Ian Douglas Sanders

Abstracting and Narrating Novice Programs Using Regular Expressions

The Syntax-Free Approach (SFA) to teaching programming was proposed in response to the perceived challenges often faced by novice programmers while taking their first course in programming. The idea of the SFA is to provide a level of abstraction over the language syntax and teach programming to novices as algorithms instead of lines of code. In this paper, we report the development of a tool that translates novice programs into detailed textual algorithms using regular expressions. We refer to these algorithms as narrations. These narrations are syntax-free, can improve readability and aid the comprehension of programs. The technique described can also be employed for automatic generation of hints or tips for novice programmers during classroom or laboratory sessions.

Requirements for secure graphical password schemes

Visual or graphical passwords have been proposed as possible alternatives to alphanumeric passwords. People can remember these better and for longer periods than they can alphanumeric passwords. Visual passwords can, however, not yet be readily adopted for use due to the disadvantages associated with them. There has therefore been a move in literature to discussions on efficient implementation of visual password schemes. This paper analyses the current challenges in the design of visual password schemes as well as the factors affecting security and usability of such schemes. The paper further presents requirements of a visual password scheme providing ease of use, a large enough password space and secure password images.

Introducing Code Adviser: A DFA-driven Electronic Programming Tutor

In this paper, we demonstrate a software system called Code Adviser that attempts to understand and find semantic bugs in student programs written in C++ programming language. To do this, Code Adviser has to take a model solution from a lecturer (or expert), generate many variations of the model solution, and compare student programs to the most similar model solution. The student’s program to be checked for correctness is normalized, granulated and abstracted to a string of semantic tokens — we call this the abstraction stage. Similarly, the model solutions are taken through the abstraction stage and the program strings representing all model solutions are abstracted to deterministic finite automaton (DFA) for the programming problem. Code Adviser then uses some algorithms to make inference on student’s program correctness. If the student’s program string is accepted by the problem’s DFA, it is reported as correct. Else, we make inferences on what the bug could be. Code Adviser is a promising proof of concept, and more work is currently being done to improve its inference and make it available to student programmers.

First year students' understanding of the flow of control in recursive algorithms

Abstract Recursion is an important concept for any computer science student to master. Many first year students develop the viable copies mental model of recursion and can successfully trace the execution of a simple recursive function. This article discusses a study focused on determining whether the ability to successfully trace a recursive function means that the student understands recursion or whether they are simply “applying a formula”. The research question investigated was thus “To what extent do students with viable trace mental models understand the flow of control of recursive algorithms?” The research followed a phenomenological approach. A group of first year students with viable mental models was identified by classifying the mental models in their answers to test questions. Fifteen of these students were interviewed. The interviews involved the students talking aloud while they tackled various tasks. Each students understanding of the active flow, the limiting case and the passive flow was assessed. The results show that in most cases even these students have some difficulty with the active flow, are confused about the passive flow and have misconceptions about the limiting case. This implies that more careful thought needs to be given to the examples used in teaching recursion and how the concept is taught.

Cooperating to buy shoes: an application of picking cycles in directed graphs

In this paper cycle picking in defined as an optimisation problem where cycles are chosen from a directed graph under the constraint that any node that is in a cycle in the original directed graph must be in at least one of the chosen cycles. This problem is an abstraction of a real-world problem where people who require different sized shoes cooperate to be able to buy shoes that fit. The paper considers a number of variations of the problem -- the minimum number of cycles, the all small cycles and the minimum total cycle length views. The paper also shows how the directed graph can be amended to ensure that every node in the original graph is in at least one cycle of an augmented graph before the optimisation phase commences. This is the equivalent of adding dummy people to the group of all people who need shoes to ensure that everyone who needs shoes has a group (even if it contains dummy nodes) of other people with whom to cooperate. Finally a simple greedy heuristic approach for finding approximate solutions to instances of the problem is considered.

Measuring Perceptual Similarity of Syntactically Generated Pictures.

This paper shows how similar pictures can be generated using random and bag context picture grammars. An online survey was conducted to determine the similarity of the pictures generated by the picture grammars. Respondents were asked to rank pictures in order of similarity to the query picture. They were also asked to rank galleries of pictures from those containing pictures that are most similar to those containing pictures that are least similar. Furthermore, respondents were required to tell us how they determined the similarity of the pictures contained in the galleries. We then compared perceptual similarity with a chosen similarity measure — spatial color distribution descriptor (SpCD) — to determine if they are consistent. The spatial color distribution descriptor has provided excellent results in determining the similarity of computer-generated pictures, and so was seen as a good similarity measure for this research. The results show that there is a good correlation between the SpCD and perceptual similarity although in some instances humans do make different judgements.

Segmenting mangrove ecosystems drone images using SLIC superpixels

Abstract Mangrove ecosystems play a very important ecological role on land–ocean interfaces in tropical regions. These ecosystems comprise of various tree species and aquatic animals, protecting the environment and providing a habitat that supports many living organisms including humans. The identification of image regions in mangrove ecosystems plays a significant role in ecosystem monitoring and conservation. Recent studies have suggested oversegmentation of colour images using superpixels as a solution to the segmentation of image regions. This study used the SLIC superpixel algorithm and k-means clustering to segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji. The SLIC superpixel algorithm performed well to demarcate image regions with similar colour and texture information into patches and to use k-means for the segmentation of the whole image. These results lend support to the use of superpixel algorithms for the segmentation of mangrove ecosystems. Understanding how superpixels can be used for the segmentation of drone images will assist conservation efforts in mangrove ecosystems.

The Impact of Leadership, Trust and Time on Technology Choice by Virtual Teams

This paper describes research relating to collaborative work by an ad hoc virtual team of students at a distance education university in South Africa. Feedback obtained after the task was completed indicates that the adoption of swift trust by at least one team member is required to move the collaboration process forward. The pattern of communication flow of the virtual team is important as it reflects the trust relationships; this was seen to be star shaped with the self-appointed leader, the most trusting team member, in the centre. The swift trust shown by the leader is rapidly followed by knowledge-based trust developed by each team member towards the leader but not towards all other members. It seems possible that low levels of initial trust lead to Perceived Ease of Use being given precedence over Perceived Usefulness when choosing the collaboration technology and this results in sub-optimal task-technology fit. Ad hoc virtual teams should be assisted by implementing strategies for leadership, building trust and for handling time constraints.

Learners' and educators' perspectives on the value of web design in the South African grade 11 computer applications technology curriculum

Web design was introduced into the Computer Applications Technology (CAT) curriculum in South Africa at Grade 11 level in 2013, and Grade 12 in 2014. This paper reports on a study determining what value learners and educators saw in using web design and Hyper Text Markup Language (HTML). The paper comprises studies undertaken by 17 honours students in 2013 and 2014 as part of a research report module, and followed a survey research design in which 18 educators were interviewed and 319 learner questionnaires analysed. It was found that there was some disagreement regarding the level of support offered to educators having to learn HTML and that most learners enjoyed learning web design and were coping with the demands of learning HTML. Educators felt that web design ought to remain part of the CAT curriculum, although time constraints were frequently raised as problematic. The majority of learners, similarly, felt that there was value in including web design within the CAT curriculum. Workshops to support educators and a focus on computational thinking as a way forward are recommended. Furthermore, starting web development in Grade 10 should be considered.

Perceptual Similarity of Images Generated using Tree Grammars

In this paper, we take a look at how humans determine similarity (perceptual similarity) of abstract computer generated images. To this end, an online similarity survey was conducted with respondents ordering answer images in order of similarity to question images. Since all the survey images were generated with tree grammars, the most popular measure of tree similarity, the tree edit distance, was used to compare the images. This was done in order to determine how closely tree edit distance measures model perceptual similarity. Eight different types of tree edit distance measures were used in order to cover the broad range of tree edit distance and tree edit distance approximation methods. All the tree edit distance measures were then correlated with the online similarity survey results to determine which ones more closely model perceptual similarity. The results are then analysed in the light of some modern psychological theories of perceptual similarity.