Bipolar Disorder Symptoms, Effects, Diagnosis and Treatment

Table of Contents Symptoms Effects of Bipolar Disorder Other Diseases That Co-Exist With Bipolar Risk Factors for Bipolar Diagnosis of Bipolar Treatment of Bipolar References The other name for bipolar disorder is Manic-depressive illness. This disease specifically causes the patient to experience extra ordinary changes in mood, strength, levels of concentration, and the ability to execute daily tasks (Kato, 2007). Unless the disease has been diagnosed, it is difficult to identify the symptoms.Advertising We will write a custom research paper sample on Bipolar Disorder: Symptoms, Effects, Diagnosis and Treatment specifically for you for only $16.05 $11/page Learn More Therefore, the infected person is constantly in conflicts with the people who interact with him/her. For instance, such persons can barely be in a stable relationship for a considerable period. Moreover, they seem to be in a habit of engaging in intense arguments at their places of work . This is probably because they cannot fully concentrate on what they are doing at a particular time. Symptoms Bipolar disorder is common in persons under the age of 25 years. However, there are situations that have been reported involving patients who are in their sun set years and others who are considered too young to contract this condition such as children below the age of ten years (Miklowitz, 2008). Bipolar disorder is considered a long-term condition that often begins gradually because it can take up to 10 years before the symptoms are visible. Usually, symptoms are only uncovered through diagnosis. This implies that bipolar disorder falls into the category of diseases such as diabetes and heart condition, which need to be managed throughout the affected person’s lifetime (Serretti Mandelli, 2008). Bipolar patients experience irregular mood swings that range between exaggerated amusement and sadness (Srivastava Ketter, 2010). This means that the patient can be extre mely happy in one minute and the next minute the person looks dull. Such people are easily irritated and hence, should be handled with a lot of care and understanding. These mood swings are not influenced by the events that are going on in their surroundings because their sadness or joy cannot be linked to anything. For instance, under normal circumstances, people laugh because something funny has been done or said, but to bipolar patients, joy and sadness alternate without a justifiable reason (Miklowitz, 2008). Likewise, persons suffering from bipolar disorder tend to speak very fast during conversations like there is a matter of urgency. When they embark on making a statement, they hardly finish putting their point across because they encounter numerous distractions in their minds that cause them to divert from the topic of discussion (Kieseppa et al., 2004).Advertising Looking for research paper on health medicine? Let's see if we can help you! Get your first paper with 15 % OFF Learn More At the end of their conversations, there are so many half-complete stories. Moreover, they have a habit of setting unrealistic goals. This is caused by their thought of having unique abilities and hence they feel they can achieve goals that are deemed unachievable. This overconfidence causes them to handle more tasks beyond their capacity, such as assuming more roles at a go (Kato, 2007). Furthermore, bipolar patients experience lack of sleep probably because they work for long hours. Nonetheless, they sleep for few hours due to the restlessness that keeps them up all night. Besides, they loose interest in activities that they previously enjoyed and in most occasions, they seem to be carried away due to their low level of concentration. They are quite forgetful and hence tend to have varied opinion or fail to stick to an agreement’s terms due to their poor memory (Miklowitz, 2008). For instance, the infected person can schedule a meeting and later fa il to avail him/herself without a good reason. Effects of Bipolar Disorder If a person suffering from bipolar is not diagnosed and the illness persists for a long time, the effects worsen with time. According to Miklowitz (2008), â€Å"The behavioral and emotional experiences of the person with bipolar disorder affect everyone – the patient’s parents, spouse, siblings, and children† (p. 5). A bipolar individual is prone to getting into fights and arguments with friends and relatives including their spouse. In the end, their family ties are disintegrated. Similarly, their employers are hardly satisfied with their performance because they make avoidable mistakes, which may lead to dismissals. This turn of events makes them to resort to abusing substances such as alcohol and other related drugs (Lam, Wright, Smith, 2004). They abuse drugs in an attempt to divert their attention. They also experience hallucinations. Furthermore, patients who suffer from this condit ion are known to have thoughts of ending their own lives and hence, they are likely to commit suicide. Other Diseases That Co-Exist With Bipolar Bipolar disorder can go for a long time without being noticed because it exhibits symptoms common to related conditions. These illnesses include post-traumatic stress disorder (PTSD), social Phobia and attention deï ¬ cit hyperactivity disorder (ADHD). Lack of concentration and restlessness are very common in these diseases and hence one may be confused for the other. When this happens, the medical expert ends up prescribing treatment for the wrong ailment and thus the symptoms persist (Srivastava Ketter, 2010).Advertising We will write a custom research paper sample on Bipolar Disorder: Symptoms, Effects, Diagnosis and Treatment specifically for you for only $16.05 $11/page Learn More Additionally, bipolar patients are prone to contracting thyroid illness, migraine headaches, heart disorders, diabetes and o besity. It is therefore advisable for patients to consult the doctor if their treatment is not making any positive progress. This will cause the doctor to carry out a thorough diagnosis that could probably unveil other underlying illnesses that could be hindering the effective treatment of bipolar (Miklowitz, 2008). Risk Factors for Bipolar There is no exact cause of bipolar disorder. However, several issues have been identified as major contributors to contracting the ailment. The generic background of an individual has been sighted as the major contributing factor. This implies that bipolar disorder is a hereditary ailment because it can be passed on from parents to their children (Mansell Pedley, 2008). People who hail from family backgrounds that have had a history of being affected by this disease are more likely to contract the ailment than their counterparts whose families have never had any brain disorder related to bipolar. Twins are also prone to contracting bipolar, but in most cases, its only one child among the pair that tests positive to bipolar diagnosis. This does not mean that the other child will also contract bipolar disease because each of them exists as an independent entity (Serretti Mandelli, 2010). Diagnosis of Bipolar Unlike other illnesses, bipolar cannot be detected through evaluation of blood samples or brain screening. However, these tests can be carried out to unearth other underlying illnesses that could hinder effective treatment of bipolar. The condition is therefore best diagnosed through physical observation coupled with thorough interrogation of the patient (Miklowitz, 2008). Psychiatrists are in a much better position to handle conditions like bipolar due to their expertise. The medical health practitioner should seek to obtain adequate information regarding the patient’s family history regarding bipolar disorder. If the condition of the patient does not favor interrogation, the practitioner should consult a close relative to the affected person such as brothers, sisters and spouse such as wife or husband. Previous medical records can also be referred to while probing the health history of the patient (Kieseppa et al., 2004). Treatment of Bipolar Bipolar is not curable, but it is manageable. People who stick to the prescribed medication are able to regulate mood swings and hence lead healthy productive lives (Serretti Mandelli, 2008). It is important to note that bipolar is a condition that keeps on recurring and hence the patient has to be on medication for the rest of his/her life. The medicine for treating bipolar is usually prescribed by licensed medical experts; it cannot be purchased without written prescription. Among the drugs that are used to treat bipolar include Lithium, Valproic acid, Anticonvulsant lamotrigine, Neurontin, and Topamax (Miklowitz, 2008).Advertising Looking for research paper on health medicine? Let's see if we can help you! Get your first paper with 15% OFF Learn More Besides medication, bipolar can be treated through psychotherapy. In this form of treatment, the patient is offered emotional support through regular conversations. The patient is helped to stop his/her destructive habits by being made to understand the consequences of his/her actions. Alternatively, the therapy can take place at the family level where the family members counsel one of their own. However, Miklowitz (2008) argue that: A close working relationship between the bipolar patient and his or her family members can not only address the multiple psychological problems that emerge in the context of this disorder, but can also facilitate the patient’s willingness to follow a prescribed medication regimen. (p. 6) Similarly, people suffering from bipolar can undergo collective counseling on the effects of bipolar disorder. Moreover, psycho-education is reserved for people who suffer from bipolar disorder. The training empowers them to be in a position to manage this lifeti me condition, and seek medical attention while there is still enough time. This reduces the impact of the disease on the patients (Kato, 2007). References Kato, T. (2007). Molecular genetics of bipolar disorder and depression. Psychiatry and Clinical Neurosciences, 61(1), 3-19. Kieseppa, T., et al. (2004). High concordance of bipolar I disorder in a nationwide sample of twins. American Journal of Psychiatry, 161(10), 1814-1821. Lam, D., Wright, K., Smith, N. (2004). Dysfunctional assumptions in bipolar disorder. Journal of Affective Disorders, 79(1-3), 193-199. Mansell, W. Pedley, R. (2008). The ascent into mania: A review of psychological processes associated with the development of manic symptoms. Clinical Psychology Review, 28(3), 494-520. Miklowitz, D.J. (2008). Bipolar disorder: A family-focused treatment approach (2nd ed.). New York, NY: Guilford Press. Serretti, A. Mandelli, L. (2008). The genetics of bipolar disorder: Genome ‘hot regions,’ genes, new potentia l candidates and future directions. Molecular Psychiatry, 13(8), 742-771. Srivastava, S. Ketter, T. A. (2010). The link between bipolar disorders and creativity: Evidence from personality and temperament studies. Current Psychiatry Reports, 12(6), 522-530. This research paper on Bipolar Disorder: Symptoms, Effects, Diagnosis and Treatment was written and submitted by user Maryam Spence to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Books to Increase Self-Confidence

Books to Increase Self-Confidence The shelves of self-help books are bursting. You can find books on finding inner peace, becoming a millionaire in 3 years, conquering your fears, fixing your social life, becoming a great leader, mastering your own fate, and thousands upon thousands of other topics. What very few of these books tell you, however, is that all of this every improvement plan you make to achieve all that you want begins with self-confidence. Nothing works until you have it. And self-confidence really boils down to trust trusting yourself more than others. So, if you are going to that self-help section today, here are 10 books that will begin your journey. 1. BARTON GOLDSMITH - 100 WAYS TO BOOST YOUR SELF-CONFIDENCE This is probably the most practical of all books on building self-confidence, and such an easy read. Goldsmith has it nailed with his descriptions of people who lack confidence. He has prescriptions for getting rid of all of those thoughts, behaviors and habits that tell yourself and others that you are well kind of wimpy, and that you are letting events and others control you. His tips range from intellectual behaviors (educating yourself), to physical style (new clothes and grooming) to embracing your flaws. 2. STEVEN R. COVEY - 7 HABITS OF HIGHLY EFFECTIVE PEOPLE Most people have the impression that this book is written only for the career professional who wants to get ahead. Yes, it is. But the principles apply to anyone and to any aspect of ones life. And, each of the 7 habits that Covey has described begins with self-confidence. Its all a matter of practicing certain behaviors until they become habitual once they do, you have changed your mindset. The overriding principle is really act as if you are highly successful and you will be. 3. GARY VURNUM - INSTANT CONFIDENCE: 92 TIPS This book does not have amazing new insights to give. It is literally 92 tips for everyday action that can project you as a self-confident person. (e.g., change the focus away from you). The basic idea is this use the tips, others will see you as self-confident, and you will respond to that be being even more self-confident. Its a good book to have around to remind yourself of the behaviors you need to be exhibiting. 4. ANTHONY ROBBINS AWAKEN THE GIANT WITHIN This is not a book you will want to read quickly. It addresses how you become the master of your own destiny, step by step from the decisions you make, to the vocabulary you choose. The book is filled with challenges for you to take up even a 7-day master plan to get control and become the self-confident giant you should be. 5. SAM HORN WHATS HOLDING YOU BACK? How about walking into a room full of strangers and being able to walk up to any of them and begin a conversation? This book is a 30-day diet of learning how to be more powerful in all settings (work, social, home), to stop comparing yourself to others (a true killer of self-confidence), and to never worry again about the impression you are making. Each chapter is a day of the 30. The best way to read this? One chapter a night before you go to bed with the commitment to follow through the next day. 6. BRIAN ROET - THE CONFIDENCE TO BE YOURSELF If you have never heard of cognitive-behavioral therapy, you will understand it after you read this book. The basic principle is that once you change your thinking, your behaviors will change to match that thinking. This book will teach you how to change those low self-esteem thoughts into thoughts of confidence, based on who you are, and then you can watch the transformation that occurs on the outside. 7. KEV​IN LEMAN - HAVE A NEW YOU BY FRIDAY An inspirational read but also one that has wonderfully practical advice about becoming self-confident. You begin by accepting the truth about yourself (Monday), and move on from there to identifying the lies you tell yourself (Wednesday), and so on. This is a great read, because Dr. Leman is so funny while he literally shows you how to transform yourself into a confident person in 5 days. 8. MARK GOULSTON - GET OUT OF YOUR OWN WAY We are our own worst enemies this old saying comes to life in Goulstons great book. Even though it is a fun read with lots of examples we can see in ourselves, it is packed with loads of practical advice for overcoming fear, anxiety, and a host of other emotions and thoughts that cause our lack of confidence. Once we slay those dragons, one by one, we emerge triumphant and confident. 9. ADAM KHAN SELF-HELP STUFF THAT WORKS Short chapters, easy to read, spliced with humor and advice for everyday situations. Khan doesnt spend any time on deep philosophical or psychological meanings for our lack of confidence he nails the behaviors and how to change them. 350 pages of golden nuggets! 10.RICHARD MACHOWICZ UNLEASH THE WARRIOR WITHIN Machowicz was a Navy SEAL in his former life and has now translated all of what he learned to very practical steps for everyday people to gain self-confidence and realize their goals. For example, you complete every task on time, no matter what the conditions and your approach is always based on a single thought failure is not an option. And its all about the weapons you choose knowledge, attitude, and commitment. The analogy to being a warrior on the battle field and being a warrior in life is really quite stunning.

Booker T. Washington and Education Essay Example | Topics and Well Written Essays - 750 words

Booker T. Washington and Education - Essay Example For instance, Washington accepted segregation of the races, his outward humility, and his opposition to black militancy (Rutkoff and Scott). For this reason, many black intellectuals from Washington’s time were shy about placing him as the spokesperson for the struggle for social recognition. Regardless, Washington’s thoughts on education have remained within the public’s consideration for a number of years, opening the question of how does our current world evaluate, and utilize, what Washington had to contribute to the field of education. Washington was born a Virginian slave in either 1858 or 1859 and, although freed by the Emancipation Proclamation in 1863, sought employment at age nine in coalmines and salt works. Washington was entirely self-educated: finding the value of knowledge after his first experience with a spelling book. In 1872, Washington moved a few hundred miles to Virginia’s Hampton Institute in Virginia to enhance his education. Washin gton took employment as a janitor in Hampton so that he could pay his tuition, room, and board. Similar to his peers at Hampton, Washington received a lesson in the value of hard work for moral and economic strength. â€Å"He worked his way through school and taught for two years at Hampton after graduating† (Hine, Hine and Harrold 339). Afterward, Washington took up a position as headmaster at a school in Tuskegee, Alabama. Understanding how Washington found himself as the head of a school is crucially important for contextualizing his contributions to the philosophy of education in the early parts of black freedom within the United States. Because Washington employed personal initiative and hard work in reaching a place of dignity, he wanted to share that experience with all black people. His take on education was representative of the fact that he was not an intellectual; rather he was a man that employed action to achieve the means of survival (Rutkoff and Scott). He want ed black people in the south to value the need for industrial education from the perspective as both American and African. Washington emphasized the industrial curriculum as a means of a stepping-stone toward race independence; however, this emphasis does not represent an inherent belief in the incapacity of blacks to master scholarly subjects as well. Rather, â€Å"one man may go into a community prepared to supply the people there an analysis of Greek sentences. The community may or may not at that time be prepared for, or feel the need of, Greek analysis, but it may feel the need of bricks and houses and wagons† (Washington 156-157). Washington’s intent by advocating the industrial curriculum was to grant these blacks the ability to break cycles of perpetual debt brought on by a lack of independence from the sharecropping system, which kept individuals from learning the tools and competences necessary for work that is more skilled. As a man of action, who achieved a high status by working hard and taking the extra step, Washington saw the production of value with one’

You guys have to refer my file Essay Example | Topics and Well Written Essays - 250 words - 1

You guys have to refer my file - Essay Example Additionally, the four encourage the reconciliation of both obedience and conscience (Milgram and Philip 189). As such, they encourage ethical and moral practice. The police officers did not obey the standards procedure in their desire to restore law and order in the streets. Furthermore, the officers brutalized their suspects thus disregarding all the ethical and moral dictates of the practice. I believe the local Oakland resident made the statement out of rage. Apparently, drug was a major cause of disharmony in the society. The rogue officers stamped their authority albeit illegally thereby reducing the prevalence of drug-related crime. The resident thus believed that such officers would help restore law and order in the society and that they were acting for the greater good of the society. The resident later reconsiders the lawless nature of the actions of the police. He understands that the actions disregarded basic human rights. Additionally, such actions would possibly begin affecting innocent residents. The resident, therefore, concludes by expressing his confusion. I imagine the rough riders came into existence because of inefficiencies in the management of the police department. The management of the police department relented in their supervision of the officers thus permitting a few officers to break the

Ethical and Social Responsibility at Hyundai Motor Company Essay

Ethical and Social Responsibility at Hyundai Motor Company - Essay Example By being ethically and socially responsible, the company ensures that it maximizes positive impact on the society, while reducing negative societal impact. Accordingly, a company is supposed to ensure legal, economic and charitable humanitarian responsibilities (Ihlen, Bartlett & May, 2011). The Hyundai motor company is an automobiles manufacturing and distribution company, of South Korean origin. This company has dealings in many other world regions including; Europe, America as well as the Middle East. According to Lansbury et al. (2007), among the company’s main concerns is, corporate social responsibility via corporate citizenship, through which, the company makes its contribution to the global society. For Hyundai motor company, ethical responsibility encompasses social contribution, environmental management and trust-based administration. As far as social contribution is concerned, the company has enlarged its capacity and obtained expertise for effective global projects (Kaslow, 2006). Hyundai also participates in charitable initiatives that contribute to the improvement of the lives of the local population. Trust-based administration focuses on the improvement of labor dealings, mutual benefit between them and their suppliers, as well as transparent management. Lastly, environmental management deals with responding to global tendencies, as well as environmentally related laws. It recognizes that the environment is an essential element in any business, therefore, promotes the manufacturing and supply of environmentally safe goods. The Hyundai Company also ensures the reduction of pollutants, while preserving sources of energy, from product manufacture to its disposal. Needle (2010) states that, this is achieved through training programs offered to all employees on international laws and regulations concerning the environment. Generally, the company aims at gaining trust from both the public and the government and pursuing qualitative and quantitat ive growth. In addition, Hyundai seeks to lead the industry in sustainable management, improve corporate competitiveness and grow as a revered company. Hyundai concerns itself with communities suffering the aftermaths of natural disasters, by providing quick and effective assistance. In the summer of 2005, Austria was hit by unusual floods on the Alps. In response, the Hyundai Motor Company sent financial help and provided vehicular support to help in the evacuation efforts. According to Hyundai worldwide (2010), this gesture was well received by Austria and served to solidify the Hyundai presence in that region. Through its subsidiary company in America, Hyundai has positively impacted on the society, especially through its â€Å"hope on wheels† foundation that has funded the field of pediatric cancer study and treatment. Hyundai is also an ardent supporter of the American society against cancer, to whose end; it has given financial aid since 2001. Hyundai is also a corporat e sponsor of the association that calls for equal rights for all Americans, thus ensuring political, social, educational and economic rights of the minority in the American system. These activities have helped Hyundai gain many accolades globally. The Hyundai Motor

Metrics and Models in Software Testing

Metrics and Models in Software Testing How do we measure the progress of testing? When do we release the software? Why do we devote more time and resources for testing a particular module? What is the reliability of software at the time of release? Who is responsible for the selection of a poor test suite? How many faults do we expect during testing? How much time and resources are required to test a software? How do we know the effectiveness of test suite? We may keep on framing such questions without much effort? However, finding answers to such questions are not easy and may require significant amount of effort. Software testing metrics may help us to measure and quantify many things which may find some answers to such important questions. 10.1 Software Metrics â€Å"What cannot be measured, cannot be controlled† is a reality in this world. If we want to control something we should first be able to measure it. Therefore, everything should be measurable. If a thing is not measurable, we should make an effort to make it measurable. The area of measurement is very important in every field and we have mature and establish metrics to quantify various things. However, in software engineering this â€Å"area of measurement† is still in its developing stage and may require significant effort to make it mature, scientific and effective. 10.1.1 Measure, Measurement and Metrics These terms are often used interchangeably. However, we should understand the difference amongst these terms. Pressman explained this clearly as [PRES05]: â€Å"A measure provides a quantitative indication of the extent, amount, dimension, capacity or size of some attributes of a product or process. Measurement is the act of determining a measure. The metric is a quantitative measure of the degree to which a product or process possesses a given attribute†. For example, a measure is the number of failures experienced during testing. Measurement is the way of recording such failures. A software metric may be average number of failures experienced per hour during testing. Fenton [FENT04] has defined measurement as: â€Å"It is the process by which numbers or symbols are assigned to attributes of entities in the real world in such a way as to describe them according to clearly defined rules†. The basic issue is that we want to measure every attribute of an entity. We should have established metrics to do so. However, we are in the process of developing metrics for many attributes of various entities used in software engineering. Software metrics can be defined as [GOOD93]: â€Å"The continuous application of measurement based techniques to the software development process and its products to supply meaningful and timely management information, together with the use of those techniques to improve that process and its products.† Many things are covered in this definition. Software metrics are related to measures which, in turn, involve numbers for quantification, these numbers are used to produce better product and improve its related process. We may like to measure quality attributes such as testability, complexity, reliability, maintainability, efficiency, portability, enhanceability, usability etc for a software. We may also like to measure size, effort, development time and resources for a software. 10.1.2 Applications Software metrics are applicable in all phases of software development life cycle. In software requirements and analysis phase, where output is the SRS document, we may have to estimate the cost, manpower requirement and development time for the software. The customer may like to know cost of the software and development time before signing the contract. As we all know, the SRS document acts as a contract between customer and developer. The readability and effectiveness of SRS document may help to increase the confidence level of the customer and may provide better foundations for designing the product. Some metrics are available for cost and size estimation like COCOMO, Putnam resource allocation model, function point estimation model etc. Some metrics are also available for the SRS document like number of mistakes found during verification, change request frequency, readability etc. In the design phase, we may like to measure stability of a design, coupling amongst modules, cohesion of a module etc. We may also like to measure the amount of data input to a software, processed by the software and also produced by the software. A count of the amount of data input to, processed in, and output from software is called a data structure metric. Many such metrics are available like number of variables, number of operators, number of operands, number of live variables, variable spans, module weakness etc. Some information flow metrics are also popular like FANIN, FAN OUT etc. Use cases may also be used to design metrics like counting actors, counting use cases, counting number of links etc. Some metrics may also be designed for various applications of websites like number of static web pages, number of dynamic web pages, number of internal page links, word count, number of static and dynamic content objects, time taken to search a web page and retrieve the desired information, similarity of web pages etc. Software metrics have number of applications during implementation phase and after the completion of such a phase. Halstead software size measures are applicable after coding like token count, program length, program volume, program level, difficulty, estimation of time and effort, language level etc. Some complexity measures are also popular like cyclomatic complexity, knot count, feature count etc. Software metrics have found good number of applications during testing. One area is the reliability estimation where popular models are Musas basic executio n time model and Logarithmic Poisson execution time model. Jelinski Moranda model [JELI72] is also used for the calculation of reliability. Source code coverage metrics are available that calculate the percentage of source code covered during testing. Test suite effectiveness may also be measured. Number of failures experienced per unit of time, number of paths, number of independent paths, number of du paths, percentage of statement coverage, percentage of branch condition covered are also useful software metrics. Maintenance phase may have many metrics like number of faults reported per year, number of requests for changes per year, percentage of source code modified per year, percentage of obsolete source code per year etc. We may find number of applications of software metrics in every phase of software development life cycle. They provide meaningful and timely information which may help us to take corrective actions as and when required. Effective implementation of metrics may improve the quality of software and may help us to deliver the software in time and within budget. 10.2 Categories of Metrics There are two broad categories of software metrics namely product metrics and process metrics. Product metrics describe the characteristics of the product such as size, complexity, design features, performance, efficiency, reliability, portability, etc. Process metrics describe the effectiveness and quality of the processes that produce the software product. Examples are effort required in the process, time to produce the product, effectiveness of defect removal during development, number of defects found during testing, maturity of the process [AGGA08]. 10.2.1 Product metrics for testing These metrics provide information about the testing status of a software product. The data for such metrics are also generated during testing and may help us to know the quality of the product. Some of the basic metrics are given as: (i) Number of failures experienced in a time interval (ii) Time interval between failures (iii) Cumulative failures experienced upto a specified time (iv) Time of failure (v) Estimated time for testing (vi) Actual testing time With these basic metrics, we may find some additional metrics as given below: (i) (ii) Average time interval between failures (iii) Maximum and minimum failures experienced in any time interval (iv) Average number of failures experienced in time intervals (v) Time remaining to complete the testing. We may design similar metrics to find the indications about the quality of the product. 10.2.2 Process metrics for testing These metrics are developed to monitor the progress of testing, status of design and development of test cases and outcome of test cases after execution. Some of the basic process metrics are given below: (i) Number of test cases designed (ii) Number of test cases executed (iii) Number of test cases passed (iv) Number of test cases failed (v) Test case execution time (vi) Total execution time (vii) Time spent for the development of a test case (viii) Total time spent for the development of all test cases On the basis of above direct measures, we may design following additional metrics which may convert the base metric data into more useful information. (i) % of test cases executed (ii) % of test cases passed (iii) % of test cases failed (iv) Total actual execution time / total estimated execution time (v) Average execution time of a test case These metrics, although simple, may help us to know the progress of testing and may provide meaningful information to the testers and project manager. An effective test plan may force us to capture data and convert it into useful metrics for process and product both. This document also guides the organization for future projects and may also suggest changes in the existing processes in order to produce a good quality maintainable software product. 10.3 Object Oriented Metrics used in Testing Object oriented metrics capture many attributes of a software and some of them are relevant in testing. Measuring structural design attributes of a software system, such as coupling, cohesion or complexity, is a promising approach towards early quality assessments. There are several metrics available in the literature to capture the quality of design and source code. 10.3.1 Coupling Metrics Coupling relations increase complexity, reduce encapsulation, potential reuse, and limit understanding and maintainability. The coupling metrics requires information about attribute usage and method invocations of other classes. These metrics are given in table 10.1. Higher values of coupling metrics indicate that a class under test will require more number of stubs during testing. In addition, each interface will require to be tested thoroughly. Metric Definition Source Coupling between Objects. (CBO) CBO for a class is count of the number of other classes to which it is coupled. [CHID94] Data Abstraction Coupling (DAC) Data Abstraction is a technique of creating new data types suited for an application to be programmed. DAC = number of ADTs defined in a class. [LI93] Message Passing Coupling. (MPC) It counts the number of send statements defined in a class. Response for a Class (RFC) It is defined as set of methods that can be potentially executed in response to a message received by an object of that class. It is given by RFC=|RS|, where RS, the response set of the class, is given by [CHID94] Information flow-based coupling (ICP) The number of methods invoked in a class, weighted by the number of parameters of the methods invoked. [LEE95] Information flow-based inheritance coupling. (IHICP) Same as ICP, but only counts methods invocations of ancestors of classes. Information flow-based non-inheritance coupling (NIHICP) Same as ICP, but only counts methods invocations of classes not related through inheritance. Fan-in Count of modules (classes) that call a given class, plus the number of global data elements. [BINK98] Fan-out Count of modules (classes) called by a given module plus the number of global data elements altered by the module (class). [BINK98] Table 10.1: Coupling Metrics 10.3.3 Inheritance Metrics Inheritance metrics requires information about ancestors and descendants of a class. They also collect information about methods overridden, inherited and added (i.e. neither inherited nor overrided). These metrics are summarized in table 10.3. If a class has more number of children (or sub classes), more amount of testing may be required in testing the methods of that class. More is the depth of inheritance tree, more complex is the design as more number of methods and classes are involved. Thus, we may test all the inherited methods of a class and testing effort well increase accordingly. Metric Definition Sources Number of Children (NOC) The NOC is the number of immediate subclasses of a class in a hierarchy. [CHID94] Depth of Inheritance Tree (DIT) The depth of a class within the inheritance hierarchy is the maximum number of steps from the class node to the root of the tree and is measured by the number of ancestor classes. Number of Parents (NOP) The number of classes that a class directly inherits from (i.e. multiple inheritance). [LORE94] Number of Descendants (NOD) The number of subclasses (both direct and indirectly inherited) of a class. Number of Ancestors (NOA) The number of superclasses (both direct and indirectly inherited) of a class. [TEGA92] Number of Methods Overridden (NMO) When a method in a subclass has the same name and type signature as in its superclass, then the method in the superclass is said to be overridden by the method in the subclass. [LORE94] Number of Methods Inherited (NMI) The number of methods that a class inherits from its super (ancestor) class. Number of Methods Added (NMA) The number of new methods added in a class (neither inherited, nor overriding). Table 10.3: Inheritance Metrics 10.3.4 Size Metrics Size metrics indicate the length of a class in terms of lines of source code and methods used in the class. These metrics are given in table 10.4. If a class has more number of methods with greater complexity, then more number of test cases will be required to test that class. When a class with more number of methods with greater complexity is inherited, it will require more rigorous testing. Similarly, a class with more number of public methods will require thorough testing of public methods as they may be used by other classes. Metric Definition Sources Number of Attributes per Class (NA) It counts the total number of attributes defined in a class. Number of Methods per Class (NM) It counts number of methods defined in a class. Weighted Methods per Class (WMC) The WMC is a count of sum of complexities of all methods in a class. Consider a class K1, with methods M1,†¦Ã¢â‚¬ ¦.. Mn that are defined in the class. Let C1,†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.Cn be the complexity of the methods. [CHID94] Number of public methods (PM) It counts number of public methods defined in a class. Number of non-public methods (NPM) It counts number of private methods defined in a class. Lines Of Code (LOC) It counts the lines in the source code. Table 10.4: Size Metrics 10.4 What should we measure during testing? We should measure every thing (if possible) which we want to control and which may help us to find answers to the questions given in the beginning of this chapter. Test metrics may help us to measure the current performance of any project. The collected data may become historical data for future projects. This data is very important because in the absence of historical data, all estimates are just the guesses. Hence, it is essential to record the key information about the current projects. Test metrics may become an important indicator of the effectiveness and efficiency of a software testing process and may also identify risky areas that may need more testing. 10.4.1 Time We may measure many things during testing with respect to time and some of them are given as: 1) Time required to run a test case. 2) Total time required to run a test suite. 3) Time available for testing 4) Time interval between failures 5) Cumulative failures experienced upto a given time 6) Time of failure 7) Failures experienced in a time interval A test case requires some time for its execution. A measurement of this time may help to estimate the total time required to execute a test suite. This is the simplest metric and may estimate the testing effort. We may calculate the time available for testing at any point in time during testing, if we know the total allotted time for testing. Generally unit of time is seconds, minutes or hours, per test case. Total testing time may be defined in terms of hours. Time needed to execute a planned test suite may also be defined in terms of hours. When we test a software, we experience failures. These failures may be recorded in different ways like time of failure, time interval between failures, cumulative failures experienced upto given time and failures experienced in a time interval. Consider the table 10.5 and table 10.6 where time based failure specification and failure based failure specification are given: Sr. No. of failure occurrences Failure time measured in minutes Failure intervals in minutes 1 12 12 2 26 14 3 35 09 4 38 03 5 50 12 6 70 20 7 106 36 8 125 19 9 155 30 10 200 45 Table 10.5: Time based failure specification Time in minutes Cumulative failures Failures in interval of 20 minutes 20 01 01 40 04 03 60 05 01 80 06 01 100 06 00 120 07 01 140 08 01 160 09 01 180 09 00 200 10 01 Table 10.6: Failure based failure specification These two tables give us the idea about failure pattern and may help us to define the following: 1) Time taken to experience ‘n failures 2) Number of failures in a particular time interval 3) Total number of failures experienced after a specified time 4) Maximum / minimum number of failures experienced in any regular time interval. 10.4.2 Quality of source code We may know the quality of the delivered source code after reasonable time of release using the following formula: Where WDB: Number of weighted defects found before release WDA: Number of weighted defects found after release The weight for each defect is defined on the basis of defect severity and removal cost. A severity is assigned to each defect by testers based on how important or serious is the defect. A lower value of this metric indicates the less number of error detection or less serious error detection. We may also calculate the number of defects per execution test case. This may also be used as an indicator of source code quality as the source code progressed through the series of test activities [STEP03]. 10.4.3 Source Code Coverage We may like to execute every statement of a program at least once before its release to the customer. Hence, percentage of source code coverage may be calculated as: The higher value of this metric given confidence about the effectiveness of a test suite. We should write additional test cases to cover the uncovered portions of the source code. 10.4.4 Test Case Defect Density This metric may help us to know the efficiency and effectiveness of our test cases. Where Failed test case: A test case that when executed, produced an undesired output. Passed test case: A test case that when executed, produced a desired output Higher value of this metric indicates that the test cases are effective and efficient because they are able to detect more number of defects. 10.4.5 Review Efficiency Review efficiency is a metric that gives insight on the quality of review process carried out during verification. Higher the value of this metric, better is the review efficiency. 10.5 Software Quality Attributes Prediction Models Software quality is dependent on many attributes like reliability, maintainability, fault proneness, testability, complexity, etc. Number of models are available for the prediction of one or more such attributes of quality. These models are especially beneficial for large-scale systems, where testing experts need to focus their attention and resources to problem areas in the system under development. 10.5.1 Reliability Models Many reliability models for software are available where emphasis is on failures rather than faults. We experience failures during execution of any program. A fault in the program may lead to failure(s) depending upon the input(s) given to a program with the purpose of executing it. Hence, time of failure and time between failures may help us to find reliability of software. As we all know, software reliability is the probability of failure free operation of software in a given time under specified conditions. Generally, we consider the calendar time. We may like to know the probability that a given software will not fail in one month time or one week time and so on. However, most of the available models are based on execution time. The execution time is the time for which the computer actually executes the program. Reliability models based on execution time normally give better results than those based on calendar time. In many cases, we have a mapping table that converts execution time to calendar time for the purpose of reliability studies. In order to differentiate both the timings, execution time is represented byand calendar time by t. Most of the reliability models are applicable at system testing level. Whenever software fails, we note the time of failure and also try to locate and correct the fault that caused the failure. During system testing, software may not fail at regular intervals and may also not follow a particular pattern. The variation in time between successive failures may be described in terms of following functions: ÃŽ ¼ () : average number of failures upto time ÃŽ » () : average number of failures per unit time at time and is known as failure intensity function. It is expected that the reliability of a program increases due to fault detection and correction over time and hence the failure intensity decreases accordingly. (i) Basic Execution Time Model This is one of the popular model of software reliability assessment and was developed by J.D. MUSA [MUSA79] in 1979. As the name indicates, it is based on execution time (). The basic assumption is that failures may occur according to a non-homogeneous poisson process (NHPP) during testing. Many examples may be given for real world events where poisson processes are used. Few examples are given as: * Number of users using a website in a given period of time. * Number of persons requesting for railway tickets in a given period of time * Number of e-mails expected in a given period of time. The failures during testing represents a non-homogeneous process, and failure intensity decreases as a function of time. J.D. Musa assumed that the decrease in failure intensity as a function of the number of failures observed, is constant and is given as: Where : Initial failure intensity at the start of testing. : Total number of failures experienced upto infinite time : Number of failures experienced upto a given point in time. Musa [MUSA79] has also given the relationship between failure intensity (ÃŽ ») and the mean failures experienced (ÃŽ ¼) and is given in 10.1. If we take the first derivative of equation given above, we get the slope of the failure intensity as given below The negative sign shows that there is a negative slope indicating a decrementing trend in failure intensity. This model also assumes a uniform failure pattern meaning thereby equal probability of failures due to various faults. The relationship between execution time () and mean failures experienced (ÃŽ ¼) is given in 10.2 The derivation of the relationship of 10.2 may be obtained as: The failure intensity as a function of time is given in 10.3. This relationship is useful for calculating present failure intensity at any given value of execution time. We may find this relationship Two additional equations are given to calculate additional failures required to be experienced to reach a failure intensity objective (ÃŽ »F) and additional time required to reach the objective. These equations are given as: Where à ¢Ã‹â€ Ã¢â‚¬  ÃŽ ¼: Expected number of additional failures to be experienced to reach failure intensity objective. : Additional time required to reach the failure intensity objective. : Present failure intensity : Failure intensity objective. and are very interesting metrics to know the additional time and additional failures required to achieve a failure intensity objective. Example 10.1: A program will experience 100 failures in infinite time. It has now experienced 50 failures. The initial failure intensity is 10 failures/hour. Use the basic execution time model for the following: (i) Find the present failure intensity. (ii) Calculate the decrement of failure intensity per failure. (iii) Determine the failure experienced and failure intensity after 10 and 50 hours of execution. (iv) Find the additional failures and additional execution time needed to reach the failure intensity objective of 2 failures/hour. Solution: (a) Present failure intensity can be calculated using the following equation: (b) Decrement of failure intensity per failure can be calculated using the following: (c) Failures experienced and failure intensity after 10 and 50 hours of execution can be calculated as: (i) After 10 hours of execution (ii) After 50 hours of execution (d) and with failure intensity objective of 2 failures/hour (ii) Logarithmic Poisson Execution time model With a slight modification in the failure intensity function, Musa presented logarithmic poisson execution time model. The failure intensity function is given as: Where ÃŽ ¸: Failure intensity decay parameter which represents the relative change of failure intensity per failure experienced. The slope of failure intensity is given as: The expected number of failures for this model is always infinite at infinite time. The relation for mean failures experienced is given as: The expression for failure intensity with respect to time is given as: The relationship for additional number of failures and additional execution time are given as: When execution time is more, the logarithmic poisson model may give large values of failure intensity than the basic model. Example 10.2: The initial failure intensity of a program is 10 failures/hour. The program has experienced 50 failures. The failure intensity decay parameter is 0.01/failure. Use the logarithmic poisson execution time model for the following: (a) Find present failure intensity. (b) Calculate the decrement of failure intensity per failure. (c) Determine the failure experienced and failure intensity after 10 and 50 hours of execution. (d) Find the additional failures and additional and failure execution time needed to reach the failure intensity objective of 2 failures/hour. Solution: (a) Present failure intensity can be calculated as: = 50 failures = 50 failures = 0.01/falures Hence = 6.06 failures/hour (b) Decrement of failure intensity per failure can be calculated as: (c) Failure experienced and failure intensity after 10 and 50 hours of execution can be calculated as: (i) After 10 hours of execution (ii) After 50 hours of execution (d) and with failure intensity objective of 2 failures/hour (iii) The Jelinski Moranda Model The Jelinski Moranda model [JELI72] is the earliest and simples software reliability model. It proposed a failure intensity function in the form of Where = Constant of proportionality N = total number of errors present i = number of errors found by time interval ti. This model assumes that all failures have the same failure rate. It means that failure rate is a step function and there will be an improvement in reliability after fixing an error. Hence, every failure contributes equally to the overall reliability. Here, failure intensity is directly proportional to the number of errors remaining in a software. Once we know the value of failure intensity function using any reliability model, we may calculate reliability using the equation given below: Where ÃŽ » is the failure intensity and t is the operating time. Lower the failure intensity and higher is the reliability and vice versa. Example 10.3: A program may experience 200 failures in infinite time of testing. It has experienced 100 failures. Use Jelinski-Moranda model to calculate failure intensity after the experience of 150 failures? Solution: Total expected number of failures (N) = 200 Failures experienced (i) =100 Constant of proportionality () = 0.02 We know = 2.02 failures/hour After 150 failures = 0.02 (200-150+1) =1.02 failures/hour Failure intensity will decrease with every additional failure experience. 10.5.2 An example of fault prediction model in practice It is clear that software metrics can be used to capture the quality of object oriented design and code. These metrics provide ways to evaluate the quality of software and their use in earlier phases of software development can help organizations in assessing a large software development quickly, at a low cost. To achieve help for planning and executing testing by focusing resources on the fault prone parts of the design and code, the model used to predict faulty classes should be used. The fault prediction model can also be used to identify classes that are prone to have severe faults. One can use this model with respect to high severity of faults to focus the testing on those parts of the system that are likely to cause serious failures. In this section, we describe models used to find relationship between object oriented metrics and fault proneness, and how such models can be of great help in planning and executing testing activities [MALH09, SING10]. In order to perform the analysis we used public domain KC1 NASA data set [NASA04] The data set is available on www.mdp.ivv.nasa.gov. The 145

Physics of a Mountain Bike Essay example -- Physics Papers

Physics of a Mountain Bike This paper will discuss some of the physics involved in bicycles. Specifically, mountain bikes with suspension. A bicycle is a very energy efficient vehicle. Its wheels allow its rider to make full use of inertia and gravitational potential energy. The basic design of a bicycle has been around for over 100 years and compared to other things, has changed very little. Some of the topics that will be covered are: frames, wheels, suspension forks, suspension frames, brakes and how all these things affect speed, momentum and stability. Some of the key parts of any bicycle are the frame, forks and wheels. The most common type of bicycle frame is known as the double diamond. It is called this because if you look at the frame, it is diamond shaped with 2 smaller triangles forming the front and rear. This designed has endured because it is easy to build, strong and efficient. The tubing that a frame is made with is usually round but can be many different shapes even on the same bike. The reason for this shaping is to increase the rigidity or improve the ride quality. For instance, the sloping tube that goes from the front of the bike to the pedal junction of the frame is sometimes ovalized along the horizontal axis at the pedal junction to make the frame flex less side to side. Frames have been made from many materials including wood, steel, aluminum, titanium and carbon fiber just to name a few. Each of the materials have a strength to weight ratio, tensile strength and cost of production that must be taken into accou nt before deciding which will work best. For example, when a frame made of beryllium was introduced, the strength to weight ratio was very high. The weight was extremely low but the cost wa... ...etty. The faster you go, the smoother it gets and the greater the force required to stop. Mass times velocity is not fun when applied to a crash. Mike Farrentino in an article in Bike magazine says, â€Å"The faster you go, the longer the crash, the greater the force of the impact. Seconds seem like hours, and the clatter and gasp and thud of cart wheeling bike and body parts is not a sound easily forgotten. †¦In spite of this, whatever any of us say, we all want to go fast†¦.Momentum is the secret key to the universe. It is the rush of joy. It is the heavy hand of gravity. It is the grin of a child, feet off the pedals, bombing downhill on a tricycle.† Sources Bike magazine: volume 10, number 2 March 2003 Bloomfield, Louis A : How things work, the physics of everyday life, 1997 Kirkpatrick & Wheeler: Physics, a world view, third edition, 1998 www.howstuffwork.com