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: Peptides are small molecules composed of amino acids linked together by peptide bonds. The targeted action of these peptides along with their magnificent ability to reach locations in body that are complicated to access, is being considered of tremendous potential in disease modifying therapies. Synthetic as well as natural peptides like Carnosine are currently under research for treatment of neurodegenerative disorders (NDDs). Peptide based vaccines are currently under immense research for diseases like dementia. Toxicity of peptide-based drugs tfigureowards eukaryotic cells due to their increased haemolytic activity is of major concern and this is being tackled by introducing modifications into the peptide structure. Some crucial peptide inhibitors currently in use for neurodegenerative disorders include Aβ (16-20) KLVFF for Alzheimer’s disease, NAPVSIPQ (NAP) for Parkinson’s disease, towards eukaryotic cells Vasoactive Intestinal Peptides (VIP) for Huntington’s disease, Polyglutamine Binding Peptide-1(QBP1) for Dentatorubral-paiidoluysial atrophy (DRPLA). Certain peptides are involved in inhibition of mitochondrial permeability transition (MPT) that plays a prominent part in the materialization of neurodegenerative diseases, one such example of peptides being Ba-V which is obtained from Bothrops atrox snake venom. New therapeutic peptides are being identified using bioinformatics tools like high throughput screening (HTS). These tools are being used to explore the selectivity, stability, extent of immune response and toxic side effects of peptides. Apart from neurodegenerative diseases, the potential of bioactive peptides is also being tested against cancer, diabetes and microbes. This review focuses on the recent advances in peptide therapeutics and novel peptides discovered for treatment of the NDs.

During the software development process, numerous bugs are reported daily in the software bug repositories. Bug triage assigned these bugs to the most relevant and expert developer for resolution. Moreover, assigning bugs to an incompetent or an over‐engaged developer causes repeated reassignment to other developers until it is resolved. This problem can be solved by devising a triage process that assigns bugs to not only expert developers but also to those who are either under‐engaged or reasonably engaged but are not over‐engaged in work. This paper has designed and implemented work engagement sensitive bug triage that resolves the issue of assigning bugs to developers considering their due work engagement, expertise as well as the current state of activity. For this purpose, a developer profile is built by using metrics to generate three types of scores: technical skill, work engagement and work experience. Metadata features like developer‐name, email, developer‐work‐experience in bug resolution, last and present‐work‐activity, timestamp, component and priority are used for it. A multi‐criteria‐based Henry–Garret technique is used to generate a single ranked list of developers from three ranked lists. The performance of the proposed approach is evaluated on four large OOS projects: Mozilla, Eclipse, Netbeans, and Open Office covering 895,439 bug reports accumulated for 33 years of development. The overall system accuracy of the proposed triage using all four datasets is 91.96 ± 0.05% which is 5.87% better than previously published work. The proposed method is achieved up to 90.30 ± 0.05 and 97.1 ± 0.05 MRR and accuracy of reassignment respectively that indicates how significantly it re‐assigns the bug to the relevant developers. The results demonstrate improvement in the accuracy of software‐bugs triaging as well as a reduction in the probability of bug‐tossing.

This paper presents a comprehensive survey of bug triaging approaches in three classes namely machine learning based, meta-data based and profile based. All approaches under three categories are critically compared and some potential future directions and challenges are reported. Findings from the survey show that there is a lot of scope to work in cold-start problem, developer- profiling, load balancing, and reopened bug analysis.