Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Thu 14 Nov 2019 13:40 - 14:00 at Hillcrest - Models and Logs Chair(s): Timo Kehrer

Recent works have considered the problem of log differencing: given two or more system’s execution logs, output a model of their differences. Log differencing has potential applications in software evolution, testing, and security. In this paper we present statistical log differencing, which accounts for frequencies of behaviors found in the logs. We present two algorithms, s2KDiff for differencing two logs, and snKDiff, for differencing of many logs at once, both presenting their results over a single inferred model. A unique aspect of our algorithms is their use of statistical hypothesis testing: we let the engineer control the sensitivity of the analysis by setting the target distance between probabilities and the statistical significance value, and report only (and all) the statistically significant differences. Our evaluation shows the effectiveness of our work in terms of soundness, completeness, and performance. It also demonstrates its effectiveness via a user-study and its potential applications via a case study using real-world logs.

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