4th Symposium on
Search Based Software Engineering
September 28th - 30th, 2012
Riva del Garda | Trento | Italy
Home » Keynote Speakers
Thu, 29 October 2020 21:01:37


Recent Advances in Evolutionary Multi-Objective Optimization

Speaker: Kalyanmoy Deb

Abstract: About 20 years ago, three separate groups worked out three different evolutionary algorithms for solving bi-objective optimization problem with a great success. Academicians and practitioners alike realized, for the first time, evolutionary algorithms had a clear niche in solving such problems. The initial studies resulted in a surge of new developments including new and more computationally efficient algorithms and new applications involving two and more objectives. The birth of evolutionary multi-objective optimization (EMO) field provided a platform for new-comers to work on their theses and new entrepreneurs to develop commercial softwares. In the last 10 years, significant new developments and applications have been made. Some of them include their hybridization with multiple criterion decision-making methods, multi-objectivization to solve other optimization problems, many-objective problem-solving and their application to new areas. In this talk, we shall provide a brief introduction to EMO and then present some recent advancements of EMO that are making the field alive and exciting.

Kalyanmoy Deb is a Professor of Mechanical Engineering at Indian Institute of Technology Kanpur and is also an Adjunct Professor at the Business Technology Department in the Aalto University in Finland and a visiting professor at the University of Skovde, Sweden. Prof. Deb received his Bachelor's degree in Mechanical Engineering from Indian Institute of Technology Kharagpur in India in 1985. He received his master's and PhD degrees in Engineering Mechanics from University of Alabama, Tuscaloosa, USA in 1989 and 1991, respectively.
His main research interests are in evolutionary optimization algorithms and their application in optimization and machine learning. He is largely known for his seminal research in developing and applying Evolutionary Multi-Criterion Optimization. He was awarded the prestigious "Edgeworth-Pareto" award in 2008, Shanti Swarup Bhatnagar Prize in Engineering Sciences in 2005, "Thomson Citation Laureate Award" from Thompson Reuters for having the highest number of citations in Computer Science in India. His 2002 IEEE-TEC NSGA-II paper is now judged as the Most Highly Cited paper and a Current Classic by Thomson Reuters having more than 3,000 citations. He is a fellow of Indian National Science Academy (INSA), Indian National Academy of Engineering (INAE), Indian Academy of Sciences (IASc), and International Society of Genetic and Evolutionary Computation (ISGEC). He has received Friedrich Wilhelm Bessel Research award from Humboldt Foundation in 2003. He has written two text books on optimization and more than 305 international journal and conference research papers. He is in the editorial board on 18 major international journals. More information about his research can be found from www.iitk.ac.in/kangal/deb.htm.

SBSE meets Software Maintenance: Achievements and Open Problems

Speaker: Massimiliano Di Penta

Abstract: Software maintenance is, together with testing, one of the most critical and effort-prone activities in software development. Surveys conducted in the past have estimated that up to 80% of the overall software development cost is due to maintenance activities. For such a reason, automated techniques aimed at supporting developers in their daunting tasks are highly appealing. Problems developers often face off include understanding undocumented software, improving the software design and source code structure to ease future maintenance tasks, and producing patches to fix bugs.
Finding a solution for the aforementioned problems is intrinsically NP-Hard, and therefore such problems are not tractable with conventional algorithmic techniques; this is particularly true in presence of very complex and large software systems. For this reason, search-based optimization techniques have been-and currently are-successfully applied to deal with all the aforementioned problems. Noticeable examples of successful applications of SBSE to software maintenance include software modularization, software refactoring, or automated bug fixing.
Despite the noticeable achievements, there are still crucial challenges researchers have to face-off. First, software development is still an extremely human-centric activity, in which many decisions concerning design or implementation are really triggered by personal experience, that is unlikely to be encoded in heuristics of automated tools. Automatically-generated solutions to maintenance problems tend very often to be meaningless and difficult to be applied in practice. For this reason, researchers should focus their effort in developing optimization algorithms where human evaluations (partially) drive the production of problem solutions. This however, requires to deal with difficulties occurring when involving humans in the optimization process: human decisions may be inconsistent and, in general, the process tend to be fairly expensive in terms of required effort.
A further challenge where SBSE meets software maintenance concerns systems which necessitate rapid reconfigurations at run-time, e.g., highly dynamic service-oriented architectures, or autonomic systems. If, on the one hand, such reconfigurations imply complex decisions where the space of possible choices is high, on the other hand such decisions have to be taken in a very short time. This implies a careful choice and performance assessment of the search-based optimization techniques adopted, aspect that is often not particularly considered when search-based optimization techniques are applied offline, e.g. for test data generation or for software modularization.
Last, but not least, many modern software systems-open source and not only-are part of large and complex software ecosystems where the evolution of a component might impact others, e.g. by creating incompatibilities from a technical or even legal point of view. Also in this case, SBSE has a great potential to support the explore such large spaces of software configurations.

Massimiliano Di Penta is associate professor at the University of Sannio, Italy. His research interests include software maintenance and evolution, reverse engineering, empirical software engineering, search-based software engineering, and service-centric software engineering. He is author of over 150 papers appeared in international conferences and journals. He serves and has served in the organizing and program committees of over 60 conferences such as ICSE, FSE, ASE, ICSM, ICPC, CSMR, GECCO, MSR, SCAM, WCRE, and others. He is program co-chair of ICSM 2012 and has been general chair of SCAM 2010, WSE 2008, general co-chair of SSBSE 2010, WCRE 2008, and program co-chair of SSBSE 2009, WCRE 2006 and 2007, IWPSE 2007, WSE 2007, SCAM 2006, STEP 2005, and of other workshops. He is steering committee member of ICSM, CSMR, WCRE, IWPSE, and past steering committee member of ICPC and SCAM. He is in the editorial board of the Empirical Software Engineering Journal edited by Springer, and of the Journal of Software: Evolution and Processes edited by Wiley. He is member-at-large of the executive committee of the Technical Council of Software Engineering (TCSE). He is member of IEEE, IEEE Computer Society, and of the ACM. Further info on www.rcost.unisannio.it/mdipenta

Last modified Monday, 10th February, 2020