Balancing Agility and Discipline
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INCOSE Working Group Addresses System and Software Interfaces Sarah Sheard, Ph.D. Rita Creel CMU Software Engineering Institute CMU Software Engineering Institute (412) 268-7612 (703) 247-1378 [email protected] [email protected] John Cadigan Joseph Marvin Prime Solutions Group, Inc. Prime Solutions Group, Inc. (623) 853-0829 (623) 853-0829 [email protected] [email protected] Leung Chim Michael E. Pafford Defence Science & Technology Group Johns Hopkins University +61 (0) 8 7389 7908 (301) 935-5280 [email protected] [email protected] Copyright © 2018 by the authors. Published and used by INCOSE with permission. Abstract. In the 21st century, when any sophisticated system has significant software content, it is increasingly critical to articulate and improve the interface between systems engineering and software engineering, i.e., the relationships between systems and software engineering technical and management processes, products, tools, and outcomes. Although systems engineers and software engineers perform similar activities and use similar processes, their primary responsibilities and concerns differ. Systems engineers focus on the global aspects of a system. Their responsibilities span the lifecycle and involve ensuring the various elements of a system—e.g., hardware, software, firmware, engineering environments, and operational environments—work together to deliver capability. Software engineers also have responsibilities that span the lifecycle, but their focus is on activities to ensure the software satisfies software-relevant system requirements and constraints. Software engineers must maintain sufficient knowledge of the non-software elements of the systems that will execute their software, as well as the systems their software must interface with. -
Automated Software Process Performance Analysis and Improvement Recommendation
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Automated Software Process Performance Analysis and Improvement Recommendation Mushtaq Raza MAP-i Doctoral Program in Computer Science Supervisor: João Pascoal Faria June 27, 2017 c Mushtaq Raza, 2017 Automated Software Process Performance Analysis and Improvement Recommendation Mushtaq Raza MAP-i Doctoral Program in Computer Science Dissertation submitted to the Faculty of Engineering, University of Porto in partial fulfillment of the requirements for the degree of Doctor of Philosophy Approved by: President: Dr. Eugénio da Costa Oliveira Referee: Dr. António Manuel Ferreira Rito da Silva Referee: Dr. Paulo Jorge dos Santos Gonçalves Ferreira Referee: Dr. Fernando Manuel Pereira da Costa Brito e Abreu Referee: Dr. Ademar Manuel Teixeira de Aguiar Supervisor: Dr. João Pascoal Faria June 27, 2017 Abstract Software development processes can generate significant amounts of data that can be periodically analyzed to identify performance problems, determine their root causes and devise improvement actions. However, there is a lack of methods and tools for helping in that kind of analysis. Con- ducting the analysis manually is challenging because of the potentially large amount of data to analyze, the effort and expertise required and the lack of benchmarks for comparison. Hence, the goal of this dissertation is to develop methods, models and tools for automating the analysis of process performance data and identifying and ranking performance problems and their root causes, reducing effort and errors and improving user satisfaction as compared to previous approaches. The main contributions of the dissertation are a novel method for process performance analysis and improvement recommendation (the ProcessPAIR method), a support tool (the ProcessPAIR tool), and a performance model for instantiating ProcessPAIR for the Personal Software Process (the ProcessPAIR model for the PSP). -
Stephan Goericke Editor the Future of Software Quality Assurance the Future of Software Quality Assurance Stephan Goericke Editor
Stephan Goericke Editor The Future of Software Quality Assurance The Future of Software Quality Assurance Stephan Goericke Editor The Future of Software Quality Assurance Editor Stephan Goericke iSQI GmbH Potsdam Germany Translated from the Dutch Original book: ‘AGILE’, © 2018, Rini van Solingen & Manage- ment Impact – translation by tolingo GmbH, © 2019, Rini van Solingen ISBN 978-3-030-29508-0 ISBN 978-3-030-29509-7 (eBook) https://doi.org/10.1007/978-3-030-29509-7 This book is an open access publication. © The Editor(s) (if applicable) and the Author(s) 2020 Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 Inter- national License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. -
Week Assignment
https://www.halvorsen.blog Week Assignment Project Kick-off & Planning Hans-Petter Halvorsen All Documents, Code, etc. should be uploaded to Teams/Azure DevOps! Week Assignment 1. Project Start: Define Teams & Roles. Make CV 2. Create a Software Development Plan (SDP) 3. Team Brainstorming (What/How?) 4. Development Tools – Install necessary Software – Get Started with “Azure DevOps”* *Previously Visual Studio Team Services (VSTS) See Next Slides for more details... Textbooks (Topics this Week) Software Engineering, Ian Sommerville Ch.1: Introduction Ch.2: Software Processes Ch.23: Project Planning (with SDP example) Video: What is Software Engineering and Why do we need it? https://youtu.be/R3NzTt0BTWE Video: Introduction to Software Engineering (10 Questions to Introduce Software Engineering) https://youtu.be/gi5kxGslkNc Video: FundaMental Activities of Software Engineering https://youtu.be/Z2no7DxDWRI Office Hours: Tirsdager 10:15-14:00 “The Office” Fredager: 10:15-14:00 Lunch 11:30-12:15 Det er meningen at dere skal være tilstede på kontoret i kontortiden – selv om ikke “sjefene” (les «lærerne») er der. Dvs. det er ikke behov for å tilkalle lærerne hvis de ikke C-139a skulle dukke opp hver gang. Når dere ankommer “kontoret” (C-139a), begynner dere å jobbe videre med prosjektet. Dere trenger ikke å sitte å vente på at dere skal få beskjed Team 2 om hva dere skal gjøre, da dere er selvstendige Team som har ansvaret for hvert deres prosjekt og fremdriften av dette. Slik er det i arbeidslivet, og slik er det her. Team 1 Management Team 3 Dere er Midlertidig ansatt (5 Måneders prøvetid) soM systemutviklere i firmaet “USN Software AS”. -
Agile Project Management with Kanban
Praise for Agile Project Management with Kanban “I have been fortunate to work closely with Eric for many years. In that time he has been one of the most productive, consistent, and efficient engineering leaders at Xbox. His philosophy and approach to software engineering are truly successful.” —Kareem Choudhry, Partner Director of Software Engineering for Xbox “Eric easily explains why Kanban has proven itself as a useful method for managing and tracking complicated work. Don’t expect this book to be an overview, however. Eric channels his deep understanding and experiences using Kanban at Microsoft to help you identify and avoid many of the common difficulties and risks when implementing Kanban.” —Richard Hundhausen, President, Accentient Inc. “Learning how Xbox uses Kanban on large-scale development of their platform lends real credibility to the validity of the method. Eric Brechner is a hands-on software development management practitioner who tells it like it is—solid, practical, pragmatic advice from someone who does it for a living.” —David J. Anderson, Chairman, Lean Kanban Inc. “As a software development coach, I continuously search for the perfect reference to pragmatically apply Kanban for continuous software delivery. Finally, my search is over.” —James Waletzky, Partner, Crosslake Technologies “Kanban has been incredibly effective at helping our team in Xbox manage shifting priorities and requirements in a very demanding environment. The concepts covered in Agile Project Management with Kanban give us the framework to process our work on a daily basis to give our customers the high- quality results they deserve.” —Doug Thompson, Principal Program Manager, Xbox Engineering “An exceptional book for those who want to deliver software with high quality, predictability, and flexibility. -
Balancing Agility and Discipline a Guide for the Perplexed
Balancing Agility and Discipline A Guide for the Perplexed Written by Barry Boehm & Richard Turner August 2003 Presented by Ben Underwood for EECS810 Fall 2015 Balancing Agility and Discipline, A Guide for the Perplexed: Boehm & Turner 1 Presentation Outline What to Expect • Meet the Authors • Discipline, Agility, and Perplexity • Contrasts and Home Grounds • A Day in the Life • Expanding the Home Grounds: Two Case Studies • Using Risk to Balance Agility and Discipline • Conclusions • Q & A Balancing Agility and Discipline, A Guide for the Perplexed: Boehm & Turner 2 Meet the Authors Barry Boehm • Born 1935 • Educated in Mathematics at Harvard and UCLA • Worked in Programming and Information Sciences in private industry and government • General Dynamics, Rand Corporation, TRW, and DARPA • Currently at the University of Southern California • Professor of Software Engineering • Founding Director of USC’s Center for Systems and Software Engineering Balancing Agility and Discipline, A Guide for the Perplexed: Boehm & Turner 3 Meet the Authors Richard Turner • Born 1954 • Educated in Mathematics, Computer Science, and Engineering Management • Worked in Computer Science, Technology, and Research in private industry and government • FAA, Systems Engineering Research Center, Software Engineering Institute, George Washington University, and more • One of the core authors of CMMI • Currently at Stevens Institute of Technology • Professor in the School of Systems and Enterprises Balancing Agility and Discipline, A Guide for the Perplexed: Boehm & -
UNIT-I: Software Engineering & Process Models
UNIT-I: Software Engineering & Process Models Dual Role of Software • Both a product and a vehicle for delivering a product – Product • Delivers computing potential • Produces, manages, acquires, modifies, display, or transmits information – Vehicle • Supports or directly provides system functionality • Controls other programs (e.g., operating systems) • Effects communications (e.g., networking software) Helps build other software (e.g., software tools) A Definition of Software • Instructions (computer programs) that when executed provide desired features, function, and performance • Data structures that enable the programs to adequately manipulate information • Documents that describe the operation and use of the programs Differences between Software and Hardware • Software is developed or engineered; it is not manufactured in the classical sense – Impacts the management of software projects • Software doesn't wear out – Hardware bathtub curve compared to the software ascending spiked curve • Industry is moving toward component-based construction, most software continues to be custom built – it is still complex to build – Reusable components are created so that engineers can concentrate on innovative elements of a design – User interfaces are built with reusable components – The data structures and processing details are kept in a library for interface construction Hardware Failure Curve Software Failure Curve Changing Nature of Software • System software • Application software • Engineering/scientific software • Embedded software • -
Software Defect Reduction Top 10 List
SOFTWARE MANANGEMENT TWO Current software projects spend about Software 40 to 50 percent of their effort on avoid- able rework. Such rework consists of effort spent fixing software difficulties that could Defect Reduction have been discovered earlier and fixed less expensively or avoided altogether. By implication, then, some effort must con- sist of “unavoidable rework,” an obser- Top 10 List vation that has gained increasing credibility with the growing realization Barry Boehm, University of Southern California that better user-interactive systems result from emergent processes. In such Victor R. Basili, University of Maryland processes, the requirements emerge from prototyping and other multistakeholder- shared learning activities, a departure from traditional reductionist processes that stipulate requirements in advance, ecently, a National Science insight has been a major driver in focus- then reduce them to practice via design Foundation grant enabled us to ing industrial software practice on thor- and coding. Emergent processes indicate establish the Center for Empiri- ough requirements analysis and design, that changes to a system’s definition that R cally Based Software Engineer- on early verification and validation, and make it more cost-effective should not be ing. CeBASE seeks to transform on up-front prototyping and simulation discouraged by classifying them as avoid- software engineering as much as pos- to avoid costly downstream fixes.” able defects. sible from a fad-based practice to an engineering-based practice through deri- vation, organization, and dissemination Software’s complexity and of empirical data on software develop- accelerated development ment and evolution phenomenology. The phrase “as much as possible” reflects the schedules make avoiding defects fact that software development must remain a people-intensive and continu- difficult. -
TSP Teams Transform Test
TSP Teams Transform Test 2009 QUEST Chicago James D. McHale Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213 [email protected] © 2008-09 Carnegie Mellon University A Nightmare Scenario The development team has been promising their “final” code drop for weeks, ever since their latest due date (months after the original date). Your test team has been filling in with clean-up, make-work tasks for most of that time. Every day represents one less day for your test team to complete their work, since the final ship date is not moving. Finally an email arrives handing off the code. All the proper links to the configuration management system are there… But they point to software that doesn’t build. A few more days pass. Another email. The software builds this time. The first day of testing cannot complete due to irrecoverable defects… and management wants you to commit to the original ship date. TSP Teams Transform Test James D. McHale, 2009 QUEST Chicago 2 © 2008-09 Carnegie Mellon University Current Test Reality Requirements, Design, Code, TEST, TEST, TEST, TEST… The focus is on writing code and getting it into test. Most working software developers learned this model implicitly, either in school or on the job, and have no other mental model available. Counting ALL of the testing costs for most modern-day applications still shows that 50% or more of development effort is spent in debugging. Is the purpose of testing to find defects? Or to verify function? TSP Teams Transform Test James D. McHale, 2009 QUEST Chicago 3 © 2008-09 Carnegie Mellon University The Problem With Testing Overload Hardware Configuration failure Good region = tested (shaded) Unknown region = untested (unshaded) Resource Operator contention error Data error TSP Teams Transform Test James D. -
Using Simulation for Understanding and Reproducing Distributed Software Development Processes in the Cloud
Using Simulation for Understanding and Reproducing Distributed Software Development Processes in the Cloud M. Ilaria Lunesu1, Jürgen Münch2, Michele Marchesi3, Marco Kuhrmann4 1Department of Electrical and Electronic Engineering, University of Cagliari, Italy 2Herman Hollerith Center, Böblingen & Reutlingen University, Germany 3Department of Mathematics and Computer Science University of Cagliari, Italy 4Clausthal University of Technology, Institute for Applied Software Systems Engineering, Germany Corresponding Contact: E-Mail: [email protected] © Elsevier 2018. Preprint. This is the author's version of the work. The definite version was accepted in Information and Software Technology journal, Issue assignment pending, The final version is available at https://www.journals.elsevier.com/information-and-software-technology Using Simulation for Understanding and Reproducing Distributed Software Development Processes in the Cloud M. Ilaria Lunesua,,Jurgen¨ Munch¨ b, Michele Marchesic, Marco Kuhrmannd aDepartment of Electrical and Electronic Engineering, University of Cagliari, Italy bHerman Hollerith Center, B¨oblingen & Reutlingen University, Germany cDepartment of Mathematics and Computer Science University of Cagliari, Italy dClausthal University of Technology, Institute for Applied Software Systems Engineering, Germany Abstract Context: Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is unknown which software processes are suited for Cloud-based development and what their e↵ects in specific contexts are. Objective: We aim at better understanding the software process applied to distributed software development using the Cloud as development environment. We further aim at providing an instrument, which helps project managers comparing di↵erent solution approaches and to adapt team processes to improve future project activities and outcomes. -
Software Engineering
SOFTWARE ENGINEERING PERSONAL SOFTWARE PROCESS Personal software process is a software development process by the developers to help themselves improve their performance and efficiency by following a personal disciplined framework that facilitates to plan, design, manage and measure their work. LEARNING OBJECTIVES • To consistently improve the performance, engineers must use well-defined and measured processes. • To produce quality products, engineers must feel personally responsible for the quality. • It costs less to find and fix defects earlier in a process than later. • The right way is always the fastest and cheapest way to do a job. Better Programmer Better programmer can be achieved by, More training ◦ Know how to use tools. ◦ Have seen some problems before. ◦ Know how things fit together. Familiar with language ◦ Object, semaphore, recursion, etc.. Better process Examples of Better Processes Incremental coding ◦ Code a little, test a little ◦ Compare to writing entire program and testing Error prevention versus debugging ◦ Cheaper and easier to prevent than to find bugs Point of Processes The point of processes is to learn from mistakes so that we never make the same mistake twice. It incorporates best practices as something works better than another. A process executes routine standard tasks, when once the task is done it right once and then it is reused. Another major point of having processes is predictability. PERSONAL SOFTWARE PROCESS Personal software process is a software development process by the developers to help themselves improve their performance and efficiency by following a personal disciplined framework that facilitates to plan, design, manage and measures their work. PSP helps you to manage your work & assess/build your talents/skills. -
Software Engineering Introduction
Software Engineering Introduction - Himasri Lekkala - CSCE Graduate student Software Engineering Application of engineering methodologies to design, develop and maintain a software within budget, on schedule and with high quality. Why Software Engineering? 1 2 3 4 5 Helps in utilizing Delivers the Makes possible Increases Customer the budget product on to handle large reliability of a satisfaction effectively schedule projects software Little Bug, Big Bang • Took 10 years and $7 billion to produce Ariane 5, a giant rocket. • Exploded in less than a minute after its launch due to a small bug in the software. Software Development Life Cycle (SDLC) Software Requirement Specification 1. Requirement (SRS) analysis Software has to be updated as 6. 2. Maintenance Design Design Document Specification needed. (DDS) SDLC At first, software is released 5. 3. in limited segment for User Deployment Development Coding Acceptance Test (UAT) 4. Testing Tests for bugs & ensures if all the requirements in SRS are met UML Diagrams (Unified Modeling Language) Class diagram Object diagram SDLC Models • Waterfall Model • Incremental Model • Spiral Model • Agile Model • Chaos Model • Scrum Model • V-Model • Sawtooth Model Waterfall Model Requirement Software Requirement Specification (SRS) Analysis Design Design Document Specification (DDS) Implementation Build code in small programs called units & perform unit testing Testing Integration of units and software testing Deployment & Maintenance Release into market and check for patches 11 Waterfall Model - Application 1 2 3 4 Requirements are Ample resources Technology is Suitable for short very well with required understood and is term projects. documented, clear expertise are not dynamic. and fixed. available to support the product.