Dimitris Christodoulakis

Measuring the readability and maintainability of hyperdocuments

The problem of poorly written hyperdocuments has already been identified. Furthermore, there is no complete definition of hyperdocument quality and the methodology and tools that will help in analysing and assessing the quality of hyperdocuments are missing. The ability to measure attributes of hyperdocuments is indispensable for the fields of hyperdocument authoring and hypertext engineering. Useful paradigms can be drawn from the practices used in the software engineering and software measurement fields. In this paper we define a hyperdocument quality model, based on the ideas of the well-known Factor-Criteria-Metric hierarchical model. The important factors of readability and maintainability are defined, as well as the corresponding criteria. Finally, structure metrics, that can be computed on the hypertext graph, are presented. Most of these metrics are derived from well-known software metrics. Experimentation is a key issue for the application of measurement, and flexible tools for the automatic collection of measures are needed to support it. Athena, a tool that was originally developed for software measurement and later tailored to meet hypertext measurement needs, is used for hyperdocument measurement.

Naming as a fundamental concept of open hypermedia systems

Names play a key role in distributed hypertext systems, for two main reasons: Firstly, because accessing and managing system services require finding and locating the relevant components. Secondly, because managing structures between hypertext resources, such as nodes, anchors and links, requires that these resources are named and addressed. We argue that naming services are endemic to hypertext systems and therefore, form a core part of any hypertext system’s infrastructure. In particular, the current move towards interoperable component-based Open Hypermedia Systems (CB-OHS) demonstrates the need for naming components.

Software Quality: The User's Point of View

In this paper is presented a methodological approach for the measurement and the evaluation of users’ opinion for a software product. The methodology is general and applicable for every product and, as a concept, in every situation. The basic principle for the methodology is that each user’s opinion should be evaluated in analogy to this user’s qualifications in respect to computers in general, to this particular product and to the application automated by this. Therefore, the measurement and the analysis of the users’ qualifications is performed before users are asked for their opinion about the product. Afterwards, the users will be asked their opinion about the product. This opinion counts equally to their pre-measured qualifications.

DirectoryRank: ordering pages in web directories

Web Directories are repositories of Web pages organized in a hierarchy of topics and sub-topics. In this paper, we present DirectoryRank, a ranking framework that orders the pages within a given topic according to how informative they are about the topic. Our method works in three steps: first, it processes Web pages within a topic in order to extract structures that are called lexical chains, which are then used for measuring how informative a page is for a particular topic. Then, it measures the relative semantic similarity of the pages within a topic. Finally, the two metrics are combined for ranking all the pages within a topic before presenting them to the users.

The Callimachus approach to distributed hypermedia

We present the issues and design of the naming architecture of Callitnachus an open distributed hypermedia system.

Early Estimation of Users' Perception of Software Quality

This paper presents a methodology for estimating users’ opinion of the quality of a software product. Users’ opinion changes with time as they progressively become more acquainted with the software product. In this paper, we study the dynamics of users’ opinion and offer a method for assessing users’ final perception, based on measurements in the early stages of product release. The paper also presents methods for collecting users’ opinion and from the derived data, shows how their initial belief state for the quality of the product is formed. It adapts aspects of Belief Revision theory in order to present a way of estimating users’ opinion, subsequently formed after their opinion revisions. This estimation is achieved by using the initial measurements and without having to conduct surveys frequently. It reports the correlation that users tend to infer among quality characteristics and represents this correlation through a determination of a set of constraints between the scores of each quality characteristic. Finally, this paper presents a fast and automated way of forming users’ new belief state for the quality of a product after examining their opinion revisions.

Web directory construction using lexical chains

Web Directories provide a way of locating relevant information on the Web. Typically, Web Directories rely on humans putting in significant time and effort into finding important pages on the Web and categorizing them in the Directory. In this paper we present a way for automating the creation of a Web Directory. At a high level, our method takes as input a subject hierarchy and a collection of pages. We first leverage a variety of lexical resources from the Natural Language Processing community to enrich our hierarchy. After that, we process the pages and identify sequences of important terms, which are referred to as lexical chains. Finally, we use the lexical chains in order to decide where in the enriched subject hierarchy we should assign every page. Our experimental results with real Web data show that our method is quite promising into assisting humans during page categorization.

POS disambiguation and unknown word guessing with decision trees

This paper presents a decision-tree approach to the problems of part-of-speech disambiguation and unknown word guessing as they appear in Modern Greek, a highly inflectional language. The learning procedure is tag-set independent and reflects the linguistic reasoning on the specific problems. The decision trees induced are combined with a high-coverage lexicon to form a tagger that achieves 93, 5% overall disambiguation accuracy.

ATHENA: a software measurement and metrics environment

ATHENA is a parametrizable software tool oriented towards the measurement of software quality characteristics. Measurement is based on the syntax and semantic (graph-based) analysis of programs. ATHENA is language-independent and customizable, i.e. language specifications as well as measurement algorithms are input to the tool which automatically generates the measurement environment for the corresponding language. Currently ATHENA has the ability to support Pascal, ADA and C and offers the possibility of measuring a set of kernel metrics (e.g. Halsteads ‘Software Complexity Measure’, McCabes ‘Cyclomatic Complexity Metric’, Tais ‘Data Flow Complexity Measure’ etc.). A specially designed specification language allows for easy implementation of design and code metrics. This is one of the reasons that ATHENA is particularly useful for software maintainability control.

Towards an automated tool for software certification

The theoretical foundation and the main functionalities of the ATHENA software quality and certification tool are outlined. ATHENA supports the measurement of software quality factors, calculates a wide range of software quality metrics, and reports on the quality of software packages, using a software certification expert subsystem. The measurement kernel and the expert subsystem are described.<<ETX>>