Graph Mining for Software Fault Localization: An Edge Ranking based Approach

Fault localization is considered one of the most challenging activities in the software debugging process. It is vital to guarantee software reliability. Hence, there has been a great demand for automated methods that can pinpoint faults for software developers. Various fault localization techniques that are based on graph mining have been proposed in the literature. These techniques rely on detecting discriminative sub-graphs between failing and passing traces. However, these approaches may not be applicable when the fault does not appear in a discriminative pattern. On the other hand, many approaches focus on selecting potentially faulty program components (statements or predicates) and then ranking these components according to their degree of suspiciousness. One of the difficulties encountered by such approaches is to understand the context of fault occurrence. To address these issues, this paper introduces an approach that helps in analyzing the context of execution traces based on control flow graphs. The proposed approach uses the edge-ranking of basic blocks in software programs using Dstar that proved to be more effective than many fault localization techniques. The proposed method helps in detecting some types of faults that could not be previously detected by many other approaches. Using Siemens benchmark, experiments show the effectiveness of the proposed technique compared to some well-known approaches such as Dstar, Tarantula, SOBER, Cause Transition and Liblit05. The percentage of localized faulty versions versus the percentage of code examined is taken as a measure. For instance, when the percentage of examined code is 30%, the proposed technique can localize nearly 81% of the faulty versions, which outperforms the other four techniques

Graph Mining for Software Fault Localization: An Edge Ranking based Approach

Fault localization is considered one of the most challenging activities in the software debugging process. It is vital to guarantee software reliability. Hence, there has been a great demand for automated methods that can pinpoint faults for software developers. Various fault localization techniques that are based on graph mining have been proposed in the literature. These techniques rely on detecting discriminative sub-graphs between failing and passing traces. However, these approaches may not be applicable when the fault does not appear in a discriminative pattern. On the other hand, many approaches focus on selecting potentially faulty program components (statements or predicates) and then ranking these components according to their degree of suspiciousness. One of the difficulties encountered by such approaches is to understand the context of fault occurrence. To address these issues, this paper introduces an approach that helps in analyzing the context of execution traces based on control flow graphs. The proposed approach uses the edge-ranking of basic blocks in software programs using Dstar that proved to be more effective than many fault localization techniques. The proposed method helps in detecting some types of faults that could not be previously detected by many other approaches. Using Siemens benchmark, experiments show the effectiveness of the proposed technique compared to some well-known approaches such as Dstar, Tarantula, SOBER, Cause Transition and Liblit05. The percentage of localized faulty versions versus the percentage of code examined is taken as a measure. For instance, when the percentage of examined code is 30%, the proposed technique can localize nearly 81% of the faulty versions, which outperforms the other four techniques

Total Synthesis and Structure Assignment of the Relacidine Lipopeptide Antibiotics and Preparation of Analogues with Enhanced Stability

Microbial Biotechnolog

Comparative study of the chemical composition and anti-proliferative activities of the aerial parts and roots of Apium graveolens L. (celery) and their biogenic nanoparticles

Apiaceae plants are multipurpose folk remedies and bioactive foods that show a remarkable ability to biosynthesize a large number of secondary metabolites with antitumor and chemopreventive potential. Among the various members of the Apiaceae, celery (Apium graveolens L.) has long been used as a popular edible and medicinal plant owing to its plentiful health benefits and nutraceutical properties; however, the anticancer potential of this important species has been seldom studied, mostly focusing on its seeds. Therefore, this work was designed to delve into the chemical composition and anti-proliferative potential of the total ethanolic extracts of the aerial parts (TEEAGA) and roots (TEEAGR) of A. graveolens var. dulce (Mill.) Pers. as well as their green synthesized silver nanoparticles (AgNPs). In general, both TEEAGA and TEEAGR exhibited moderate to potent inhibitory activities against human liver (HepG-2), colon (Caco-2), and breast (MCF-7) cancer cell lines, with interesting IC50 profiles [(41.37 ± 0.12, 27.65 ± 0.27, and 9.48 ± 0.04 μg/mL) and (11.58 ± 0.02, 7.13 ± 0.03, and 6.58 ± 0.02 μg/mL), respectively] as compared with doxorubicin, while more pronounced anti-proliferative effects were observed for their biogenic AgNPs, which showed IC50 values ranging between 25.41 ± 0.16 and 1.37 ± 0.03 μg/mL. Moreover, HPLC‒HESI‒HRMS-based metabolomics analysis of both extracts showed the presence of a varied group of secondary metabolites, including flavonoids, phenylpropanoids, phthalides, coumarins, and sesquiterpenes that further displayed moderate to promising binding affinities to the active site of cyclin G-associated kinase (GAK), particularly graveobioside A, graveobioside B, and celeroside C, suggesting their possible contribution as GAK modulators to the anti-proliferative potential of celery. These findings can help broaden future research on the utilization of different parts of celery and their NPs as functional foods and medicines in cancer chemoprevention and therapy

Discovery and derivatization of tridecaptin antibiotics with altered host specificity and enhanced bioactivity

The prevalence of multidrug-resistant (MDR) pathogens combined with a decline in antibiotic discovery presents a major challenge for health care. To refill the discovery pipeline, we need to find new ways to uncover new chemical entities. Here, we report the global genome mining-guided discovery of new lipopeptide antibiotics tridecaptin A5 and tridecaptin D, which exhibit unusual bioactivities within their class. The change in the antibacterial spectrum of Oct-TriA5 was explained solely by a Phe to Trp substitution as compared to Oct-TriA1, while Oct-TriD contained 6 substitutions. Metabolomic analysis of producer Paenibacillus sp. JJ-21 validated the predicted amino acid sequence of tridecaptin A5. Screening of tridecaptin analogues substituted at position 9 identified Oct-His9 as a potent congener with exceptional efficacy against Pseudomonas aeruginosa and reduced hemolytic and cytotoxic properties. Our work highlights the promise of tridecaptin analogues to combat MDR pathogens.Microbial Biotechnolog

Taxonomic and metabolic diversity of Actinomycetota isolated from faeces of a 28,000‐year‐old mammoth

Ancient environmental samples, including permafrost soils and frozen animal remains, represent an archive with microbial communities that have barely been explored. This yet unexplored microbial world is a genetic resource that may provide us with new evolutionary insights into recent genomic changes, as well as novel metabolic pathways and chemistry. Here, we describe Actinomycetota Micromonospora, Oerskovia, Saccharopolyspora, Sanguibacter and Streptomyces species were successfully revived and their genome sequences resolved. Surprisingly, the genomes of these bacteria from an ancient source show a large phylogenetic distance to known strains and harbour many novel biosynthetic gene clusters that may well represent uncharacterised biosynthetic potential. Metabolic profiles of the strains display the production of known molecules like antimycin, conglobatin and macrotetrolides, but the majority of the mass features could not be dereplicated. Our work provides insights into Actinomycetota isolated from an ancient source, yielding unexplored genomic information that is not yet present in current databases.Microbial Biotechnolog

Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome

Microorganisms living inside plants can promote plant growth and health, but their genomic and functional diversity remain largely elusive. Here, metagenomics and network inference show that fungal infection of plant roots enriched for Chitinophagaceae and Flavobacteriaceae in the root endosphere and for chitinase genes and various unknown biosynthetic gene clusters encoding the production of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs). After strain-level genome reconstruction, a consortium of Chitinophaga and Flavobacterium was designed that consistently suppressed fungal root disease. Site-directed mutagenesis then revealed that a previously unidentified NRPS-PKS gene cluster from Flavobacterium was essential for disease suppression by the endophytic consortium. Our results highlight that endophytic root microbiomes harbor a wealth of as yet unknown functional traits that, in concert, can protect the plant inside out.Microbial Biotechnolog

The Cholecystectomy As A Day Case (CAAD) score: a validated score of preoperative predictors of successful day-case cholecystectomy using the CholeS data set

Background: Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods: Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results: Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions: The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century