Regression Verification in a User-Centered Software Development Process for Evolving Automated Production Systems
The vision for this project is to advance technology such that
regression verification methods are available that will be
routinely used for ensuring correctness in the evolution
processes for long-living reliable systems requiring frequent
re-validation. The goal of regression verification is to
formally prove that software remains correct through its
evolution, changes have the desired effect, and no new bugs
Regression verification avoids the main bottleneck for the routine practical use of formal verification, namely the need to write full functional specifications (which is a huge effort). Also, given two program versions or variants that are both complex but similar to each other, the effort for verifying the relation between them mainly depends on the difference between the programs and not on their overall size and complexity.
As a follow-up to the IMPROVE project, we plan to overcome the two remaining obstacles on the path to reaching the above vision of routine use:
- Reach and power: The reach and power of regression verification needs to be extended to cover real-world systems and change scenarios.
- User in the loop: Regression verification needs to be integrated into the software development and evolution process, and useful feedback needs to be given to the user in case a verification attempt is not immediately successful.
In this phase, we will target a particular application domain. This provides the third main motif for our project in Phase 2 – now called IMPROVE APS:
Automated production systems in the pharmaceutical and the food-manufacturing industry: The control software and discrete processes of automated production systems (aPS) are a very promising application area for regression verification. These systems are long-living and have to fulfill dependability and reliability criteria to avoid machine hazards or accidents involving operator or maintenance personnel. Applicability in realistic industrial situations is within reach as we focus on evolution with limited changes (e.g., bug fixes) and small variations in the software. As case studies, we use manufacturing systems in the pharmaceutical and the food industry, where aPS must be validated following regulations to ensure no harm is inflicted on consumers of the products.The envisaged solutions of IMPROVE APS follow the goal of a comprehensive elaboration of approaches to manage software evolution with additional constraints from application taken into account.
This project is part of the DFG SPP1593 "Design for Future"
HistoryThis project is the successor of the IMPROVE project, which focused on regression verification of imperative and object-oriented programs.
We have investigated the foundations of regression verification, developed the basic methods, and shown their applicability to realistic examples and case studies.
PeopleIn line with the new focus on integration into the software development process and the application domain of automated production systems, IMPROVE APS has a new set of principal investigators and is now a collaboration of the Institute of Automation and Information Systems (led by Birgit Vogel-Heuser) at Technische Universität München (TUM) and the Application-oriented Formal Verification group (led by Bernhard Beckert) at Karlsruhe Institute of Technology (KIT).
|Bernhard Beckert||Project Investigator||KIT|
|Birgit Vogel-Heuser||Project Investigator||TUM|
|Mattias Ulbrich||Project Investigator||KIT|
|Suhyun Cha||Funded Member||TUM|
|Alexander Weigl||Funded Member||KIT|
|Sebastian Ulewicz||Former Member||TUM|
|Michael Kirsten||Former Member||KIT|
|Franziska Wiebe||Former Member||TUM|
|Applicability of Generalized Test Tables: A Case Study Using the Manufacturing System Demonstrator xPPU||Suhyun Cha, Alexander Weigl, Mattias Ulbrich, Bernhard Beckert, and Birgit Vogel‑Heuser||Automatisierungstechnik Special Issue|
|Achieving delta description for the system software of an automated production evolution based on partially inferenced model||Suhyun Cha, Alexander Weigl, Mattias Ulbrich, Bernhard Beckert, and Birgit Vogel‑Heuser||14th IEEE International Conference on Automation Science and Engineering (CASE 2018)|
|Generalised Test Tables: A Practical Specification Language for Reactive Systems||Bernhard Beckert, Suhyun Cha, Mattias Ulbrich, Birgit Vogel‑Heuser, and Alexander Weigl||13th International Conference on integrated Formal Methods (iFM 2017)|
|Generation of Monitoring Functions in Production Automation Using Test Specifications||Suhyun Cha, Sebastian Ulewicz, Birgit Vogel‑Heuser, Alexander Weigl, Mattias Ulbrich, and Bernhard Beckert||15th IEEE International Conference on Industrial Informatics (INDIN 2017)|
|Generalized Test Tables: A Powerful and Intuitive Specification Language for Reactive Systems||Alexander Weigl, Franziska Wiebe, Mattias Ulbrich, Sebastian Ulewicz, Suhyun Cha, Michael Kirsten, Bernhard Beckert, and Birgit Vogel‑Heuser||15th IEEE International Conference on Industrial Informatics (INDIN 2017)|
|A Verification-Supported Evolution Approach to Assist Software Application Engineers in Industrial Factory Automation||Sebastian Ulewicz, Mattias Ulbrich, Alexander Weigl, Michael Kirsten, Franziska Wiebe, Bernhard Beckert, and Birgit Vogel‑Heuser||IEEE International Symposium on Assembly and Manufacturing (ISAM 2016)|
|Relational Program Reasoning Using Compiler IR – Combining Static Verification and Dynamic Analysis||Moritz Kiefer, Vladimir Klebanov, and Mattias Ulbrich||Journal of Automated Reasoning 60(3)|
|Automating Regression Verification||Dennis Felsing, Sarah Grebing, Vladimir Klebanov, Philipp Rümmer, and Mattias Ulbrich||29th IEEE/ACM International Conference on Automated Software Engineering (ASE 2014)|