Generalizing Perspective-based Inspection to handle Object-Oriented Development Artifacts

The value of software inspection for uncovering defects early in the development lifecycle has been well documented. Of the various types of inspection methods published to date, experiments have shown perspective-based inspection to be one of the most effective, because of its enhanced coverage of the defect space. However, inspections in general, and perspective-based inspections in particular, have so far been applied predominantly in the context of conventional structured development methods, and then almost always to textual artifacts, such as requirements documents or code modules. Object oriented-models, particularly of the graphical form, have so far not been adequately addressed by inspection methods. This paper tackles this problem by first discussing the difficulties involved in tailoring the perspective-based inspection approach to object-oriented development methods and, second, by presenting a generalization of the approach which overcomes these limitations. The new version of the approach is illustrated in the context of UML-based object-oriented development

Analysis of Errors in Software Reliability Prediction Systems and Application of Model Uncertainty Theory to Provide Better Predictions

Models are the medium by which we reflect and express our understanding of some aspect of reality, a particular unknown of interest. As it is virtually impossible to grasp any situation in its entire complexity, models are representations of reality that are always partial resulting in a state of uncertainty or error. However the question of model error from a pragmatic point of view is not one of accounting for the difference between models and reality at a fundamental level, as such difference always exists. Rather the question is whether the prediction or performance of the model is correct at some practically acceptable level, within the model's domain of application. Here lays the importance of assessing the impact of uncertainties about predictions of a model, modeling the error and trying to reduce the uncertainties associated as much as possible to provide better estimations. While the methods for assessing the impact of errors on the performance of a model and error modeling are well established in various scientific and engineering disciplines, to the best of our knowledge no substantial work has been done in the field of Software Reliability Modeling despite the fact that the inadequacy of the present state and techniques of software reliability estimation has been recognized by industry and government agencies. In summary, even though hundreds of software reliability models have been developed, the software reliability discipline is still struggling to establish a software reliability prediction framework. This work intends to improve the performance of software reliability models through error modeling. It analyzes the errors associated with a set of five software Reliability Prediction Systems (RePSs) and attempts to improve their prediction accuracy using a model uncertainty framework. In the process, this work also statistically validates the performances of the RePSs. It also provides a time and cost effective alternative to performing experiments that are required to assess the error form which is integral to the process of application of the model uncertainty framework

The Impact of Background and Experience on Software Inspections

This dissertation is an initial study into the relationship between an inspector's characteristics and his or her effectiveness in an inspection. Research has shown that improving the individual effectiveness of the inspectors improves the overall effectiveness of an inspection team. But, the performance of inspectors varies widely, even when using the same inspection technique. This variation is often due to the inherent differences among the inspectors who used the technique. In order to better understand this variation and provide guidance to inspection planners, this dissertation has focused on the background and experience of the inspector as the source of variation. To study this issue I used a novel approach for software engineering, grounded theory. This methodology allowed hypotheses to be built both top-down, from the literature, as well as bottom-up, using data. The literature portion came from software engineering as well as education and psychology. The data portion came from both existing studies and newly designed studies. The data from existing studies allowed the initial hypotheses to become more concrete. Once some of the hypotheses had support from data, the final step was to design studies to test a subset of the hypotheses. I designed and ran two studies to test the selected hypotheses. The goal of the first study was to understand the type and level of experience with the software inspection process that was necessary. The earlier data had shown that process experience was important, but the effect of the type and level of experience was still unclear. The goal of the second study was to understand the interaction between an inspector's software development experience and the level of detail required in an inspection process. The earlier data had shown some indications that for experienced inspectors too much detail reduced the number of defects found, while less experienced inspectors needed more detail to overcome their lack of experience and find more defects. This dissertation presents complete list of hypotheses and the results of these studies along with some specific suggestions for both researchers and practitioners