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Improving Software Quality Prediction Using Intelligent Computing Techniques

Thesis Info

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External Link

Author

Rana, Zeeshan Ali

Program

PhD

Institute

Lahore University of Management Sciences

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

Fri May 20 00:00:00 PKT 2016

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/9229/1/Zeeshan_Ali_Rana_Computer_Science_2016_HSR_LUMS_Lahore_07.09.2016.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727775639

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Software Quality Prediction (SQP) has been an area of interest for the last four decades. The aim of quality prediction has been to identify the defect prone modules in software. With the help of SQP the defect prone modules can be identified and thus improved at early stages of software development. SQP is done using models that predict the defect prone modules. These prediction are based on software metrics. Software metrics and defect related information is recorded in form of datasets. These defect datasets contain instances of defect prone and not-defect prone modules. Major motive behind quality prediction is to identify defect prone modules correctly in early phases of development. Imbalanced datasets and late predictions are problems that affect this motive. In most of the datasets, the number of instances of not-defect prone modules dominate the number of instances of defect prone modules. This creates imbalance in the datasets. The defect prone modules are not identified effectively due to the imbalance. Effectively predicting defect prone modules and achieving high Recall using the public datasets becomes a challenging task. Predictions based on code metrics are considered late. Majority of the metrics in the datasets are code metrics which means that accurate predictions can be made once code metrics become available. Another issue in the domain of software quality and metrics is that software metrics used so far have inconsistent nomenclature which makes it difficult to study certain software metrics. In this thesis an association mining (AM) based approach is proposed that improves prediction of defect prone modules. The proposed approach modifies the data in a manner that a prediction model learns defect prone modules better even if there are few instances of defect prone modules. We use Recall to measure performance of the model developed after proposed preprocessing. The issue of late predictions has been handled by using a model which can work with imprecise values of software metrics. This thesis proposes a Fuzzy Inference System (FIS) based model that helps predict defect prone modules when exact values of code metrics are not available. To handle the issue of inconsistent nomenclature this thesis provides a unification and categorization framework that works on the principle of chronological use of metric names. The framework has been used to identify same metrics with different names as well as different metrics with same name. The association mining based approach has been tested using public datasets and Naive Bayes classifier. Naive Bayes classifier is the simplest and is considered as one of the best performers. The proposed approach has increased Recall of the Naive Bayes classifier upto 40%. Performance of the proposed Fuzzy Inference System (FIS), used to handle the issue of late predictions, has been compared with models like neural networks, classification trees, and linear regression based classifiers. The FIS model has performed as good as other models. Upto 10% improvement in Recall has been observed in case of FIS model. The nomenclature unification of approximately 140 metrics has been done using the proposed unification framework. Out of these 140 metrics approximately 6% different metrics have been used with same name in literature. Their naming issues have been resolved based on the chronological use of the names. Achieving better Recall using the proposed approach can help avoid costs incurred due to identification of a defect prone module late in software lifecycle when cost of fixing defects becomes higher. The proposed FIS model can be used for earlier rough estimates initially. Later, better and accurate estimates can be made when code metrics become available.
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میری بات

میری بات

                                                                                ڈاکٹر محمد ایوب

کتاب بینی کا شوق کالج کے زمانے سے ہی شروع ہو گیا تھا۔ کیونکہ کالج کے مقابلہ مضمون نویسی بعنوان( پاکستان میں مرغی اور انڈے کی پیداوار) میں حصہ لینے کے لیے تیاری کے سلسلے میں زرعی یونیورسٹی فیصل آباد جاکر کافی کتب پڑھنے کا موقع ملا۔خدائے وحدہ لاشریک کا کروڑہا بار شکر ہے جس کی کرم نوازی سے مجھے اس مقابلہ مضمون نویسی میں پہلے انعام کا حقدار قرار دیا گیا۔ اس انعام سے حوصلہ پا کر میں اکثر چھوٹے چھوٹے مضامین لکھتا رہتا تھا۔ کیونکہ بنیادی طور پر میں پنجابی زبان و ادب کا استاد اور طالب علم ہوں اس لئے اردو زبان و ادب کا مطالعہ واجبی سا رہا۔ میں 1988 جب فرائض منصبی کی ادائیگی کے لئے گورنمنٹ کالج بہاولنگر گیا تو وہاں کی ادبی فضا نے اردو زبان و ادب کے مطالعہ کا موقع فراہم کیا۔ میرے کالج کے ساتھی پروفیسر راؤ مختار شعبہ اردو کی شاعری کی کتاب پر پہلا تنقیدی مضمون اردو میں لکھا جو بعد میں مقامی اخبار میں بھی شائع ہوا۔ پروفیسر موصوف کی حوصلہ افزائی سے اردو لکھنے کی تحریک پیدا ہوئی۔ اب تک بہت سے تنقیدی و تحقیقی مضمون لکھ چکا ہوں۔ جن میں سے تین مضامین اٹلی اور آسٹریلیا سے نکلنے والے اردو جرائد میں میں شائع ہو چکے ہیں۔ کیونکہ دوست اکثر اپنی اردو تخلیقات بھیجتے رہتے ہیں اس لئے ان کو پڑھنے کے بعد جو کچھ محسوس کیا اسے الفاظ کے پیراہن میں آپ کے سامنے رکھ دیا  ہے۔

کتابی صورت اردو میں میری یہ پہلی کوشش ہے۔ میرا اردو کا ذخیرہ الفاظ بھی زیادہ نہیں جس کی وجہ سے میری تمام تحریروں میں آپ کو بے شمار غلطیاں نظر آئیں گی۔ میری خواہش ہوگی کہ...

Concept of Islamic Leadership in Syed Muhammad Naquib Al-Attas’s Philosophy

Islamic leadership is defined as a divine trust (amanah) from Allah, based on the Tauhidic paradigm of oneness of Allah that is focusing to serve HIM as HIS servant, while at the same time be the servant of Allah, perform the role of Khalefah (vicegerent) of Allah fully adheres to the Sunnah central to Islamic personality, characteristics and aklaq (Islamic moral and ethical) that was exemplified by the prophet (s.a.w), leading followers to the organization goals and to the straight path of the success in the Hereafter. It is based on this adopted definition that the paper tries to look into the notion from perspective of a Malaysian Muslim Philosopher to the core, Syed Muhammad Naquib Al-Attas, who believes in delivering amanah given to him, and at the same time perform the role of vicegerent of Allah. He suggests that lack of good leaders or rise of unqualified and false ones is one of the major problems of Ummah. Content analysis approach is engaged on both primary and secondary data collected. That is to say, it is a qualitative research in nature. The finding shows that the basis of Al-Attas’s concept of leadership is entrenched in Al-Qur’an and the tradition of the prophet in addition to his deep understanding on the Islamic Sciences such as Islamic theology, philosophy, and metaphysis and so on.

Studies on the Development of a Consortium of Fungi and Bacteria for Efficient Composting

Composting is the microbial degradation of organic waste material into a useful product that can provide nutrient to plants. Composts containing biocontrol agents can be useful in reducing the use of chemical fertilizer and pesticides since these composts not only increase the plant growth but also provide better suppression in root colonization by soil borne pathogens. During the present studies, microorganisms isolated from various composts were evaluated for their enzymatic and biocontrol activities in order to develop consortia of microorganisms that can reduce the time required for composting, and also provide protection to roots against soil-borne pathogens. A total number of 15 bacteria including six mesophilic, five thermotolerant and four thermophilic, and 44 fungi including 13 mesophilic, 11 thermotolerant and 20 thermophilic species isolated from cow dung, goat pellet, poultry manure and plant debris. Thermophilic fungi viz., Annelophora africana, Conidiobolus thermophilus and Haplotrichum croceum have been reported for the first time from Pakistan. The highest population of thermophilic microorganisms was observed in cow dung followed by goat pellet poultry manure and plant debris. The highest population of thermotolerant microorganisms was recorded from goat pellet followed by poultry manure, cow dung and plant debris. Similarly, the x highest population of mesophilic microorganisms was in plant debris followed by poultry manure, goat pellet and cow dung. The growth of thermophilic fungi was better on yeast starch agar as compared to potato sucrose agar medium. Similarly, the thermotolerant fungi showed better growth on PSA. Among the mesophilic fungi, Aspergillus flavus, Penicillium dipodomyis, Stachybotrys chartarum and Syncephalastrum racemosum showed better growth on YSA medium, PSA was more suitable for the remaining mesophilic fungi. During the present study, 33 fungi and 7 bacteria exhibited amylase activity. Of these, no previous report on amylase activity of Mucor fragilis, Aspergillus floccosus, Aspergillus nidulans (Teleomorph) and Aspergillus rugulosus is available. Similarly, 40 fungi and 6 bacteria showed cellulase activity that included Annelophora africana, Haplotrichum croceum, Aspergillus floccosus, Trichoderma virens and Micrococcus varians as now sources for cullulase enzymes. A total of 17 fungi and 7 bacteria showed chitinase activity and 20 fungi and 5 bacteria showed pectinase activity. No previous report on pectinase activity of Aspergillus rugulosus and Micrococcus varians is available. Furthermore 27 fungi and 6 bacteria showed protease activity. xi In vitro compatibility interactions showed that Acremonium thermophilum, Annelophora africana and Haplotrichum croceum were compatible with 10 fungi. Similarly, Bacillus cerreus and B. megaterium were compatible with 11 different fungi. Individual inoculations of the 44 fungi and15 bacteria into the composting materials showed that rate of degradation of grass clipping was the highest, followed by fruit waste, leave and wheat straw in descending order. The mesophilic microorganisms showed no composting at 50°C but composting activity was very good in thermopole boxes. The thermotolerant microorganisms were less effective at 50°C but in thermopole boxes these activities was very good. The thermophilic microorganisms were equally effective both at 50°C and in thermopole boxes. During single inoculations, the efficient thermophilic microorganisms took 7-8 days to completely degrade the grass clippings into compost. The time taken by the efficient thermotolerant and mesophilic microorganisms was 8 and 12 days, respectively. Combined use of two microorganisms degraded the grass clippings within five to eight days. Combinations of Isaria fumosorosea with Thermomyces lanuginosus, and Bacillus licheniformis with Aureobasidium pullulans were the most efficient. Based on the compatibility between the different microorganisms, three consortia with 17 members in each, developed to evaluate their xii composting ability. Consortium-1 showed the most efficient composting followed by consortia 2 and 3. The populations of the microorganisms were higher in compost developed by consortium-1 followed by consortia 2 and 3. The population densities in all the composts increased after four days whereas after 14 days, the populations of the microorganisms reduced and no bad smell was observed. It indicated the complete degradation of grass clippings. In case of the control, the bad smell continued even after 14 days, that indicates slow degradation. During pit composting, the initial average temperature of the composting material was 20°C. Only the mesophilic microbes isolated during the initial three weeks. The thermotolerant microbes thrived during 4th and 5th weeks. Thermophilic microbes grew from 6th to 8th week and finally disappeared. The peak heating phases (50oC) was at 8th week of composting, and during phase, the highest numbers of thermophilic microorganisms were isolated. Thereafter, the temperature gradually reduced to 40°C by the 9th and 10th weeks; the thermotolerant microbes reappear and later mesophilic microbes re-colonized the compost at 11th and 12th weeks when temperature reduced to 28°C. In pot and field experiments, composts developed by the consortia of microorganisms increased plant growth and reduced root colonization by soil borne pathogen viz., Fusarium solani, Macrophomina phaseolina, xiii Pythium aphanidermatum, Rhizoctonia solani and Sclerotium rolfsii. Use of consortia composts @ 10% w/w gave the highest increase in growth parameters followed by 5% and 1% treatments. Compost developed by consortium-1 was more effective as compared to consortia 2 and 3; consortium-3 compost being the least effective. The efficacy of the composts was greater in pot experiment as compared to field experiments. Plants treated with consortium-1 compost at 5% and 10% showed flowering within one month. Plants treated with consortia 2 and 3 composts flowered after one month only in 10% treatments. No flowering observed in one month old control plants. This early flowering occurred in pot experiments but not in field experiments. In field experiments, soil amendment with consortia composts showed persistence of the efficacy. Mungbean plants grown in the same micro plots without further addition of the composts showed a slight reduction in plant growth promotion and suppression in root colonization by soil-borne pathogens. Planting for the third time without adding consortia composts resulted in further reduction in the efficacy of the compost. However, the plant growth and suppression in root colonization was still better than that in control plants.