Software engineer process group

Hit enter to search or ESC to close. SEPG,Software Engineering Process Group,offshore development, Custom application development, Broadband application Development, e-zest solutions One important form of technology receptor group in the e-Zest is the software engineering process group SEPG , which focuses on software process improvement.

The Process Improvement Cycle Software process improvement is a continuous cycle. The following steps are adapted by e-Zest from the well-known Shewart cycle Set expectations Assess the current practice Analyze the variance between expectation and practice Propose changes that will reduce the variance and thereby improve the process Plan the integration of the improvements into the existing process and update the process definition. If a formal process definition does not exist, it should be documented now Implement the improvements.

Perform the process as it is now defined Start over To know more write to info e-zest. Other related services Infrastructure Business Continuity Plan.

Related Insights Work Building scalable enterprise digital commerce for a global pharma giant Digital transformation around the e-commerce services across multiple geographies and business divisions for a globally leading pharma company. For example, a quantitative assessment of the software inspection process might be performed by examining the procedural steps followed and results obtained plus data concerning defects found and time required to find and fix the defects as compared to software testing.

A typical method of software process assessment includes planning, fact-finding by collecting evidence through questionnaires, interviews, and observation of work practices , collection and validation of process data, and analysis and reporting.

Process assessments may rely on the subjective, qualitative judgment of the assessor, or on the objective presence or absence of defined artifacts, records, and other evidence. The activities performed during a software process assessment and the distribution of effort for assessment activities are different depending on the purpose of the software process assessment.

Software process assessments may be undertaken to develop capability ratings used to make recommendations for process improvements or may be undertaken to obtain a process maturity rating in order to qualify for a contract or award. The goal of a software process assessment is to gain insight that will establish the current status of a process or processes and provide a basis for process improvement; performing a software process assessment by following a checklist for conformance without gaining insight adds little value.

Software process improvement models emphasize iterative cycles of continuous improvement. A software process improvement cycle typically involves the subprocesses of measuring, analyzing, and changing. The Plan-Do-Check-Act model is a well-known iterative approach to software process improvement. Improvement activities include identifying and prioritizing desired improvements planning ; introducing an improvement, including change management and training doing ; evaluating the improvement as compared to previous or exemplary process results and costs checking ; and making further modifications acting.

The Plan-Do-Check-Act process improvement model can be applied, for example, to improve software processes that enhance defect prevention. Software process capability and software process maturity are typically rated using five or six levels to characterize the capability or maturity of the software processes used within an organization.

A continuous rating system involves assigning a rating to each software process of interest; a staged rating system is established by assigning the same maturity rating to all of the software processes within a specified process level. A representation of continuous and staged process levels is provided in Table 8.

Continuous models typically use a level 0 rating; staged models typically do not. In Table 8. At level 1, a software process is being performed capability rating , or the software processes in a maturity level 1 group are being performed but on an ad hoc, informal basis.

At level 2, a software process capability rating or the processes in maturity level 2 are being performed in a manner that provides management visibility into intermediate work products and can exert some control over transitions between processes. At level 3, a single software process or the processes in a maturity level 3 group plus the process or processes in maturity level 2 are well defined perhaps in organizational policies and procedures and are being repeated across different projects.

Level 3 of process capability or maturity provides the basis for process improvement across an organization because the process is or processes are conducted in a similar manner. This allows collection of performance data in a uniform manner across multiple projects. At maturity level 4, quantitative measures can be applied and used for process assessment; statistical analysis may be used. At maturity level 5, the mechanisms for continuous process improvements are applied.

Continuous and staged representations can be used to determine the order in which software processes are to be improved. In the continuous representation, the different capability levels for different software processes provide a guideline for determining the order in which software processes will be improved.

In the staged representation, satisfying the goals of a set of software processes within a maturity level is accomplished for that maturity level, which provides a foundation for improving all of the software processes at the next higher level. This topic addresses software process and product measurement, quality of measurement results, software information models, and software process measurement techniques see Measurement in the Engineering Foundations KA.

Before a new process is implemented or a current process is modified, measurement results for the current situation should be obtained to provide a baseline for comparison between the current situation and the new situation.

For example, before introducing the software inspection process, effort required to fix defects discovered by testing should be measured. Following an initial start-up period after the inspection process is introduced, the combined effort of inspection plus testing can be compared to the previous amount of effort required for testing alone. Similar considerations apply if a process is changed. Software process and product measurement are concerned with determining the efficiency and effectiveness of a software process, activity, or task.

The efficiency of a software process, activity, or task is the ratio of resources actually consumed to resources expected or desired to be consumed in accomplishing a software process, activity, or task see Efficiency in the Software Engineering Economics KA. Effort or equivalent cost is the primary measure of resources for most software processes, activities, and tasks; it is measured in units such as person-hours, person-days, staffweeks, or staff-months of effort or in equivalent monetary units—such as euros or dollars.

Effectiveness is the ratio of actual output to expected output produced by a software process, activity, or task; for example, actual number of defects detected and corrected during software testing to expected number of defects to be detected and corrected—perhaps based on historical data for similar projects see Effectiveness in the Software Engineering Economics KA. Note that measurement of software process effectiveness requires measurement of the relevant product attributes; for example, measurement of software defects discovered and corrected during software testing.

One must take care when measuring product attributes for the purpose of determining process effectiveness. For example, the number of defects detected and corrected by testing may not achieve the expected number of defects and thus provide a misleadingly low effectiveness measure, either because the software being tested is of betterthan- usual quality or perhaps because introduction of a newly introduced upstream inspection process has reduced the remaining number of defects in the software.

Product measures that may be important in determining the effectiveness of software processes include product complexity, total defects, defect density, and the quality of requirements, design documentation, and other related work products.

Also note that efficiency and effectiveness are independent concepts. An effective software process can be inefficient in achieving a desired software process result; for example, the amount of effort expended to find and fix software defects could be very high and result in low efficiency, as compared to expectations.

An efficient process can be ineffective in accomplishing the desired transformation of input work products into output work products; for example, failure to find and correct a sufficient number of software defects during the testing process. The efficiency and effectiveness of software process execution are also affected either positively or negatively by factors such as turnover in software personnel, schedule changes, a new customer representative, or a new organizational policy.

In software engineering, productivity in performing a process, activity, or task is the ratio of output produced divided by resources consumed; for example, the number of software defects discovered and corrected divided by person-hours of effort see Productivity in the Software Engineering Economics KA.

Accurate measurement of productivity must include total effort used to satisfy the exit criteria of a software process, activity, or task; for example, the effort required to correct defects discovered during software testing must be included in software development productivity. Calculation of productivity must account for the context in which the work is accomplished.

For example, the effort to correct discovered defects will be included in the productivity calculation of a software team if team members correct the defects they find—as in unit testing by software developers or in a cross-functional agile team.

Or the productivity calculation may include either the effort of the software developers or the effort of an independent testing team, depending on who fixes the defects found by the independent testers. Note that this example refers to the effort of teams of developers or teams of testers and not to individuals.

Software productivity calculated at the level of individuals can be misleading because of the many factors that can affect the individual productivity of software engineers.

Standardized definitions and counting rules for measurement of software processes and work products are necessary to provide standardized measurement results across projects within an organization, to populate a repository of historical data that can be analyzed to identify software processes that need to be improved, and to build predictive models based on accumulated data. In the example above, definitions of software defects and staff-hours of testing effort plus counting rules for defects and effort would be necessary to obtain satisfactory measurement results.

Software processes may be institutionalized by adoption within the local organizational unit or across larger units of an enterprise. The quality of process and product measurement results is primarily determined by the reliability and validity of the measured results. Measurements that do not satisfy these quality criteria can result in incorrect interpretations and faulty software process improvement initiatives.

Other desirable properties of software measurements include ease of collection, analysis, and presentation plus a strong correlation between cause and effect. The Software Engineering Measurement topic in the Software Engineering Management KA describes a process for implementing a software measurement program.

Software information models allow modeling, analysis, and prediction of software process and software product attributes to provide answers to relevant questions and achieve process and product improvement goals. Needed data can be collected and retained in a repository; the data can be analyzed and models can be constructed.

Validation and refinement of software information models occur during software projects and after projects are completed to ensure that the level of accuracy is sufficient and that their limitations are known and understood. Software information models may also be developed for contexts other than software projects; for example, a software information model might be developed for processes that apply across an organization, such as software configuration management or software quality assurance processes at the organizational level.

Analysis-driven software information model building involves the development, calibration, and evaluation of a model. A software information model is developed by establishing a hypothesized transformation of input variables into desired outputs; for example, product size and complexity might be transformed into estimated effort needed to develop a software product using a regression equation developed from observed data from past projects. A model is calibrated by adjusting parameters in the model to match observed results from past projects; for example, the exponent in a nonlinear regression model might be changed by applying the regression equation to a different set of past projects other than the projects used to develop the model.

A model is evaluated by comparing computed results to actual outcomes for a different set of similar data. There are three possible evaluation outcomes:. Continuous evaluation of the model may indicate a need for adjustments over time as the context in which the model is applied changes. It can be used to guide analysis-driven software information model building; results obtained from the software information model can be used to guide process improvement.

Software process measurement techniques are used to collect process data and work product data, transform the data into useful information, and analyze the information to identify process activities that are candidates for improvement. In some cases, new software processes may be needed.

Process measurement techniques also provide the information needed to measure the effects of process improvement initiatives. Process measurement techniques can be used to collect both quantitative and qualitative data. The purpose of quantitative process measurement techniques is to collect, transform, and analyze quantitative process and work product data that can be used to indicate where process improvements are needed and to assess the results of process improvement initiatives.

Quantitative process measurement techniques are used to collect and analyze data in numerical form to which mathematical and statistical techniques can be applied. Quantitative process data can be collected as a byproduct of software processes.

For example, the number of defects discovered during software testing and the staff-hours expended can be collected by direct measurement, and the productivity of defect discovery can be derived by calculating defects discovered per staff-hour.

Software Web Developer, Sr. Software Web Developer A software web developer, or senior software web developer is someone who has: several years of professional programming experience; can write complex code; possesses a thorough understanding of databases, application services and application lifecycle development; and has become proficient at creating entire applications. However, this position can also be a great jumping off point to a position as a software engineer or a manager, such as lead software engineer or CTO chief technical officer of a startup.

Lead Software Engineer, Technical Architect For someone who wants to take on additional responsibility and more of a challenge, but is not interested in team management, a lead software engineer or architect role may be a great fit.

Lead engineers are looked to for guidance and direction by other engineers and programmers, and the role is seen as a mid-level management position. Lead engineers still write code, but also collaborate with others regarding work flow priorities and implement final decisions. They have years of programming experience, expertise in a specific subject matter, and can think of, plan, and build appropriate software to solve complicated problems. Architects still write code occasionally as well, however they are mainly responsible for designing complex systems that other web developers will implement.

The role of architect is a technical one and not usually a stepping stone to something more - often thought of as the highest position on the technical side of things. Development Team Lead, Software Development Manager Management is the next step along the software engineer's career path that can involve different focuses and responsibilities. These can include managing teams of developers, managing large-scale projects, and hiring and firing developers.

Mid-level managers like lead software engineers keep track of productivity and workflow in the department and report to a senior manager. A senior manager coordinates the needs of the project leader with the development team, which requires excellent people skills and the ability to resolve conflict effectively. Director, Vice President, Chief Technology Officer Senior management which can include titles such as director, vice president, or chief technology officer report to the CEO or to the company's board of directors.

They oversee the work of other managers and often have some responsibility towards setting strategic and corporate direction. Some executive type responsibilities may include setting goals and initiatives, developing long-term strategies, and holding various departments accountable for specific measurable objectives. Senior managers are also responsible for supervising, hiring, and firing mid-level managers.

If managing people is just not something you are interested in, a career as a software engineer still provides such a decent level of income that you can still be a team contributor and have a rewarding career. Continue reading. One of the main differences between software engineering and software development is job function.

They systematically develop processes to provide specific functions by using engineering concepts to develop software. On the other hand, software developers are responsible for the entire development process and are the driving creative force behind programs. They typically work together with the client to create a conceptual design and then have computer programmers create the programming code needed to run the software.

The computer programmers along with the software developers will test and fix problems together and the developers will provide project leadership and technical guidance through each stage of the software development life cycle. To sum things up, a software engineer is often involved with software development, but very few software developers are engineers.

The main difference between software engineering and software development is that one oversees the engineering while the other focuses on creating functional programs. Attracted by high salaries, strong employment opportunities, and a chance to build things that can change the world, more people than ever are choosing software engineering as a career choice.

However, succeeding in this career requires more than just great coding ability. The best software engineers bring specific qualities and attributes to the job that make them stand out from everyone else. Working well with others There are many media portrayals of a lone-wolf that stays up all night coding furiously in isolation. This stereotype represents coders as exceptionally smart but emotionally stunted. Unfortunately this type of temperament doesn't work well in real life.

Software engineers who know how to work well with others are much more likely to be successful in their careers than lone wolves are. A software engineer's job is to figure problems out and to produce a great product, not just to write as many amazing lines of code as possible. That means communicating with other engineers, developers, managers, quality control people, customers, etc. The better your relationships are with your team, the better your own work will be.

Letting go of the ego Not bringing your ego to work with you and staying humble can be difficult at times. No matter how good you think you are at what you do, it's inevitable that you will make mistakes along with some bad decisions.

Accepting constructive criticism from your peers when errors are pointed out and accepting responsibility for your mistakes will make you a much better engineer in the long run. Possessing a humble attitude is the only way you'll be able to channel other people's feedback into improving, learning, and making yourself a better software engineer and person.

Not putting out mediocre work Software engineers who pay attention to details tend to write higher-quality code. They tend to step back and catch mistakes, instead of rushing and cutting corners. Those that feel a personal sense of ownership and pride when it comes to their work tend to be more successful in this career. Putting effort into what you're doing wards off mediocrity and gives you that push to produce high-quality work and not get too complacent. Also, sharpening your skills by learning new languages or keeping abreast of any new data structures or algorithms can keep things interesting and fresh.