Projects

Over the last two decades, microservices have emerged as a new architectural style for the development of software applications consisting of a number of loosely coupled and reusable software components. Microservices are used, for example, in online shop applications, where each microservice provides a specific functionality. For example, one microservice provides the functionality for a shopping cart, while another microservice provides the functionality for payment. This is in contrast to monolithic software applications where all services would be implemented in a single component. The biggest advantages of microservices are that they can be developed, tested, deployed and reused independently. Although microservices are highly independent, there is a degree of coupling between them. This also means that changes to one microservice can cause unexpected side effects in other microservices. Consequently, the affected microservices may no longer function as expected, which can be very unsatisfactory for the users of the microservice. Therefore, software developers take various quality assurance measures to identify potential side effects of their changes and avoid errors. However, existing quality assurance methods and tools are imprecise and therefore potential side effects must be analyzed manually. This is not only time-consuming, but also error prone.The aim of this research project is to explore novel methods and techniques that enable software developers to accurately determine and understand the side effects of changes in a microservice. Determining possible side effects is challenging and usually not easy to calculate even for small programs, as the number of possible effects can quickly reach infinity. To overcome this challenge, we will explore different approaches to abstracting programs and interpreting the effects of individual changes. We will then experiment with different visualization techniques to help software developers understand the impact more quickly and accurately. In addition, we will investigate techniques to selectively choose test cases that use information about a change and its impact to reduce testing effort. We will implement our methods and techniques in several prototypes to evaluate them in experiments and user studies with open-source systems as well as systems and developers from our industry partners. All prototypes created in this project will be made publicly available as open source.

• University of British Columbia, Department of Electrical and Computer Engineering
• University of Bamberg, Information Systems and Applied Computer Sciences

Further Information

Over the last two decades, microservices have emerged as a new architectural style for the development of software applications consisting of a number of loosely coupled and reusable software components. Microservices are used, for example, in online shop applications, where each microservice provides a specific functionality. For example, one microservice provides the functionality for a shopping cart, while another microservice provides the functionality for payment. This is in contrast to monolithic software applications where all services would be implemented in a single component. The biggest advantages of microservices are that they can be developed, tested, deployed and reused independently. Although microservices are highly independent, there is a degree of coupling between them. This also means that changes to one microservice can cause unexpected side effects in other microservices. Consequently, the affected microservices may no longer function as expected, which can be very unsatisfactory for the users of the microservice. Therefore, software developers take various quality assurance measures to identify potential side effects of their changes and avoid errors. However, existing quality assurance methods and tools are imprecise and therefore potential side effects must be analyzed manually. This is not only time-consuming, but also error prone.The aim of this research project is to explore novel methods and techniques that enable software developers to accurately determine and understand the side effects of changes in a microservice. Determining possible side effects is challenging and usually not easy to calculate even for small programs, as the number of possible effects can quickly reach infinity. To overcome this challenge, we will explore different approaches to abstracting programs and interpreting the effects of individual changes. We will then experiment with different visualization techniques to help software developers understand the impact more quickly and accurately. In addition, we will investigate techniques to selectively choose test cases that use information about a change and its impact to reduce testing effort. We will implement our methods and techniques in several prototypes to evaluate them in experiments and user studies with open-source systems as well as systems and developers from our industry partners. All prototypes created in this project will be made publicly available as open source.

• University of British Columbia, Department of Electrical and Computer Engineering
• University of Bamberg, Information Systems and Applied Computer Sciences

Further Information

In this project, we will investigate methods for improving debugging and locating faults in programs using incremental, interactive formal program analysis. Our envisioned approach uses symbolic/concolic execution to obtain a first semantic of a function in a program. This will be shown to the developer(s) that can refine and/or extend the semantic. Next, the symbolic/concolic execution will be rerun with the refined semantic. This will be repeated, until the developer locates the fault and is able to understand it. The two main research challenges are: 1) find methods for refining and extending semantics as obtained with symbolic/concolic execution; 2) find methods to represent the semantics to developers so that he/she can understand and work with it.

Further Information

In this project, we will investigate methods for improving debugging and locating faults in programs using incremental, interactive formal program analysis. Our envisioned approach uses symbolic/concolic execution to obtain a first semantic of a function in a program. This will be shown to the developer(s) that can refine and/or extend the semantic. Next, the symbolic/concolic execution will be rerun with the refined semantic. This will be repeated, until the developer locates the fault and is able to understand it. The two main research challenges are: 1) find methods for refining and extending semantics as obtained with symbolic/concolic execution; 2) find methods to represent the semantics to developers so that he/she can understand and work with it.

Further Information

SEEROSE features four Ph.D. projects: The goal of the Ph.D. project DevSafe is to provide techniques and tools to support developers to responsibly develop and evolve safe and secure robotic systems. The goal of the Ph.D. project INBASE-GET is to provide mechanisms for incentivizing developers and robot collaborators to use and follow security precautions out of their own interests. The goal of the Ph.D. project SCoRE is to provide an instrument for the psychological assessment of the core qualifications relevant to robotics engineers. And finally, the goal of the Ph.D. project CERSE is to provide a guideline for the implementation of a process-ethical procedure for distributed assumption of responsibility in safe and secure robotic systems engineering.

Further Information

SEEROSE features four Ph.D. projects: The goal of the Ph.D. project DevSafe is to provide techniques and tools to support developers to responsibly develop and evolve safe and secure robotic systems. The goal of the Ph.D. project INBASE-GET is to provide mechanisms for incentivizing developers and robot collaborators to use and follow security precautions out of their own interests. The goal of the Ph.D. project SCoRE is to provide an instrument for the psychological assessment of the core qualifications relevant to robotics engineers. And finally, the goal of the Ph.D. project CERSE is to provide a guideline for the implementation of a process-ethical procedure for distributed assumption of responsibility in safe and secure robotic systems engineering.

Further Information