Looking for PhDs and Postdocs in Software Analytics and Data Science for 3TU.BSR "Big Software on the Run" research program
by Marieke Huisman, Feb. 9, 2015In the context of the 3TU.BSR "Big Software on the Run" research program we are looking for 6 PhDs and 3 Postdocs interested in Software Analytics and Data Science.
Context
Millions of lines of code - written in different languages by different people at different times, and operating on a variety of platforms - drive the systems performing key processes in our society. The resulting software needs to evolve and can no longer be controlled a priori as is illustrated by a range of software problems. The 3TU.BSR research program will develop novel techniques and tools to analyze software systems in vivo - making it possible to visualize behavior, create models, check conformance, predict problems, and recommend corrective actions. To deal with Big Software on the Run (BSR), we propose to shift the main focus from a priori software design to a posteriori software analytics thereby exploiting the large amounts of event data generated by today's systems. The core idea is to study software systems in vivo, i.e., at runtime and in their natural habitat. We would like to understand the actual (desired or undesired) behavior of software. Running software needs to adapt to evolving and diverging environments and requirements. This forces us to consider software artifacts as "living organisms operating in a changing ecosystem". This paradigm shift requires new forms of empirical investigation that go far beyond the common practice of collecting error messages and providing software updates.
Project
The project will run for a period of four years and is supported by the three Dutch technical universities (Eindhoven University of Technology, TU Delft, and University of Twente). It was initiated by 3TU.NIRICT, the Netherlands Institute for Research on ICT, which comprises all ICT research of the three universities of technology in the Netherlands. The PhD positions will run for 4 years. The three postdocs will be appointed for 2-3 years.
The following chairs/groups are involved:
· The Architecture of Information Systems (AIS) group at Eindhoven University of Technology (Van der Aalst).
· The Visualization (VIS) group at Eindhoven University of Technology (Van Wijk).
· The Software Engineering Research Group (SERG) at Delft University of Technology (Van Deursen)
· The Cybersecurity Group (CY) at Delft University of Technology (Lagendijk)
· The Formal Methods and Tools (FMT) at University of Twente (Van de Pol & Huisman)
Interested PhD candidates are requested to apply on a specific PhD position (see details below):
1. Automatically Discovering Behavioral Software Models from Software Event Data (Van der Aalst & Van Deursen) at Eindhoven University of Technology
2. Model-based Visualization of Software Event Data (Van Wijk & Huisman) at Eindhoven University of Technology
3. Exceptional Patterns (Van Deursen & Van Wijk) at TU Delft
4. Monitoring Concurrent Software (Huisman & Lagendijk) at University of Twente
5. Privacy Preserving On-line Conformance Checking (Lagendijk & Van de Pol) at TU Delft
6. Parallel Checking and Prediction (Van de Pol & Van der Aalst) at University of Twente
Moreover, there will be three postdoc positions:
1. A postdoc related to PhD projects 1 & 2 at Eindhoven University of Technology
2. A postdoc related to PhD projects 3 & 5 at TU Delft
3. A postdoc related to PhD projects 4 & 6 at University of Twente
Requirements
We are looking for candidates that meet the following requirements:
· a solid background in Computer Science, Data Science, or Software Science (demonstrated by a relevant Master);
· for the postdoc positions a relevant PhD is expected;
· candidates from non-Dutch or non-English speaking countries should be prepared to prove their English language skills;
· good communicative skills in English, both in speaking and in writing;
· candidates are expected to realize research ideas in terms of prototype software, so software development skills are needed.
Note that we are looking for candidates that really want to make a difference and like to work on things that have a high practical relevance while having the ambition to compete at an international scientific level (i.e., present at top conferences and in top journals).
Appointment and salary
PhDs and postdocs will be employed by the respective university using the standard VSNU conditions for Dutch universities. See for more information:
· http://w3.tue.nl/en/services/dpo/conditions_of_employment/tue_conditions_of_employment
· http://www.utwente.nl/hr/en/terms-of-employment/
· http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/tu-delft-as-employer/
How to apply?
Please apply for the position you are interested in. Each position has a contact person and a pointer to a website and e-mail address to actually apply.
PhD 1: Automatically Discovering Behavioral Software Models from Software Event Data (Van der Aalst & Van Deursen)
Process models and user interface workflows underlie the functional specification of almost every substantial software system. However, these are often left implicit or are not kept consistent with the actual software development. When the system is utilized, user interaction with the system can be recorded in event logs. After applying process mining methods to logs, we can derive process and user interface workflow models. These models provide insights regarding the real usage of the software and can enable usability improvements and software redesign. In this project, we aim to develop process discovery techniques specific for software. How can domain knowledge and software structure be exploited while mining? How to discover software patterns and anti-patterns?
· More information about this position contact Wil van der Aalst (http://wwwis.win.tue.nl/~wvdaalst/).
· For more information about the employment conditions contact Charl Kuiters HR advisor, e-mail: [email protected].
· You can apply by using the following link: http://jobs.tue.nl/en/vacancy/phd-discovering-behavioral-software-models-from-software-event-data-206118.html or visit http://jobs.tue.nl/en/vacancies.html and choose Department of Mathematics and Computer Science and click ‘search’ to find this vacancy (V32.2142).
PhD 2: Model-based Visualization of Software Event Data (Van Wijk & Huisman)
Visualization can be a powerful means for understanding large and complex data sets, such as the huge event streams produced by running software systems. During explorative analysis experts have to be enabled to see what patterns occur, during monitoring anomalous events and patterns have to be detected, where in both cases we can exploit the unique capabilities of the human visual system. However, simply showing events as a sequence of items will fall short because of lack of scalability. The challenge is to enable users to specify what they are interested in, and to show only a limited subset of the data, using filtering, aggregation, and abstraction. We propose to enable users to define models for this, ranging from simple range filters to process models. We will study which (combinations of) models are most appropriate here, such that occurrences of events, temporal and logical patterns, and the relations between occurrences and attributes of events can be detected, and to facilitate analysts to define and check hypotheses on patterns.
· More information about this position contact Jack van Wijk (http://www.win.tue.nl/~vanwijk/).
· For more information about the employment conditions contact Charl Kuiters HR advisor, e-mail: [email protected].
· You can apply by using the following link: http://jobs.tue.nl/en/vacancy/phd-modelbased-visualization-of-software-event-data-206124.html or visit http://jobs.tue.nl/en/vacancies.html and choose Department of Mathematics and Computer Science and click ‘search’ to find this vacancy (V32.2143).
PhD 3: Exceptional Patterns (Van Deursen & Van Wijk)
A particularly challenging phenomenon in software development are 'exceptions'. Most programming is focused on 'good weather behavior', in which the system works under normal circumstances. Actual deployment however, often takes place in a changing or unexpected environment. This may lead to exceptions being raised by the application, which should be handled by the application. Unfortunately, predicting such exceptional circumstances is often impossible. Consequently, developers have difficulty adequately handling such exceptions. Some exceptions are simply swallowed by the applications, others are properly logged, and yet other may lead to unpredictable behavior. To resolve this, we propose to analyze log files for 'exceptional patterns' -- patterns that hint at the presence of exceptions. To find such patterns, we propose to use visualization techniques applied to log data and stack traces. Furthermore, we will investigate ways to predict future occurrences of exceptions, and recommendations on how to improve exception handling in the code base.
· More information about this position contact Arie van Deursen (http://www.st.ewi.tudelft.nl/~arie/).
· More information on how to apply will follow via http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/jobs/academic-jobs/.
PhD 4: Monitoring Concurrent Software (Huisman & Lagendijk)
The goal is to develop a monitoring system for concurrent software. Making monitoring transparent is the big challenge: monitoring should not affect program behavior. A general-purpose approach will be designed, based on local annotations and global properties. Runtime monitoring is essential to check conformance of concurrent software during deployment. At the same time, runtime monitoring provides insight in low-level software events, generating a continuous data stream of events that feeds discovery. With process mining and visualization technology in Eindhoven, we will explore the scope of concurrent software monitoring.
· More information about this position: see http://fmt.cs.utwente.nl/vacancies/ or contact Marieke Huisman (http://fmt.cs.utwente.nl/~marieke/ ).
· More information on the terms of employment: http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, HR advisor, e-mail: [email protected].
· You can apply directly using the following link: http://tinyurl.com/3TU-BSR-PhD4.
PhD 5: Privacy Preserving On-line Conformance Checking (Lagendijk & Van de Pol)
Privacy enhancing techniques have been applied dominantly to data analysis problems (such as pattern recognition) and multimedia algorithms (such as recommendation engines). The goal of privacy preserving on-line conformance checking is to research the problem of privacy and security protection in software engineering for the first time. The central problem is that conformance checking algorithms may need to operate on event data that is sensitive in some way, for instance, contains user-related information. Such data can be anonymized or encrypted for protection, yet this might affect the accuracy of the conformance checking procedure. It will therefore be necessary to find an acceptable trade-off between the level of protection, the utility of the results obtained from the privacy-enhanced version of the conformance checking algorithm, and the additional computational overhead introduced by the anonymization or encryption process.
· More information about this position contact Inald Lagendijk (http://mmc.tudelft.nl/users/inald-lagendijk).
· More information on how to apply will follow via http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/jobs/academic-jobs/.
PhD 6: Parallel Checking and Prediction (Van de Pol & Van der Aalst)
Based on the models discovered by online observations (Track 1), the goal of this research project is to develop scalable technology for predicting future system behavior (Track 3). Assuming that the system’s components will behave similar to the process models learnt so far, (quantitative) model checking techniques will be applied to explore possible runs and interactions of the integrated system. In order to support online recommendations (Track 4), the model checking results should be available nearly instantaneously. This calls for parallel, scalable algorithms that will be run on local and national cloud infrastructure.
· More information about this position: see http://fmt.cs.utwente.nl/vacancies/ or contact Jaco van de Pol (http://fmt.cs.utwente.nl/~vdpol/).
· More information on the terms of employment: http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, HR advisor, e-mail: [email protected].
· You can apply directly using the following link: http://tinyurl.com/3TU-BSR-PhD6.
Postdoc 1: Software Analytics and Process Mining (Van der Aalst)
The postdoc will be involved in the supervision of the PhDs based at Eindhoven University of Technology (PhD positions 1 & 2). Moreover, the postdoc will also run the Eindhoven side of the 3TU.BSR "Big Software on the Run" research program. This also includes making sure that software and application efforts are integrated and coordinated between the different subprojects.
· More information about this position contact Wil van der Aalst (http://wwwis.win.tue.nl/~wvdaalst/).
· For more information about the employment conditions contact Charl Kuiters HR advisor, e-mail: [email protected].
· You can apply by using the following link: http://jobs.tue.nl/nl/vacature/postdoc-software-analytics-and-process-mining-206130.html or visit http://jobs.tue.nl/en/vacancies.html, choose Department of Mathematics and Computer Science and click ‘search’ to find this vacancy (V32.2144).
Postdoc 2 (TUD): Information will follow later.
Postdoc 3: Monitoring, Testing and Conformance Checking (Van de Pol)
This postdoc will investigate the frontier between model-based testing, runtime monitoring and conformance checking. The goal is to evaluate and improve test-generation techniques based on massive data gathered from online monitoring and the software development process, in collaboration with TU Delft (van Deursen) and TU Eindhoven (van der Aalst).
The postdoc will be involved in the supervision of the PhDs based at the University of Twente (PhD positions 4 & 6). Moreover, the postdoc will also run the Twente side of the 3TU.BSR "Big Software on the Run" research program. This includes ensuring that software and application efforts are integrated and coordinated between the different subprojects.
· More information about this position: see http://fmt.cs.utwente.nl/vacancies/ or contact Jaco van de Pol (http://fmt.cs.utwente.nl/~vdpol/).
· More information on the terms of employment: http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, HR advisor, e-mail: [email protected].
· You can apply directly using the following link: http://tinyurl.com/3TU-BSR-PD3.
