Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Thu 14 Nov 2019 14:40 - 15:00 at Hillcrest - Models and Logs Chair(s): Timo Kehrer

Many works infer finite-state models from execution logs. Large models are more accurate but also more difficult to present and understand. Small models are easier to present and understand but are less accurate. In this work we investigate the tradeoff between model size and accuracy in the context of the classic k-Tails model inference algorithm. First, we define mk-Tails, a generalization of k-Tails from one to many parameters, which enables fine-grained control over the tradeoff. Second, we extend mk-Tails with a reduction based on past-equivalence, which effectively reduces the size of the model without decreasing its accuracy. We implemented our work and evaluated its performance and effectiveness on models and generated logs from the literature.

Thu 14 Nov

13:40 - 15:20: Papers - Models and Logs at Hillcrest
Chair(s): Timo KehrerHumboldt-Universtität zu Berlin
ase-2019-papers13:40 - 14:00
Statistical Log Differencing
Lingfeng BaoInstitute of Information Engineering, Chinese Academy of Sciences, Nimrod BusanyTel Aviv University, David LoSingapore Management University, Shahar MaozTel Aviv University
ase-2019-papers14:00 - 14:20
Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression
Jinyang LiuSun Yat-Sen University, Jieming ZhuHuawei Noah's Ark Lab, Shilin HeChinese University of Hong Kong, Pinjia HeETH Zurich, Zibin ZhengSun Yat-Sen University, Michael LyuThe Chinese University of Hong Kong
ase-2019-papers14:20 - 14:40
Code-First Model-Driven Engineering: On the Agile Adoption of MDE Tooling
Artur BoronatUniversity of Leicester
ase-2019-papers14:40 - 15:00
Size and Accuracy in Model Inference
Nimrod BusanyTel Aviv University, Shahar MaozTel Aviv University, Yehonatan YulazariTel Aviv University
ase-2019-Demonstrations15:00 - 15:10
PMExec: An Execution Engine of Partial UML-RT Models
Mojtaba BagherzadehQueen's University, Karim JahedQueen's University, Nafiseh KahaniQueen's University, Juergen DingelQueen's University, Kingston, Ontario
ase-2019-Demonstrations15:10 - 15:20
mCUTE: A Model-level Concolic Unit Testing Engine for UML State Machines
Reza AhmadiQueen's University, Karim JahedQueen's University, Juergen DingelQueen's University, Kingston, Ontario