Can using Fagan Inspections improve the quality of specification in 2011? A Case Study

In this paper, we explore why Fagan Inspections have become obsolete in the software industry, given the body of evidence which supports their use to improve the quality of software artefacts and the software development process. Since the late 1970’s, much has been written about how Fagan Inspections improve the quality of both processes and outputs of the software development process. The literature indicates that the Fagan Inspection technique can improve quality of software (or other software development artefacts) by a reduction in defects of 60 – 90%. However, recent literature suggests that inspection techniques in general and Fagan Inspections in particular, are no longer used. A study in 1998 found that respondents used inspections either irregularly or not at all. Teams often review artefacts informally, but believe that they are performing an inspection or formal review. The lack of rigour in the review process results in reduced benefits and more defects in the artefacts. To explore this situation, we conducted a case study with a local enterprise and we report on the early findings. These suggest that the introduction of Fagan Inspections may have a number of benefits before they have even been introduced fully, including recognition of flaws in the current development process, development of technical knowledge relating to the software process domain, and improved team relations and a ‘quality’ culture. In addition, the personnel using Fagan Inspection gain experience in the production of ‘quality’ artefacts

Autonomous systems thermographic NDT of composite structures

Transient thermography is a method used successfully in the evaluation of composite materials and aerospace structures. It has the capacity to deliver both qualitative and quantitative results about hidden defects or features in a composite structure. Aircraft must undergo routine maintenance – inspection to check for any critical damage and thus to ensure its safety. This work aims to address the challenge of NDT automated inspection and improve the defects’ detection by suggesting an autonomous thermographic imaging approach using a UAV (Unmanned Aerial Vehicle) active thermographic system. The concept of active thermography is discussed and presented in the inspection of aircraft CFRP panels along with the mission planning for aerial inspection using the UAV for real time inspection. Results indicate that the suggested approach could significantly reduce the inspection time, cost, and workload, whilst potentially increase the probability of detection of defects on aircraft composites

Towards a self-evolving software defect detection process

Software defect detection research typically focuses on individual inspection and testing techniques. However, to be effective in applying defect detection techniques, it is important to recognize when to use inspection techniques and when to use testing techniques. In addition, it is important to know when to deliver a product and use maintenance activities, such as trouble shooting and bug fixing, to address the remaining defects in the software.To be more effective detecting software defects, not only should defect detection techniques be studied and compared, but the entire software defect detection process should be studied to give us a better idea of how it can be conducted, controlled, evaluated and improved.This thesis presents a self-evolving software defect detection process (SEDD) that provides a systematic approach to software defect detection and guides us as to when inspection, testing or maintenance activities are best performed. The approach is self-evolving in that it is continuously improved by assessing the outcome of the defect detection techniques in comparison with historical data.A software architecture and prototype implementation of the approach is also presented along with a case study that was conducted to validate the approach. Initial results of using the self-evolving defect detection approach are promising

Investigating Effective Inspection of Object-Oriented Code

Since the development of software inspection over twenty-five years ago it has become established as an effective means of detecting defects. Inspections were originally developed at a time when the procedural paradigm was dominant but, with the Object- Oriented (OO) paradigm growing in influence and use, there now exists a lack of guidance on how to apply inspections to OO systems. Object-oriented and procedural languages differ not only in their syntax but also in a number of more profound ways - the encapsulation of data and associated functionality, the common use of inheritance, and the concepts of polymorphism and dynamic binding. These factors influence the way that modules (classes) are created in OO systems, which in turn influences the way that OO systems are structured and execute. Failure to take this into account may hinder the application of inspections to OO code. This thesis shows that the way in which the objectoriented paradigm distributes related functionality can have a serious impact on code inspection and, to address this problem, it develops and empirically evaluates three code reading techniques

Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare dierent edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS