Title | Business Process Extraction Using Static Analysis |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Islam, Md Rofiqul, Cerny, Tomas |
Conference Name | 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) |
Date Published | nov |
Keywords | Business, Business Process Mining, cloud computing, codes, composability, Costs, data mining, Data Science, Distributed Systems, Human Behavior, log analysis, pubcrawl, Resiliency, Runtime, static analysis, static code analysis |
Abstract | Business process mining of a large-scale project has many benefits such as finding vulnerabilities, improving processes, collecting data for data science, generating more clear and simple representation, etc. The general way of process mining is to turn event data such as application logs into insights and actions. Observing logs broad enough to depict the whole business logic scenario of a large project can become very costly due to difficult environment setup, unavailability of users, presence of not reachable or hardly reachable log statements, etc. Using static source code analysis to extract logs and arranging them perfect runtime execution order is a potential way to solve the problem and reduce the business process mining operation cost. |
DOI | 10.1109/ASE51524.2021.9678588 |
Citation Key | islam_business_2021 |