On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.     

Design of nonlinear controllers for active vehicle suspension with state constraints

Design of active vehicle suspension has tradeoffs between three main performance metrics (passenger comfort, suspension deflection and road holding ability). It has been known that each performance can be achieved by H _∞ controller and they can be gathered by LPV (Linear Parameter Varying) method. However, because the suspension deflection limit was not explicitly considered, this limit may be exceeded. In this paper, the authors propose a “reference shaping“ based method in order to improve the control performance. In this approach, a “virtual reference” signal is imposed to the system such that the suspension deflection is kept small. The effectiveness of the approach is examined by numerical simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Modelling asymmetry in the peripheral auditory system of the lizard

The ears of lizards are highly directional. The directionality is generated by strong acoustical coupling of the eardrums. A simple lumped-parameter model of the ear followed by binaural comparisons has been shown to perform successful phonotaxis in robot implementations. However, such a model will produce localization errors in the form of response bias if the ears are asymmetrical. We have evaluated how large errors are generated by asymmetry using simulations of the ear model in Mathematica 5.2. The study shows that the effect of asymmetry is minimal around the most directional frequency of the ear, but that biases reduce the useful bandwidth of localization. This work was presented in part at the First European Workshop on Artificial Life and Robotics, Vienna, Austria, July 12–13, 2007     

2D artificial life system using network-type assembly-like language: influence of change in environment with costs of instructions

To unlock the full potential of evolution in digital media, a Tierra-like system using network-type assembly-like language has been constructed. In the system, like Avida, digital creatures, self-replicating programs, live in a discrete 2D torus space and an interaction between creatures is restricted locally. Bearing a genetic network in mind, network structure is introduced. In the previous works, it is shown that the possibility that the network-type model has more potential of evolution than a linear-type model like Avida in a simple environment. In this paper, to study the potential of evolution more precisely, we model the effects of environment other than creatures. As one of the simplest models of such environment, the cost of execution, i.e. executing time, is introduced. The difficult environment to live in costs high to execute instructions, the easy environment does low. In computer experiments, we have investigated the influence of change in environment by analyzing the process of evolution and diversity of the system. Experimental results show that the network-type system keeps more stable diversity than the linear-type system does, even when the environment changes drastically. This indicates the possibility that the network-type system has more potential of evolution than the linear-type system has. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008