Mathematical Modeling of Software Bug Complexity

During testing of software, most of the bugs lying dormant in the software gets uncovered once the test cases are executed. Different bugs may take different amounts of effort and expertise for their removal. To understand the complexity of bugs from a developer‟s perspective, researchers have developed different mathematical models. Software consists of two types of bugs, dependent and independent. Dependent bugs are those whose removal depends upon the removal of some other bugs on which it is dependent. Dependency of bugs also makes the bug complex and bugs will take more time during fixing. Different debugging time lags functions have been taken to model different complexity of bugs. The aim of this paper is to study the bugs of different complexity. The complexity of bugs has been also modeled using dependency concept. Testing effort dependent bug complexity model using fault dependency has been also discussed. We also feel that that more complex bug will take more time and less complex bug will take less time during fixing. During removal of bugs, the removal team gets more familiar with the code during the fixing. The learning effect during testing has been incorporated using logistic removal rate. The models are validated based on different comparison criteria namely MSE, R2 , Bias, Variation and Root mean squared error.Keywords/Index Terms: Non-homogeneous Poisson process, bug complexity, bugs types

Draft genome sequence of Sclerospora graminicola, the pearl millet downy mildew pathogen:Genome sequence of pearl millet downy mildew pathogen

Sclerospora graminicola pathogen is one of the most important biotic production constraints of pearl millet worldwide. We report a de novo whole genome assembly and analysis of pathotype 1. The draft genome assembly contained 299,901,251 bp with 65,404 genes. Pearl millet [Pennisetum glaucum (L.) R. Br.], is an important crop of the semi-arid and arid regions of the world. It is capable of growing in harsh and marginal environments with highest degree of tolerance to drought and heat among cereals (1). Downy mildew is the most devastating disease of pearl millet caused by Sclerospora graminicola (sacc. Schroet), particularly on genetically uniform hybrids. Estimated annual grain yield loss due to downy mildew is approximately 10?80 % (2-7). Pathotype 1 has been reported to be the highly virulent pathotype of Sclerospora graminicola in India (8). We report a de novo whole genome assembly and analysis of Sclerospora graminicola pathotype 1 from India. A susceptible pearl millet genotype Tift 23D2B1P1-P5 was used for obtaining single-zoospore isolates from the original oosporic sample. The library for whole genome sequencing was prepared according to the instructions by NEB ultra DNA library kit for Illumina (New England Biolabs, USA). The libraries were normalised, pooled and sequenced on Illumina HiSeq 2500 (Illumina Inc., San Diego, CA, USA) platform at 2 x100 bp length. Mate pair (MP) libraries were prepared using the Nextera mate pair library preparation kit (Illumina Inc., USA). 1 ?g of Genomic DNA was subject to tagmentation and was followed by strand displacement. Size selection tagmented/strand displaced DNA was carried out using AmpureXP beads. The libraries were validated using an Agilent Bioanalyser using DNA HS chip. The libraries were normalised, pooled and sequenced on Illumina MiSeq (Illumina Inc., USA) platform at 2 x300 bp length. The whole genome sequencing was performed by sequencing of 7.38 Gb with 73,889,924 paired end reads from paired end library, and 1.15 Gb with 3,851,788 reads from mate pair library generated from Illumina HiSeq2500 and Illumina MiSeq, respectively. The sequences were assembled using various assemblers like ABySS, MaSuRCA, Velvet, SOAPdenovo2, and ALLPATHS-LG. The assembly generated by MaSuRCA (9) algorithm was observed superior over other algorithms and hence used for scaffolding using SSPACE. Assembled draft genome sequence of S. graminicola pathotype 1 was 299,901,251 bp long, with a 47.2 % GC content consisting of 26,786 scaffolds with N50 of 17,909 bp with longest scaffold size of 238,843 bp. The overall coverage was 40X. The draft genome sequence was used for gene prediction using AUGUSTUS. The completeness of the assembly was investigated using CEGMA and revealed 92.74% proteins completely present and 95.56% proteins partially present, while BUSCO fungal dataset indicated 64.9% complete, 12.4% fragmented, 22.7% missing out of 290 BUSCO groups. A total of 52,285 predicted genes were annotated using BLASTX and 38,120 genes were observed with significant BLASTX match. Repetitive element analysis in the assembly revealed 8,196 simple repeats, 1,058 low complexity repeats and 5,562 dinucleotide to hexanucleotide microsatellite repeats.publishersversionPeer reviewe

Utilization of Agro-food By-products for Gluconic Acid Production by <i>Aspergillus niger </i>ORS-4 Under Surface Culture Cultivation

356-360Among the seven isolated microbial strains from dumping sites of the sugarcane industry waste, a potent fungal strain Aspergillus niger ORS-4 was selected, th at gave 48 g/L of gluconic acid with 74 per cent yield when glucose was used as the carbon source. Starch hydrolysate, molasses and the banana must were evaluated as the cheaper carbohydrate sources for gluconic acid production by A niger ORS-4 in surface culture fermentation process. The banana must was found to be a better source with significant gluconic acid production (39.6 g/L, 40 per cent yield ) and 12 d incubation. The untreated sugarcane molasses gave marginal production of gluconic acid (2.4 g/L), however, the production increased significantly(34.6 g/L, yield 38.5 per cent) after the molasses were subjected to the hexacynoferrate (HCF) treatment. Starch hydrolysate on the other hand, resulted into comparative production (30.2 g/L, yield 35.9 per cent) but lower than that obtained with HCF treated molasses, whereas the acid production was low ( 10 g/L) with unhydrolyzed starch. Gluconic acid production from these substrates was comparable to that obtained with glucose

<span style="font-size:14.0pt;line-height: 115%;font-family:"Times New Roman";mso-fareast-font-family:"Times New Roman"; color:black;mso-ansi-language:EN-IN;mso-fareast-language:EN-IN;mso-bidi-language: HI" lang="EN-IN">Optimisation of fermentation conditions for gluconic acid production by a mutant of <i>Aspergillus niger</i></span>

1136-1143<span style="font-size:14.0pt;line-height: 115%;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" color:black;mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:="" hi"="" lang="EN-IN">Aspergillus niger <span style="font-size:14.0pt;line-height:115%; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" color:black;mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:="" hi"="" lang="EN-IN">ORS-4, isolated from the sugarcane industry waste materials was found to produce notable level of gluconic acid. From this strain, a mutant Aspergillus niger ORS-4.410 having remarkable increase in gluconic acid production was isolated and compared for fermentation properties. Among the various substrates used, glucose resulted into maximum production of gluconic acid (78.04 g/L). 12% concentration led to maximum production. Effect of spore age and inoculums level on fermentation indicated an inoculum level of 2% of the 4-7 days old spores were best suited for gluconic acid production. Maximum gluconate production could be achieved after 10-12 days of the fermentation at 30°C and at a pH of 5.5. Kinetic analysis of production indicated that growth of the mutant was favoured during initial stages of the fermentation (4-8 days) and production increased during the subsequent 8- 12 days of the fermentation. CaCO3 and varying concentrations of different nutrients affected the production of gluconic acid. Analysis of variance for the factors evaluated the significant difference in the production levels.</span

<span style="font-size: 21.0pt;mso-bidi-font-size:14.0pt;font-family:"Times New Roman","serif"">Gluconic acid production by <i>Aspergillus niger </i>mutant ORS-4.410 in submerged and solid state surface fermentation </span>

691-696Aspergillus niger <span style="font-size:15.0pt;mso-bidi-font-size:8.0pt; font-family:" times="" new="" roman","serif""="">ORS-4.410, a mutant of Aspergillus niger <span style="font-size:15.0pt;mso-bidi-font-size:8.0pt; font-family:" times="" new="" roman","serif""="">ORS-4 was produced by repeated irradiation with UV rays. Treatments with chemical mutagnes also resulted into mutant strains. The mutants differed from the parent strain morphologically and in gluconic acid production. The relationship between UV treatment dosage, conidial survival and frequency of mutation showed the maximum frequency of positive mutants (25%) was obtained along with a conidial survival of 59% after second stage of UV irradiation. Comparison of gluconic acid production of the parent and mutant ORS-4.410 strain showed a significant increase in gluconic acid production that was 87% higher than the wild type strain. ORS-4.410 strain when transferred every 15 days and monitored for gluconic acid levels for a total period of ten months appeared stable. Mutant ORS-4.410 at 12% substrate concentration resulted into significantly higher i.e. 85-87 and 94-97% yields of gluconic acid under submerged and solid state surface conditions respectively. Further increase in substrate concentration appeared inhibitory. Maximum yield of gluconic acid was obtained after 6 days under submerged condition and decreased on further cultivation. Solid state surface culture condition on the other hand resulted into higher yield after 12 clays of cultivation and similar levels of yields continued thereafter. </span

Isolation and Characterization of a Potent Fungal Strain <i>Aspergillus niger ORS-4 </i>for Gluconic Acid Production

594-600A fungal strain of A. niger ORS-4 was isolated from soil samples from sites where the waste of the sugarcane industry is being decomposed, The isolated fungal strain on analysis showed the capacity to produce gluconic acid. Under controlled conditions, substantial amounts of gluconic acid (yield up to 89 per cent) resulted from submerged culture fermentation between 28-32°C following 144 h of incubation. Among the various sugars used, glucose and the fructose were found to be suitable carbon sources. Further, the strain could utilize glucose in concentrations varying from 10-25 per cent for maximal gluconate production during fermentation. Inorganic salts were found to improve gluconic acid production when used in trace amounts but had a negative effect at concentration greater than 0.2 per cent. It is suggested that A, niger ORS-4 has potentials that can be exploited for commercial production of gluconic acid

Mathematical Modeling of Software Bug Complexity

During testing of software, most of the bugs lying dormant in the software gets uncovered once the test cases are executed. Different bugs may take different amounts of effort and expertise for their removal. To understand the complexity of bugs from a developer‟s perspective, researchers have developed different mathematical models. Software consists of two types of bugs, dependent and independent. Dependent bugs are those whose removal depends upon the removal of some other bugs on which it is dependent. Dependency of bugs also makes the bug complex and bugs will take more time during fixing. Different debugging time lags functions have been taken to model different complexity of bugs. The aim of this paper is to study the bugs of different complexity. The complexity of bugs has been also modeled using dependency concept. Testing effort dependent bug complexity model using fault dependency has been also discussed. We also feel that that more complex bug will take more time and less complex bug will take less time during fixing. During removal of bugs, the removal team gets more familiar with the code during the fixing. The learning effect during testing has been incorporated using logistic removal rate. The models are validated based on different comparison criteria namely MSE, R2 , Bias, Variation and Root mean squared error.Keywords/Index Terms: Non-homogeneous Poisson process, bug complexity, bugs types

Characterisation of Natural Resources of Deolikhan Water Shed

31-37Presently the country is facing with the problem of population explosion. In order to meet the ever-increasing demands of increasing population, in both mountainous and plain areas, there is an urgent need to increase agricultural production as well as productivity. With the evolution of the process of planning in the fragile (mountainous) ecosystem, currently the emphasis has been on decemralized planning to smaller area units (i.e. micro - watershed, district or below). This is to facilitate developmental strategies that are sustainable, area-specific and take into account the local needs and the problems. Interrelation and inter-dependence between various sectors make such decentralized planning of micro level a complex and information sensitive task, involving a large matrix of sectoral data on the local natural resources and requiring appropriate methodologies for data collection, analysis and processing. The present study demonstrates the collection, processing and application of this local level data on natural resource for understanding the land and water related problems of a representative (Deolikhan) micro-watershed in Almora district of Uttaranchal state. For this, land use related information comprising of present land use, land management practices, cropping pattern, irrigation practices, fertilizer applications and their use efficiency etc along with the soil and hydrologic data were collected from the test site. The land use data was obtained by means of a primary survey of the local farmers through a questionnaire while the hydrologic data was obtained, at regular time-intervals, through in-situ gauging stations. Besides this, soil samples collected from different sampling sites within the test watershed were analyzed and digitized in Arc/ Info GIS package for obtaining soil property based maps of the test area. The above effort could thus very lucidly demonstrate the use of such studies in proposing developmental plans and effective solutions to the local level problems by the agricultural specialists and decision or policy makers. </span