Estimating Software Task Effort in Crowds

A key task during software maintenance is the refinement and elaboration of emerging software issues, such as feature implementations and bug resolution. It includes the annotation of software tasks with additional information, such as criticality, assignee and estimated cost of resolution. This paper reports on a first study to investigate the feasibility of using crowd workers supplied with limited information about an issue and project to provide comparably accurate estimates using planning poker. The paper describes our adaptation of planning poker to crowdsourcing and our initial trials. The results demonstrate the feasibility and potential efficiency of using crowds to deliver estimates. We also review the additional benefit that asking crowds for an estimate brings, in terms of further elaboration of the details of an issue. Finally, we outline our plans for a more extensive evaluation of planning poker in crowds

On the application of artificial intelligence and human computation to the automation of agile software task effort estimation

Software effort estimation (SEE), as part of the wider project planning and product road mapping process, occurs throughout a software development life cycle. A variety of effort estimation methods have been proposed in the literature, including algorithmic methods, expert based methods, and more recently, methods based on techniques drawn from machine learning and natural language processing. In general, the consensus in the literature is that expert-based methods such as Planning Poker are more reliable than automated effort estimation. However, these methods are labour intensive and difficult to scale to large-scale projects. To address this limitation, this thesis investigates the feasibility of using human computation techniques to coordinate crowds of inexpert workers to predict expert-comparable effort estimates for a given software development task. The research followed an empirical methodology and used four different methods: literature review, replication, a series of laboratory experiments, and ethnography. The literature uncovered the lack of suitable datasets that include the attributes of descriptive text (corpus), actual cost, and expert estimates for a given software development task. Thus, a new dataset was developed to meet the necessary requirements. Next, effort estimation based on recent natural language processing advancements was evaluated and compared with expert estimates. The results suggest that there was no significant improvement, and the automated approach was still outperformed by expert estimates. Therefore, the feasibility of scaling the Planning Poker effort estimation method by using human computation in a micro-task crowdsourcing environment was explored. A series of pilot experiments were conducted to find the proper design for adapting Planning Poker to a crowd environment. This resulted in designing a new estimation method called Crowd Planning Poker (CPP). The pilot experiments revealed that a significant proportion of the crowd submitted poor quality assignments. Therefore, an approach to actively managing the quality of SEE work was proposed and evaluated before being integrated into the CPP method. A substantial overall evaluation was then conducted. The results demonstrated that crowd workers were able to discriminate between tasks of varying complexity and produce estimates that were comparable with those of experts and at substantially reduced cost compared with small teams of domain experts. It was further noted in the experiments that crowd workers provide useful insights as to the resolution of the task. Therefore, as a final step, fine-grained details about crowd workers’ behaviour, including actions taken and artifacts reviewed, were used in an ethnographic study to understand how crowd effort estimation takes place in a crowd. Four persona archetypes were developed to describe the crowd behaviours, and the results of the behaviour analysis were confirmed by surveying the crowd workers

Evaluation of Context-Aware Language Models and Experts for Effort Estimation of Software Maintenance Issues

Reflecting upon recent advances in Natural Language Processing (NLP), this paper evaluates the effectiveness of context-aware NLP models for predicting software task effort estimates. Term Frequency–Inverse Document Frequency (TF-IDF) and Bidirectional Encoder Representations from Transformers (BERT) were used as feature extraction methods; Random forest and BERT feed-forward linear neural networks were used as classifiers. Using three datasets drawn from open-source projects and one from a commercial project, the paper evaluates the models and compares the best performing model with expert estimates from both kinds of datasets. The results suggest that BERT as a feature extraction and classifier shows slightly better performance than other combinations, but that there is no significant difference between the presented methods. On the other hand, the results show that expert and Machine Learning (ML) estimate performances are similar, with the experts’ performance being slightly better. Both findings confirmed existing literature, but using substantially different experimental settings

Playing Planning Poker in Crowds: Human Computation of Software Effort Estimates

Reliable cost effective effort estimation remains a considerable challenge for software projects. Recent work has demonstrated that the popular Planning Poker practice can produce reliable estimates when undertaken within a software team of knowledgeable domain experts. However, the process depends on the availability of experts and can be time-consuming to perform, making it impractical for large scale or open source projects that may curate many thousands of outstanding tasks. This paper reports on a full study to investigate the feasibility of using crowd workers supplied with limited information about a task to provide comparably accurate estimates using Planning Poker. We describe the design of a Crowd Planning Poker (CPP) process implemented on Amazon Mechanical Turk and the results of a substantial set of trials, involving more than 5000 crowd workers and 39 diverse software tasks. Our results show that a carefully organised and selected crowd of workers can produce effort estimates that are of similar accuracy to those of a single expert

Comparing Privacy Control Methods for Smartphone Platforms

Abstract-Nowadays, many important applications are performed through mobile phones. It is essential to ensure that users' private information is not leaked through those applications. In this paper, we perform a comparison on privacy control methods implemented on the Android and iOS platforms based on the Bellotti and Sellen's framework. The comparison helps understand the discrepancies existent between the users' expectations for privacy and the privacy control methods currently implemented in Android and iOS. To better address users' privacy concerns, we propose a programming model for platform designers to improve privacy. Our initial study on 60 privacy bugs show that using the proposed programming models, 14 Android and 5 iOS privacy bugs can be eliminated

The Role of Technology in Preventive Measures to Combat Money Laundering Crime: Case study Sudan

This study aimed to highlight the role that technology can play in the preventive measures to combat money laundering, especially since money laundering crimes have become dependent on advanced technical techniques in addition to many electronic means that are currently available. This necessitated the development of advanced technical means and tools to combat money laundering. The researchers used the case study methodology, which is characterized by many advantages that make it suitable for this study, including that it allows the collection of data from multiple sources. The study reached many results, the most prominent of which is that the phenomenon of money laundering passes in most of the stage of transfers through bank accounts, which must provide a degree of banking secrecy for customer accounts, which makes the matter of balancing between combating money laundering and maintaining the secrecy of customer accounts difficult and not Palliser. The most prominent of the recommendations of this study is that the legislation and laws of money laundering crimes must be revised and followed up with the necessary decisive, strict and rapid amendments, at least annually

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Design and Anti-Proliferative Evaluation of Triptorelin Conjugated Tris (4-Methoxyphenyl) Methanol Derivatives

Triptorelin, a gonadotropin releasing hormone (GnRH) agonist, is being routinely used in treating patients with advanced symptoms of prostate cancer. The major limitations of triptorelin therapy include its low uptake by the cells, high efflux rate as well as resistance development, all of which significantly abrogate its bio-efficacy. Effectual strategies to increase the cellular uptake of triptorelin are therefore being contemplated to increase the potency of the drug. Modulating the hydrophobicity of the peptide by addition of hydrophobic linkers is an effective approach to this end. In this study, a number of triptorelin conjugates of tris(4-methoxyphenyl) methanol derivatives with optimized hydrophobicity were synthesized by the reaction of 2-substituted methoxy benzenes (e.g. 1-chloro-2-methoxybenzene, 1-bromo-2-methoxybenzene, 1-fluoro-2-methoxybenzene, 1-methyl-2-methylbenzene, 1-methoxy-2-nitrobenzene) and 1,3,5-trioxane followed by conjugation with triptorelin acetate in the presence of HBTU/DIPEA/DIC in moderate yields. The efficacy of synthesized triptorelin conjugates were evaluated using an in vitro lipid peroxidation assay. The derivatives effectively reduced lipid peroxidation which were measured as thiobarbituric reactive substance (TBARS) in a dose- and time-dependent manner following the Fenton\u27s pathway. Overall, TBARS decreased between 20-30% for the treated samples of synthesized conjugates compare to their respective controls. These data establishes in vitro anti-oxidant activities of the triptorelin conjugates of tris(4-methoxyphenyl) methanol derivatives, indicating their potential biological efficacy