Norsaremah Salleh

An empirical study of the effects of personality in pair programming using the five-factor model

Pair Programming (PP) has been long researched in industry and academia. Although research evidence about its usefulness is somewhat inconclusive, previous studies showed that its use in an academic environment can benefit students in programming and design courses. In our study, we investigated the “human” aspect of PP; in particular the effects that personality attributes may have on PPs effectiveness as a pedagogical tool. We conducted a formal experiment at the University of Auckland to investigate the influence of personality differences among paired students using the Five-Factor Model as a personality measurement framework. The aim of our study was to improve the implementation of PP as a pedagogical tool through understanding the impact the variation in the personality profile of paired students has towards their academic performance. Our findings showed that differences in personality traits did not significantly affect the academic performance of students who pair programmed.

Investigating the effects of personality traits on pair programming in a higher education setting through a family of experiments

Evidence from our systematic literature review revealed numerous inconsistencies in findings from the Pair Programming (PP) literature regarding the effects of personality on PP’s effectiveness as a pedagogical tool. In particular: i) the effect of differing personality traits of pairs on the successful implementation of pair-programming (PP) within a higher education setting is still unclear, and ii) the personality instrument most often used had been Myers-Briggs Type Indicator (MBTI), despite being an indicator criticized by personality psychologists as unreliable in measuring an individual’s personality traits. These issues motivated the research described in this paper. We conducted a series of five formal experiments (one of which was a replicated experiment), between 2009 and 2010, at the University of Auckland, to investigate the effects of personality composition on PP’s effectiveness. Each experiment looked at a particular personality trait of the Five-Factor personality framework. This framework comprises five broad traits (Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), and our experiments focused on three of these - Conscientiousness, Neuroticism, and Openness. A total of 594 undergraduate students participated as subjects. Overall, our findings for all five experiments, including the replication, showed that Conscientiousness and Neuroticism did not present a statistically significant effect upon paired students’ academic performance. However, Openness played a significant role in differentiating paired students’ academic performance. Participants’ survey results also indicated that PP not only caused an increase in satisfaction and confidence levels but also brought enjoyment to the tutorial classes and enhanced students’ motivation.

A systematic mapping study of mobile application testing techniques

We performed a systematic mapping study on mobile application testing techniques.79 empirical studies are mapped to a classification schema.Classification scheme includes, structure the topic, evaluation type and contribution facets.Several research gaps in current literature are revealed and discussed. The importance of mobile application specific testing techniques and methods has been attracting much attention of software engineers over the past few years. This is due to the fact that mobile applications are different than traditional web and desktop applications, and more and more they are moving to being used in critical domains. Mobile applications require a different approach to application quality and dependability and require an effective testing approach to build high quality and more reliable software. We performed a systematic mapping study to categorize and to structure the research evidence that has been published in the area of mobile application testing techniques and challenges that they have reported. Seventy nine (79) empirical studies are mapped to a classification schema. Several research gaps are identified and specific key testing issues for practitioners are identified: there is a need for eliciting testing requirements early during development process; the need to conduct research in real-world development environments; specific testing techniques targeting application life-cycle conformance and mobile services testing; and comparative studies for security and usability testing.

The effects of openness to experience on pair programming in a higher education context

This paper describes a formal experiment carried out to investigate the effect of the personality factor Openness to experience on the academic performance of students who practiced pair programming (PP) in higher education. The experiment was carried out at the University of Auckland, using as subjects undergraduate students attending an introductory software programming course. Our results showed that differences in Openness level could significantly affect academic performance of students who pair programmed. In addition, our results also showed that most students gained higher satisfaction from the PP experience and their confidence level in solving programming exercises was also high.

Examining Information Disclosure Behavior on Social Network Sites Using Protection Motivation Theory, Trust and Risk

This paper reports on an empirical study that investigates the information disclosure behavior on Social Network Sites (SNS) focusing on undergraduate University students as our population. Although much have been reported on the issue of information privacy or privacy leakage on SNS, very few have employed the Protection Motivation Theory (PMT) as a framework to understand SNS user’s behavior related to information disclosure. In this study, the PMT incorporated with trust and risk factor, has revealed that trust on SNS and perceived benefits influenced information disclosure behaviour. Our findings showed that all PMT constructs are significantly related to privacy concern. However, privacy concern and perceived risk were found not related to information disclosure behaviour. Using self-administered questionnaire, 486 undergraduate students from five different universities in Malaysia were involved in this study.

Extracting features from online software reviews to aid requirements reuse

Display Omitted The extraction of software features from Software Requirement Specifications (SRS) is viable only to practitioners who have the access.Online reviews for software products can be used as input for features extraction to assist requirements reuse.Techniques from unsupervised learning and Natural Language Processing is employed as a propose solutions to Requirements Reuse problem.The approach obtained a precision of 87% (62% average) and a recall of 86% (82% average), when evaluated against the truth data set created manually. Sets of common features are essential assets to be reused in fulfilling specific needs in software product line methodology. In Requirements Reuse (RR), the extraction of software features from Software Requirement Specifications (SRS) is viable only to practitioners who have access to these software artefacts. Due to organisational privacy, SRS are always kept confidential and not easily available to the public. As alternatives, researchers opted to use the publicly available software descriptions such as product brochures and online software descriptions to identify potential software features to initiate the RR process. The aim of this paper is to propose a semi-automated approach, known as Feature Extraction for Reuse of Natural Language requirements (FENL), to extract phrases that can represent software features from software reviews in the absence of SRS as a way to initiate the RR process. FENL is composed of four stages, which depend on keyword occurrences from several combinations of nouns, verbs, and/or adjectives. In the experiment conducted, phrases that could reflect software features, which reside within online software reviews were extracted by utilising the techniques from information retrieval (IR) area. As a way to demonstrate the feature groupings phase, a semi-automated approach to group the extracted features were then conducted with the assistance of a modified word overlap algorithm. As for the evaluation, the proposed extraction approach is evaluated through experiments against the truth data set created manually. The performance results obtained from the feature extraction phase indicates that the proposed approach performed comparably with related works in terms of recall, precision, and F-Measure.

Empirical Studies of Cloud Computing in Education: A Systematic Literature Review

The purpose of this paper is to present the evidence about adoption of cloud computing in the education system in universities or higher education institutions. We performed a systematic literature review SLR of empirical studies that investigated the current level of adoption of cloud computing in the education systems and motivations for using cloud computing in the institution. Seven papers were included in our synthesis of evidence. It has been found that several universities are interested in using cloud computing in their education systems, and they have utilized different types of cloud computing service models IaaS, PaaS, SaaS. The results of this SLR show that a clear gap exists in this research field: a lack of empirical studies focusing on utilizing cloud computing within educational institutions.

A Framework for Evaluating Skyline Queries over Incomplete Data

Research interest in skyline queries has been significantly increased over the years, as skyline queries can be utilized in many contemporary applications, such as multi-criteria decision-making system, decision support system, recommendation system, data mining, and personalized systems. Skyline queries return data item that is not dominated by any other data items in all dimensions (attributes). Most of the existing skyline approaches assumed that database is complete and values are present during the skyline process. However, such assumption is not always to be true, particularly in a real world database where values of data item might not be available (missing) in one or more dimensions. Thus, the incompleteness of the data impacts negatively on skyline process due to losing the transitivity property which leads into the issue of cyclic dominance. Therefore, applying skyline technique directly on an incomplete database is prohibitive and might result into exhaustive pairwise comparison. This paper presents an approach that efficiently evaluates skyline queries in incomplete database. The approach aims at reducing the number of pairwise comparisons and shortens the searching space in identifying the skylines. Several experiments have been conducted to demonstrate that our approach outperforms the previous approach through producing a lower number of pairwise comparisons. Furthermore, the result also illustrates that our approach is scalable and efficient.

Terms Extractions: An Approach for Requirements Reuse

This paper presents a solution to a requirements reuse problem that utilises natural language processing and information retrieval technique. We proposed a semi-automated approach to extract the software features from online software review to assist the process to reuse natural language requirements. We have conducted an experiment to compare the manual feature extraction versus the semi-automated feature extraction. We used compilations of software review from the Internet as a source of this extraction process. The extracted software features are compared against the features obtained manually by human and the evaluation results obtained in terms of time, precision, recall, and F-Measure indicate a promising result.

Mobile Application Testing in Industrial Contexts: An Exploratory Multiple Case-Study

Recent empirical studies in the area of mobile application testing indicate the need for specific testing techniques and methods for mobile applications. This is due to mobile applications being significantly different than traditional web and desktop applications, particularly in terms of the physical constraints of mobile devices and the very different features of their operating systems. In this paper, we presented a multiple case-study involving four software development companies in the area of mobile and smartphones application. We aimed to identify testing techniques currently being applied by developers and challenges that they are facing. Our principle results are that many industrial teams seem to lack sufficient knowledge on how to test mobile applications, particularly in the areas of mobile application life-cycle conformance, context-awareness, and integration testing. We also found that there is no formal testing approach or methodology that can facilitate a development team to systematically test a critical mobile application.