Adding traceability to an educational IDE : a thesis presented in partial fulfilment of the requirements for the Master degree in Computer Science at Massey University, Manawatu, New Zealand

High dropout and failure rate in introductory programming courses indicate the need to improve programming comprehension of novice learners. Some of educational tools have successfully used game environments to motivate students. Our approach is based on a novel type of notional machine which can facilitate programming comprehension in the context of turn-based games. The first aim of this project is to design a layered notional machine that is reversible. This type of notional machine provides bi-directional traceability and supports multiple layers of abstraction. The second aim of this project is to explore the feasibility and in particular to evaluate the performance of using the traceability in a web-based environment. To achieve these aims, we implement this type of notional machine through instrumentation and investigate the capture of the entire execution state of a program. However, capturing the entire execution state produces a large amount of tracing data that raises scalability issues. Therefore, several encoding and compression methods are proposed to minimise the server work-load. A proof-of-concept implementation which based on the SoGaCo educational web IDE is presented. The evaluation of the educational benefits and end user studies are outside the scope of this thesis

A study of the high-inclination population in the Kuiper belt - II. The Twotinos

As the second part of our study, in this paper we proceed to explore the dynamics of the high-inclination Twotinos in the 1:2 Neptune mean motion resonance (NMMR). Depending on the inclination $i$, we show the existence of two critical eccentricities $e_a(i)$ and $e_c(i)$, which are lower limits of the eccentricity $e$ for the resonant angle $\sigma$ to exhibit libration and asymmetric libration, respectively. Accordingly, we have determined the libration centres $\sigma_0$ for inclined orbits, which are strongly dependent on $i$. With initial $\sigma=\sigma_0$ on a fine grid of $(e, i)$, the stability of orbits in the 1:2 NMMR is probed by 4-Gyr integrations. It is shown that symmetric librators are totally unstable for $i\ge30^{\circ}$; while stable asymmetric librators exist for $i$ up to $90^{\circ}$. We further investigate the 1:2 NMMR capture and retention of planetesimals with initial inclinations $i_0\le90^{\circ}$ in the planet migration model using a time-scale of $2\times10^7$ yr. We find that: (1) the capture efficiency of the 1:2 NMMR decreases drastically with the increase of $i_0$, and it goes to 0 when $i_0\ge60^{\circ}$; (2) the probability of discovering Twotinos with $i>25^{\circ}$, beyond observed values, is roughly estimated to be $\le0.1$ per cent; (3) more particles are captured into the leading rather than the trailing asymmetric resonance for $i_0\le10^{\circ}$, but this number difference appears to be the opposite at $i_0=20^{\circ}$ and is continuously varying for even larger $i_0$; (4) captured Twotinos residing in the trailing resonance or having $i>15^{\circ}$ are practically outside the Kozai mechanism, like currently observed samples.Comment: 13 pages, 10 figures, Accepted by MNRAS. Comments welcome

Statistical computation of Boltzmann entropy and estimation of the optimal probability density function from statistical sample

In this work, we investigate the statistical computation of the Boltzmann entropy of statistical samples. For this purpose, we use both histogram and kernel function to estimate the probability density function of statistical samples. We find that, due to coarse-graining, the entropy is a monotonic increasing function of the bin width for histogram or bandwidth for kernel estimation, which seems to be difficult to select an optimal bin width/bandwidth for computing the entropy. Fortunately, we notice that there exists a minimum of the first derivative of entropy for both histogram and kernel estimation, and this minimum point of the first derivative asymptotically points to the optimal bin width or bandwidth. We have verified these findings by large amounts of numerical experiments. Hence, we suggest that the minimum of the first derivative of entropy be used as a selector for the optimal bin width or bandwidth of density estimation. Moreover, the optimal bandwidth selected by the minimum of the first derivative of entropy is purely data-based, independent of the unknown underlying probability density distribution, which is obviously superior to the existing estimators. Our results are not restricted to one-dimensional, but can also be extended to multivariate cases. It should be emphasized, however, that we do not provide a robust mathematical proof of these findings, and we leave these issues with those who are interested in them.Comment: 8 pages, 6 figures, MNRAS, in the pres

Implicit Discourse Relation Classification via Multi-Task Neural Networks

Without discourse connectives, classifying implicit discourse relations is a challenging task and a bottleneck for building a practical discourse parser. Previous research usually makes use of one kind of discourse framework such as PDTB or RST to improve the classification performance on discourse relations. Actually, under different discourse annotation frameworks, there exist multiple corpora which have internal connections. To exploit the combination of different discourse corpora, we design related discourse classification tasks specific to a corpus, and propose a novel Convolutional Neural Network embedded multi-task learning system to synthesize these tasks by learning both unique and shared representations for each task. The experimental results on the PDTB implicit discourse relation classification task demonstrate that our model achieves significant gains over baseline systems.Comment: This is the pre-print version of a paper accepted by AAAI-1

Tissue Culture of Pili Nut (Canarium Ovatum) Andisozyme Electrophoresis of Some Related Canarium Species

Studies were conducted for the in vitro culture of pili nut. Different explant sources, such as petiole, leaf, mature cotyledon, immature cotyledon and embryo axis were used. Horizontally placed petioles produced vigorous callus growth in half and full strength WPM with combinations of 2, 4-D and Kinetin. The highest callus fresh weight was obtained in the medium with 1 mg/1 2, 4-D, or 1 mg/1 2, 4-D plus 1 mg/1 Kinetin. Embryogenesis or shoot inductions were not successful from the petiole callus. Leaf and cotyledon explants produced limited callus using the same medium and growth regulator treatments, and immature embryo axes produced no callus. Shoot tips harvested from in vitro seedlings showed shoot and new leaf growth in WPM with a combination of BA and Kinetin, at 1 or 2 mg/1, but no root induction occurred when NAA and lAA were used. Shoot tips and nodal cuttings harvested from greenhouse grown seedlings were difficult to disinfect and did not perform well in in vitro culture. In this study, isozyme phenotypes (fingerprinting) of seven Canarium species were also developed using six enzyme systems (LAP, MDH, PGI, PGM, TPI and UGPP) utilizing a histidine - citric acid (pH 6.5) buffer system. Fifty-two plant samples of different Canarium species (twenty-two C. ovatum, five C. album, four C. megalanthum, six C. harveyi, eight C. mehenbethene, two C. odontophyllum, three C. indicum and two unknown) and one Dacroydes rostrata plant were surveyed. Ninety-seven different phenotypes of the six enzyme systems were obtained. All six enzymes showed high polymorphism. Phenotypic polymorphism (Pj) ranged from 0.93 (MDH) to 0.75 (TPI). The average Pj was 0.86 and the weighted polymorphism (Pw) was 0.84 among the accessions tested. All seven species were polymorphic, the Pj ranged from 0.53 for C. ovatum to 0.18 for C. mehenbethene. The pattern from cluster analysis agreed with most of the accession identities. Accessions of the same species formed a distinct cluster from other species. Some unique banding in different species have been tentatively identified and could be useful for the classification of the Canarium species

An investigation into the unsoundness of static program analysis : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Palmerston North, New Zealand

Static program analysis is widely used in many software applications such as in security analysis, compiler optimisation, program verification and code refactoring. In contrast to dynamic analysis, static analysis can perform a full program analysis without the need of running the program under analysis. While it provides full program coverage, one of the main issues with static analysis is imprecision -- i.e., the potential of reporting false positives due to overestimating actual program behaviours. For many years, research in static program analysis has focused on reducing such imprecision while improving scalability. However, static program analysis may also miss some critical parts of the program, resulting in program behaviours not being reported. A typical example of this is the case of dynamic language features, where certain behaviours are hard to model due to their dynamic nature. The term ``unsoundness'' has been used to describe those missed program behaviours. Compared to static analysis, dynamic analysis has the advantage of obtaining precise results, as it only captures what has been executed during run-time. However, dynamic analysis is also limited to the defined program executions. This thesis investigates the unsoundness issue in static program analysis. We first investigate causes of unsoundness in terms of Java dynamic language features and identify potential usage patterns of such features. We then report the results of a number of empirical experiments we conducted in order to identify and categorise the sources of unsoundness in state-of-the-art static analysis frameworks. Finally, we quantify and measure the level of unsoundness in static analysis in the presence of dynamic language features. The models developed in this thesis can be used by static analysis frameworks and tools to boost the soundness in those frameworks and tools