A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Data mining and database systems: integrating conceptual clustering with a relational database management system.

Many clustering algorithms have been developed and improved over the years to cater for large scale data clustering. However, much of this work has been in developing numeric based algorithms that use efficient summarisations to scale to large data sets. There is a growing need for scalable categorical clustering algorithms as, although numeric based algorithms can be adapted to categorical data, they do not always produce good results. This thesis presents a categorical conceptual clustering algorithm that can scale to large data sets using appropriate data summarisations. Data mining is distinguished from machine learning by the use of larger data sets that are often stored in database management systems (DBMSs). Many clustering algorithms require data to be extracted from the DBMS and reformatted for input to the algorithm. This thesis presents an approach that integrates conceptual clustering with a DBMS. The presented approach makes the algorithm main memory independent and supports on-line data mining

Faculty Publications and Creative Works 1999

One of the ways in which we recognize our faculty at the University of New Mexico is through Faculty Publications & Creative Works. An annual publication, it highlights our faculty\u27s scholarly and creative activities and achievements and serves as a compendium of UNM faculty efforts during the 1999 calendar year. Faculty Publications & Creative Works strives to illustrate the depth and breadth of research activities performed throughout our University\u27s laboratories, studios and classrooms. We believe that the communication of individual research is a significant method of sharing concepts and thoughts and ultimately inspiring the birth of new ideas. In support of this, UNM faculty during 1999 produced over 2,292 works, including 1,837 scholarly papers and articles, 78 books, 82 book chapters, 175 reviews, 113 creative works and 7 patented works. We are proud of the accomplishments of our faculty which are in part reflected in this book, which illustrates the diversity of intellectual pursuits in support of research and education at the University of New Mexico

Functionality-based application confinement: A parameterised and hierarchical approach to policy abstraction for rule-based application-oriented access controls

Access controls are traditionally designed to protect resources from users, and consequently make access decisions based on the identity of the user, treating all processes as if they are acting on behalf of the user that runs them. However, this user-oriented approach is insufficient at protecting against contemporary threats, where security compromises are often due to applications running malicious code, either due to software vulnerabilities or malware. Application-oriented access controls can mitigate this threat by managing the authority of individual applications. Rule-based application-oriented access controls can restrict applications to only allow access to the specific finely-grained resources required for them to carry out their tasks, and thus can significantly limit the damage that can be caused by malicious code. Unfortunately existing application-oriented access controls have policy complexity and usability problems that have limited their use. This thesis proposes a new access control model, known as functionality-based application confinement (FBAC). The FBAC model has a number of unique features designed to overcome problems with previous approaches. Policy abstractions, known as functionalities, are used to assign authority to applications based on the features they provide. Functionalities authorise elaborate sets of finely grained privileges based on high-level security goals, and adapt to the needs of specific applications through parameterisation. FBAC is hierarchical, which enables it to provide layers of abstraction and encapsulation in policy. It also simultaneously enforces the security goals of both users and administrators by providing discretionary and mandatory controls. An LSM-based (Linux security module) prototype implementation, known as FBAC-LSM, was developed as a proof-of-concept and was used to evaluate the new model and associated techniques. The policy requirements of over one hundred applications were analysed, and policy abstractions and application policies were developed. Analysis showed that the FBAC model is capable of representing the privilege needs of applications. The model is also well suited to automaiii tion techniques that can in many cases create complete application policies a priori, that is, without first running the applications. This is an improvement over previous approaches that typically rely on learning modes to generate policies. A usability study was conducted, which showed that compared to two widely-deployed alternatives (SELinux and AppArmor), FBAC-LSM had significantly higher perceived usability and resulted in significantly more protective policies. Qualitative analysis was performed and gave further insight into the issues surrounding the usability of application-oriented access controls, and confirmed the success of the FBAC model

Computer Graphics. Volume 2 - an Annotated Bibliography to the NASA-MSFC Digital Computer Graphics Program

Annotated bibliography on digital computer graphic