Associated research group: Critical Systems Research GroupSolutions to non-linear requirements engineering problems may be "brittle"; i.e. small changes may dramatically alter solution effectiveness. Hence, it is not enough to just generate solutions to requirements problems- we must also assess solution robustness. The KEYS2 algorithm can generate decision ordering diagrams. Once generated, these diagrams can assess solution robustness in linear time. In experiments with real-world requirements engineering models, we show that KEYS2 can generate decision ordering diagrams in O(N 2). When assessed in terms of terms of (a) reducing inference times, (b) increasing solution quality, and (c) decreasing the variance of the generated solution, KE...
Model-based diagnosis can be framed as optimization for constraints with preferences (soft constrain...
This paper is devoted to the the search of robust solutions in state space graphs when costs depend ...
AbstractThe data of real-world optimization problems are usually uncertain, that is especially true ...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
Solutions to non-linear requirements engineering problems may be brittle ; i.e. small changes may d...
Recent work with NASA's Jet Propulsion Laboratory has allowed for external access to five of JPL's r...
Associated research group: Critical Systems Research GroupBackground: Search-based Software Engineer...
Optimization of simulated systems is tackled by many methods, but most methods assume known environm...
Abstract. In this position paper, we argue that search based software engineering techniques can be ...
Optimization of simulated systems is tackled by many methods, but most methods assume known environm...
Abstract. In this position paper, we argue that search based software engineering techniques can be ...
Multiple viewpoints are often used in requirements engineering to facilitate traceability to stake-h...
Search-Based Software Engineering (SBSE) is about solving software development problems by formulati...
AbstractRequirement engineering is the cornerstone of systems engineering. Numerous large scale engi...
Model-based diagnosis can be framed as optimization for constraints with preferences (soft constrain...
This paper is devoted to the the search of robust solutions in state space graphs when costs depend ...
AbstractThe data of real-world optimization problems are usually uncertain, that is especially true ...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
Solutions to non-linear requirements engineering problems may be brittle ; i.e. small changes may d...
Recent work with NASA's Jet Propulsion Laboratory has allowed for external access to five of JPL's r...
Associated research group: Critical Systems Research GroupBackground: Search-based Software Engineer...
Optimization of simulated systems is tackled by many methods, but most methods assume known environm...
Abstract. In this position paper, we argue that search based software engineering techniques can be ...
Optimization of simulated systems is tackled by many methods, but most methods assume known environm...
Abstract. In this position paper, we argue that search based software engineering techniques can be ...
Multiple viewpoints are often used in requirements engineering to facilitate traceability to stake-h...
Search-Based Software Engineering (SBSE) is about solving software development problems by formulati...
AbstractRequirement engineering is the cornerstone of systems engineering. Numerous large scale engi...
Model-based diagnosis can be framed as optimization for constraints with preferences (soft constrain...
This paper is devoted to the the search of robust solutions in state space graphs when costs depend ...
AbstractThe data of real-world optimization problems are usually uncertain, that is especially true ...