of ICTAC. Berlin: Springer, 2005, 272–287Google Scholar
  24. 24.
    Fu Y, Wang H. Distributed utilization control for real-time clusters with load balancing. In: Proceedings of IEEE RTSS. Rio, 2006, 137–146Google Scholar
  25. 25.
    Zhou H, Wang Y J, Wang Q. Measuring internet bottlenecks: location, capacity, and available bandwidth. In: Lu XC, Zhao W, eds. Proceedings of CNMC. Berlin: Springer, 2005, 1052–1062Google Scholar
  26. 26.
    Wang X X, Wang Y J, Zhou J H, et al. Congestion control algorithm based on improved model in large-delay networks. Acta Electronica Sinica, 2005, 33(5): 842–846Google Scholar
  27. 27.
    Wang X L, Wang Y J, Zhou H, et al. PSO-PID: a novel controller for AQM routers. In: Proceedings of IEEE/IFIP WOCN. Bangalore, 2006, 1–5Google Scholar
  28. 28.
    Wang X L, Wang Y J, Zeng H T, et al. Particle swarm optimization with escape velocity. In: Proceedings of CIS. Guangzhou: IEEE Press, 2006, 457–460Google Scholar
  29. 29.
    Shen Y D, You J H, Yuan L Y, et al. A dynamic approach to characterizing termination of general logic programs. ACM Transactions on Computational Logic, 2003, 4(4): 417–430CrossRefMathSciNetGoogle Scholar
  30. 30.
    Shen Y D, You J H, Yuan L Y. Enhancing global SLS-resolution with loop cutting and tabling mechanisms. Theoretical Computer Science, 2004, 328(3): 271–287zbMATHCrossRefMathSciNetGoogle Scholar
  31. 31.
    Dowek G, Jiang Y. Eigenvariables, bracketing and the decidability of positive minimal predicate logic. Theoretical Computer Science, 2006, 360(1–3): 193–208zbMATHCrossRefMathSciNetGoogle Scholar
  32. 32.
    Zhang WH, Huang Z, Zhang J. Parallel execution of stochastic search procedures on reduced SAT instances. In: Proceedings of PRICAI. Berlin: Springer, 2002, 108–117Google Scholar
  33. 33.
    Jia X X, Zhang J. Predicate-oriented isomorphism elimination in model finding. In: Proceedings of IJCAI. St Louis: Morgan Kaufmann Publishers, 2005, 1525–1526Google Scholar
  34. 34.
    Jia X X, Zhang J. A powerful technique to eliminate isomorphism in finite model search. In: Proceedings of IJCAR. Berlin: Springer, 2006, 318–331Google Scholar
  35. 35.
    Dong Y M. MLIRF method for specification acquisition and reuse. In: Proceedings of the 9th National Conference of China Computer Federation. Chongqing, 1996, 21–27 (in Chinese)Google Scholar
  36. 36.
    Dong YM. Recursive functions of context free languages (I) — the definitions of CFPRF and CFRF. Science in China Series F, 2002, 45(1): 25–39zbMATHMathSciNetGoogle Scholar
  37. 37.
    Dong YM. Recursive functions of context free languages (II) — validity of CFPRF and CFRF definitions. Science in China Series F, 2002, 45(2): 1–21Google Scholar
  38. 38.
    Dong YM. An interactive learning algorithm for acquisition of concepts represented as CFL. Journal of Computer Science and Technology, 1998, 13(1): 1–8zbMATHMathSciNetGoogle Scholar
  39. 39.
    Dong Y M, Li K, Chen H, et al. Design and implementation of the formal specification acquisition system SAQ. In: Proceedings of Conference Software: Theory and Practice, IFIP 16th World Computer Congress 2000. Beijing, 2000, 201–211Google Scholar
  40. 40.
    Sun J C. Multivariate fourier series over a class of non tensorproduct partition domains. Journal of Computational Mathematics, 2003, 21(1): 53–62zbMATHMathSciNetGoogle Scholar
  41. 41.
    Sun J C, Yao J F. Fast generalized discrete fourier transforms on hexagon domains. Chinese Journal of Numerical Mathematics and Application, 2004, 26(3): 351–366MathSciNetGoogle Scholar
  42. 42.
    Sun J C, Li H Y. Generalized fourier transform on an arbitrary triangular domain. Advances in Computational Mathematics, 2005, 22: 223–248zbMATHCrossRefMathSciNetGoogle Scholar
  43. 43.
    Yao J F, Sun J C. HFFT on parallel dodecahedron domains and its parallel implementation. Numerical computation and computer applications, 2004, 4: 304–313 (in Chinese)Google Scholar
  44. 44.
    Sun J C. Multivariate fourier transform methods over simplex and super-simplex domains. Journal of Computational Mathematics, 2006, 24(3): 305–322zbMATHMathSciNetGoogle Scholar
  45. 45.
    Zhang Y Q. Performance optimizations on parallel numerical software package and study on memory complexity. Dissertation for the Doctoral Degree. Beijing: Institute of Software, Chinese Academy of Sciences, 2000Google Scholar
  46. 46.
    Zhang Y Q. DRAM(h): a parallel computation model for high performance numerical computing. Chinese Journal of Computers, 2003, 26(12): 1660–1670MathSciNetGoogle Scholar
  47. 47.
    Zhang Y Q, Chen G L, Sun G Z, et al. Models of parallel computation: a survey and classification. Frontiers of Computer Science in China, 2007, 1(2): 156–165CrossRefGoogle Scholar
  48. 48.
    Zhang Y Q, Sun J C, Tang Z M, et al. Memory complexity in high performance computing. In: Proceedings of HPC’ASIA. Singapore, 1998: 142–151Google Scholar
  49. 49.
    Alpern B, Carter L, Feig E, et al. The Uniform Memory Hierarchy Model of Computation. Algorithmica, 1994, 12(2–3): 72–109zbMATHCrossRefMathSciNetGoogle Scholar
  50. 50.
    Culler D, Karpy R, Patterson D, et al. LogP: towards a realistic model of parallel computation. In: Proceedings of PPoPP. San Diego, 1993, 1–12Google Scholar
  51. 51.
    Li M S. Expanding the horizons of software development processes: a 3-D integrated methodology. In: Proceedings of SPW. Beijing, 2005, 54–67Google Scholar
  52. 52.
    Li M S. Assessing 3-D integrated software development processes: a new benchmark. In: Proceedings of SPW/ProSim. Shanghai, 2006, 15–38Google Scholar
  53. 53.
    Wang Q, Li M S. Software process management: practices in China. In: Proceedings of SPW. Beijing, 2005, 317–331Google Scholar
  54. 54.
    Li M S. TRISO-model: a new approach to integrated software process assessment and improvement. Software Process: Improvement and Practice, 2007, 12(5): 387–398CrossRefGoogle Scholar
  55. 55.
    Wang Q, Xiao J, Li M S, et al. A process-agent construction method for software process modeling in SoftPM. In: Proceedings of SPW/ProSim. Shanghai, 2006, 204–213Google Scholar
  56. 56.
    Li N, Li M S, Wang Q, et al. A negotiation model for the process agent in an agent-based process-centered software engineering environment. In: Proceedings of SEKE. San Francisco, 2006, 664–669Google Scholar
  57. 57.
    Zhao X, Chan K, Li M S. Applying agent technology to software process modeling and process-centered software engineering environment. In: Proceedings of SAC. Santa Fe, 2005, 1529–1533Google Scholar
  58. 58.
    Xiao J, Osterweil L J, Zhang L, et al. Applying little-JIL to describe process-agent knowledge in SoftPM. In: Proceedings of SPW/ProSim. Shanghai, 2006, 214–221Google Scholar
  59. 59.
    Zhang L, Wang Q, Xiao J, et al. A tool to create process-agents for OEC-SPM from historical project data. In: Proceedings of ICSP. Beilin: Springer, 2007, 84–95Google Scholar
  60. 60.
    Xiao J, Osterweil L J, Zhang L, et al. Applying little-JIL to describe process-agent knowledge and support project planning. Software Process: Improvement and Practice, 2007, 12(5): 437–448CrossRefGoogle Scholar
  61. 61.
    Li MS, Yang Q, Zhai J, et al. On mobility of software processes. In: Proceedings of SPW/ProSim. Shanghai, 2006, 105–114Google Scholar
  62. 62.
    Yang Q, Li M S, Wang Q, et al. An algebraic approach for managing inconsistencies in software processes. In: Proceedings of ICSP. Berlin: Springer, 2007, 121–133Google Scholar
  63. 63.
    Yuan F, Li MS, Wan Z. SPEM2XPDL-towards SPEM model enactment. In: Proceedings of SERP. Las vegas, 2006, 240–245Google Scholar
  64. 64.
    Li J, Li M S, Wu Z, et al. A SPEM-based software process metamodel for CMM. Journal of Software, 2005, 16(8): 1366–1377CrossRefGoogle Scholar
  65. 65.
    Yang D, Wan Y, Tang Z, et al. COCOMO-U: an extension of COCOMO II for cost estimation with uncertainty. In: Proceeding of SPW/ProSim. Shanghai, 2006, 132–141Google Scholar
  66. 66.
    Yang D, Boehm B, Yang Y, et al. Coping with the cone of uncertainty: an empirical study of the SAIV process model. In: Proceedings of ICSP. Berlin: Springer, 2007, 37–48Google Scholar
  67. 67.
    He M, Yang Y, Wang Q, et al. Cost estimation and analysis for government contract pricing in China. In: Proceedings of ICSP. Berlin: Springer, 2007, 134–146Google Scholar
  68. 68.
    Wang Q, Jiang N, Gou L, et al. BSR: a statistic-based approach for establishing and refining software process performance baseline. In: Proceedings of ICSE. Shanghai, 2006, 585–594Google Scholar
  69. 69.
    Wang Q, Li M S. Measuring and improving software process in China. In: Proceedings of ISESE. Noosa Heads, 2005, 183–192Google Scholar
  70. 70.
    Wang Q, Li M S, Liu X. An active measurement model for software process control and improvement. Journal of Software, 2005, 16(3): 407–418zbMATHCrossRefGoogle Scholar
  71. 71.
    Ruan L, Wang Y, Wang Q, et al. ARIMAmmse: an improved ARIMA-based software productivity prediction method. In: Proceedings of COMPSAC. Chicago, 2006, 17–21Google Scholar
  72. 72.
    Ruan L, Wang Y, Wang Q, et al. Empirical study on benchmarking software development tasks. In: the International Conference on Software Process. Minneapolis, 2007, 221–232Google Scholar
  73. 73.
    Zhang S, Wang Y, Yuan F, et al. Mining software repositories to understand the performance of individual developers. In: Proceedings of COMPSAC 2007. Beijing, 2007, 625–626Google Scholar
  74. 74.
    Zhang S, Wang Y, Tong J, et al. Evaluation of project quality: a DEA-based approach. In: Proceedings of SPW/ProSim. Shanghai, 2005, 88–96Google Scholar
  75. 75.
    Wang J, Li M S. A tridimensional requirements model and its support for stakeholder coordination. Journal of Software, 2007, 18(10): 2380–2392CrossRefGoogle Scholar
  76. 76.
    Shu F, Zhao Y, Wang J, et al. User-driven requirements elicitation method with the support of personalized domain knowledge. Computer Research and Development, 2007, 44(6): 1044–1052CrossRefGoogle Scholar
  77. 77.
    Huang M, Shu F, Li MS. A risk-driven method for prioritizing requirements in iteration development. Journal of Software, 2006, 17(12): 2450–2460zbMATHCrossRefGoogle Scholar
  78. 78.
    Li M S, Huang M, Shu F, et al. A risk-driven method for extreme programming release planning. In: Proceedings of ICSE 2006. Shanghai, 2006, 423–430Google Scholar
  79. 79.
    Huang T, Ding X N, Wei J. An application-semantics-based relaxed transaction model for internetware. Science in China Series F, 2006, 49(6): 774–791CrossRefGoogle Scholar
  80. 80.
    Huang T, Chen N J, Wei J, et al. OnceAS/Q: a QoS-enabled web application server. Journal of Software, 2004, 15(12): 1787–1799zbMATHGoogle Scholar
  81. 81.
    Chen H, Wu E H. An efficient radiosity solution for bump texture generation. Computer Graphics, 1990, 24(4): 125–134CrossRefGoogle Scholar
  82. 82.
    Chen H, Wu E H. Radiosity for furry surfaces. In: Post F H, Barth W, eds. Proceedings of EUROGRAPHICS. North-Holland: Elsevier Science Publishers, 1991, 447–457Google Scholar
  83. 83.
    Wu E H. A radiosity solution for illumination of random fractal surfaces. The Journal of Visualization and Computer Animation, 1995, 6(4): 219–229CrossRefGoogle Scholar
  84. 84.
    Chen Y Y, Sun H Q, Wu E H. Modeling and rendering snowy natural scenery using multi-mapping techniques. The Journal of Visualization and Computer Animation, 2003, 14(1): 21–30zbMATHCrossRefGoogle Scholar
  85. 85.
    Xu Y Q, Chen Y Y, Lin S, et al. Photo-realistic rendering of knitwear using the lumislice. In: Proceedings of ACM SIGGRAPH. New York: ACM Press, 2001, 391–398Google Scholar
  86. 86.
    Liu X H, Wu E H. Hierarchical structure with focus criterion for rendering height field. Journal of Computer Science and Technology, 1998, 13(12): 1–8zbMATHMathSciNetGoogle Scholar
  87. 87.
    Wang W C, Wu E H. Adaptable splatting for irregular volume rendering. Computer Graphics Forum, 1999, 18(4): 213–222CrossRefGoogle Scholar
  88. 88.
    Wang WC, Wu E H, Max N. A selective rendering method for data visualization. Journal of Visualization and Computer Animation, 1999, 10(3): 123–131CrossRefGoogle Scholar
  89. 89.
    Wang W C, Zhou D H, Wu E H. Accelerating techniques in volume rendering of irregular data. Computers and Graphics, 1997, 21(3): 289–295zbMATHCrossRefGoogle Scholar
  90. 90.
    Wu E H, Liu Y Q, Liu X H. An improved study of real time fluid simulation on GPU (invited paper). Computer Animation and Virtual World, 2004, 15(3–4): 139–146CrossRefGoogle Scholar
  91. 91.
    Liu Y Q, Liu X H, Wu E H. Real-time 3D fluid simulation on GPU with complex obstacles. In: Proceedings of Pacific Graphics. Seoul: IEEE Computer Society, 2004, 247–256Google Scholar
  92. 92.
    Liu Y Q, Liu X H, Wu E H. Fluid simulations on GPU with complex boundary conditions. In: Proceedings of Poster Workshop on GPGPU, at ACM SIGGRAPG, 2004Google Scholar
  93. 93.
    Liu Y Q, Zhu H B, Liu X H, et al. Real time simulation of physically based on-surface flow. The Visual Computer, 2005, 21(8–10): 727–734CrossRefGoogle Scholar
  94. 94.
    Zhu H B, Liu X H, Liu Y Q, et al. Simulation of miscible binary mixtures based on lattice boltzmann method. Computer Animation and Virtual Worlds, 2006, 17(3–4): 403–411CrossRefGoogle Scholar
  95. 95.
    Wu E H, Zhu H B, Liu X H, et al. Physically based fluid dynamics and interactions. In: Proceedings of CyberWorlds. Lausanne: IEEE Computer Society, 2006, 3–13CrossRefGoogle Scholar
  96. 96.
    Fei GZ, Cai KY, Guo BN, et al. An adaptive sampling scheme for out-of-core simplification. Computer Graphics Forum, 2002, 21(2): 111–119CrossRefGoogle Scholar
  97. 97.
    Wang W C, Li J, Wu E H. 2D point-in-polygon test by classifying edges into layers. Computers and Graphics, 2005, 29(3): 427–439CrossRefMathSciNetGoogle Scholar
  98. 98.
    Wang WC, Li J, Sun HQ, et al. A layer-based representation of polyhedrons for point containment tests. IEEE Transactions on Visualization and Computer Graphics, 2007, to appearGoogle Scholar
  99. 99.
    Ao X, Wang XG, Tian F, et al. Cross-modal error correction of continuous handwriting recognition by Speech. In: Proceedings of ACM International Conference on Intelligent User Interfaces. Honolulu, 2007, 243–250Google Scholar
  100. 100.
    Ao X, Li J F, Wang X G, et al. Structuralizing digital ink for efficient selection. In: Proceedings of ACM International Conference on Intelligent User Interfaces. Sydney, 2006, 148–153Google Scholar
  101. 101.
    Li J F, Zhang X W, Ao X, et al. Sketch recognition with continuous feedback based on incremental intention extraction. In: Proceedings of ACM International Conference on Intelligent User Interfaces. San Diego, 2005, 145–150Google Scholar
  102. 102.
    Tian F, Ao X, Wang H A, et al. The tilt cursor: enhancing stimulus-response compatibility by providing 3D orientation cue of pen. In: ACM Conference on Human Factors in Computing Systems. San Jose, 2007, 303–306Google Scholar
  103. 103.
    Wang W X, Wang H, Dai G Z, et al. Visualization of large hierarchical data by circle packing. In: ACM Conference on Human Factors in Computing Systems. New York: ACM Press, 2006, 517–520Google Scholar
  104. 104.
    Xia M. Maximum edge-disjoint paths problem in planar graphs. In: Cai J Y, Cooper S B, Zhu H, eds. Proceedings of TAMC, 566–572Google Scholar
  105. 105.
    Zhang P. An approximation algorithm to the k-steiner forest problem. In: Cai J Y, Cooper S B, Zhu H, eds. Proceedings of TAMC, 2007, 728–737Google Scholar
  106. 106.
    Yan J, Zhang J. Backtracking algorithms and search heuristics to generate test suites for combinatorial testing. In: Proceedings of COMPSAC. Chicago: IEEE Computer Society, 2006, 385–394Google Scholar
  107. 107.
    Xu Z X, Zhang J. A test data generation tool for unit testing of C programs. In: Proceedings of QSIC, 2006, 107–116Google Scholar
  108. 108.
    Shen Y D, Zhang Z, Yang Q. Objective-oriented utility-based association mining. In: Proceedings of ICDM, 2002, 426–433Google Scholar

Copyright information

© Higher Education Press 2008

Authors and Affiliations

  • Jian Zhang
    • 1
    Email author
  • Wenhui Zhang
    • 1
  • Naijun Zhan
    • 1
  • Yidong Shen
    • 1
  • Haiming Chen
    • 1
  • Yunquan Zhang
    • 1
  • Yongji Wang
    • 1
  • Enhua Wu
    • 1
  • Hongan Wang
    • 1
  • Xueyang Zhu
    • 1
  1. 1.State Key Laboratory of Computer Science, Institute of SoftwareChinese Academy of SciencesBeijingChina

Personalised recommendations