A Software Vulnerability Prediction Model Using Traceable Code Patterns And Software Metrics

Software security is an important aspect of ensuring software quality. The goal of this study is to help developers evaluate software security at the early stage of development using traceable patterns and software metrics. The concept of traceable patterns is similar to design patterns, but they can be automatically recognized and extracted from source code. If these patterns can better predict vulnerable code compared to the traditional software metrics, they can be used in developing a vulnerability prediction model to classify code as vulnerable or not. By analyzing and comparing the performance of traceable patterns with metrics, we propose a vulnerability prediction model. Objective: This study explores the performance of code patterns in vulnerability prediction and compares them with traditional software metrics. We have used the findings to build an effective vulnerability prediction model. Method: We designed and conducted experiments on the security vulnerabilities reported for Apache Tomcat (Releases 6, 7 and 8), Apache CXF and three stand-alone Java web applications of Stanford Securibench. We used machine learning and statistical techniques for predicting vulnerabilities of the systems using traceable patterns and metrics as features. Result: We found that patterns have a lower false negative rate and higher recall in detecting vulnerable code than the traditional software metrics. We also found a set of patterns and metrics that shows higher recall in vulnerability prediction. Conclusion: Based on the results of the experiments, we proposed a prediction model using patterns and metrics to better predict vulnerable code with higher recall rate. We evaluated the model for the systems under study. We also evaluated their performance in the cross-dataset validation

A descriptive model of the offence chain for imprisoned adult male firesetters (descriptive model of adult male firesetting)

Purpose: Firesetting has devastating consequences. Although some theoretical efforts have been made to explain firesetting (i.e., a small number of multi- and single-factor theories), little effort has been devoted to understand how deliberate firesetting unfolds across time (i.e., micro or offence chain theories). This research aimed to produce the first descriptive offence chain theory for incarcerated adult male firesetters.Methods: Thirty-eight adult male firesetters—recruited from prison establishments in England and Wales—were interviewed about the events, thoughts and feelings leading up to, surrounding, and immediately following a deliberate incident of firesetting. Results: Using Grounded Theory analysis, the Descriptive Model of Adult male Firesetting (DMAF) was developed documenting the cognitive, behavioural, affective and contextual factors leading to a single incident of deliberate firesetting. Conclusions: New information generated from the DMAF is presented and its contributions to the current evidence base are highlighted. Clinical implications, limitations and future research directions are also discussed

Low Carbon Resilient Development and Gender Equality in the Least Developed Countries

The issue of gender equality and climate change has come to the fore in both policy and research arenas in the last decade, due to the widespread recognition that neither the impact pathways for climate change, nor the policy responses are gender-neutral. Whilst it shouldn't be assumed to always be the case, climate change can worsen existing conflicts and gender inequalities, and some strategies to address climate risks can exacerbate this if not applied with gender-sensitive principles. Gender-sensitivity is therefore a key priority for lowcarbon climate resilient planning at local, national and international levels

Assessment of access to health services and vulnerabilities of female fish traders in the Kafue Flats, Zambia: analysis report

Under the regional programme Fisheries and HIV/AIDS in Africa: Investing in Sustainable Solutions, the WorldFish Center conducted this study on access to health services and vulnerabilities of female fish traders in the Kafue Flats floodplains in Zambia. This report outlines and analyses the particular vulnerabilities of female fish traders in the Kafue Flats fishery and formulates recommendations to facilitate stakeholder uptake of strategic responses to tackle the drivers of the epidemic in fishing communities and improve the livelihoods of fisher folk and fish traders in the Kafue Flats and other fisheries in Zambia. (pdf contains 55 pages

HIV/AIDS, Security and Conflict: New Realities, New Responses

Ten years after the HIV/AIDS epidemic itself was identified as a threat to international peace and security, findings from the three-year AIDS, Security and Conflict Initiative (ASCI)(1) present evidence of the mutually reinforcing dynamics linking HIV/AIDS, conflict and security

A Deep Learning approach to predict software bugs using micro patterns and software metrics

Software bugs prediction is one of the most active research areas in the software engineering community. The process of testing and debugging code proves to be costly during the software development life cycle. Software metrics measure the quality of source code to identify software bugs and vulnerabilities. Traceable code patterns are able to de- scribe code at a finer granularity level to measure quality. Micro patterns will be used in this research to mechanically describe java code at the class level. Machine learning has also been introduced for bug prediction to localize source code for testing and debugging. Deep Learning is a branch of Machine Learning that is relatively new. This research looks to improve the prediction of software bugs by utilizing micro patterns with deep learning techniques. Software bug prediction at a finer granularity level will enable developers to localize code to test and debug during the development process

Towards Inclusive Gender in Transitional Justice: Gaps, Blind-Spots and Opportunities

While gender perspectives have become a burgeoning focus of analysis in transitional justice, the dominant conceptualization of 'gender' in such processes is effectively an exclusive one. As a result, careful consideration for the roles of masculinities and for the experiences of sexual and gender minorities remains strikingly absent. To engage with these blind-spots, in this article I initiate a move towards a more inclusive understanding of gender in transitional justice, which includes masculinities and queer perspectives. I also indicate how a move from the macro- to the micro-level of TJ implies opportunities and challenges for more inclusive understandings of gender

Capturing the We-ness of Happy Couples through Narrative Analysis

“We-ness” refers to a couple’s mutual investment in their relationship and in each other, involving reciprocity and prioritization of the relationship. The goal of this study was to examine We-ness through relationship narratives called “We-Stories” constructed by couples, and to develop a coding system to identify the core thematic elements that make up these narratives. Couples who self-identified as “happy” (N = 53) generated We-Stories and completed measures of relationship satisfaction and mutuality. These stories were then coded using the We-Stories coding manual developed by the researcher in conjunction with their supervising professor. Findings indicated that security, an element that involves aspects of safety, support, and commitment, was overwhelmingly present, appearing in 58.5% of all narratives. This element was followed by the elements of pleasure (49.1%) and shared meaning/vision (37.7%). The frequency of these particular elements suggests that the relationship aspects that happy couples value most are a solid trusting foundation, a genuine enjoyment of and love for their partners, and the visualization of a larger shared purpose in their lives. Number of “We-ness” elements was also correlated with and predictive of discrepancy scores on measures of relationship mutuality, indicating the validity of the We-Stories coding manual. Limitations and future directions are discussed

Studying small states : a review

This essay provides an overview of the literature in the field of small states studies. It analyses the development of the discipline, and in particular how vulnerability and a lack of capacity – core concepts of the early small state literature – have dominated the discipline ever since. It also explores how realism, liberalism and constructivism respectively approach the study of small states. However, we also outline how the focus has over time slowly shifted from the challenges associated with smallness to opportunities. There is considerable literature across various disciplines that helps us to better understand small states in International Relations; but there remains a largely unexplored field of inquiry about small states which needs to be thoroughly examined and theorised. Studies of small states have never been as relevant as today, given the increasing number of small states and with many small territories that are potential candidates for independence.peer-reviewe