ANITA CARLETON
This post is coauthored by John Robert, Mark Klein, Doug Schmidt, Forrest Shull,John Foreman, Ipek Ozkaya, Robert Cunningham, Charlie Holland, Erin Harper, andEdward Desautels
翻譯：田媛
Software is vital to our country’sglobal competitiveness, innovation, and national security. It also ensures our modernstandard of living and enables continued advances in defense, infrastructure, healthcare,commerce, education, and entertainment. As the DoD’s federally funded research anddevelopment center (FFRDC) focused on improving the practice ofsoftware engineering, the Carnegie Mellon University (CMU) Software Engineering Institute(SEI) is leading the community in creating a multi-year researchand development vision and roadmap for engineering next-generation software-reliantsystems. This blog post describes that effort.
軟體對於我國的國際競爭力、創新、國家安全至關重要。軟體還保證了我們的現代生活水平，並確保國防、基礎設施、醫療保健、商業、教育和娛樂等方面持續進步。美國國防部聯邦資助的研究和發展中心（FFRDC）專注於改進軟體工程實踐，卡耐基梅隆大學（CMU）軟體工程研究所（SEI）正圍繞下一代軟體依賴系統，領導團隊規劃未來多年的研發遠景和路線圖。本文介紹了這方面的一些工作。
Software Engineering as StrategicAdvantage
軟體工程被視作戰略優勢
In a 2020 National Academyof Science Study on Air Force software sustainment, the U.S. AirForce recognized that 「to continue to be a world-class fighting force, it needsto be a world-class software developer.」 This concept clearly applies far beyondthe Department of Defense.Software systems enable world-class healthcare, commerce, education, energy generation,and more. These systems that run our world are rapidly becoming more data intensiveand interconnected, increasingly utilize AI, require larger-scale integration, andmust be considerably more resilient. Consequently, significant investment in softwareengineering R&D is needed now to enable and ensure future capability.
在2020年度美國國家科學院關於空軍軟體維護的研究中，美國空軍認識到，「要繼續擁有世界一流的戰鬥力，就需要具備世界一流的軟體開發人員」。這一概念顯然遠遠不只適用於國防部。軟體系統可以使醫療保健、商業、教育、能源生產等達到世界一流水平。這些運行於我們世界中的系統，其數據密集程度和互聯程度正在迅速提升，應用人工智慧的程度越來越高，需要更大規模的集成，而且必須更具靈活性。
Goals of This Work
工作目標
The SEI has leveraged its connectionswith academic institutions and communities, DoD leaders and members of the Defense IndustrialBase, and industry innovators and research organizations to:
SEI與學術機構和社區、國防部領導者和國防工業基地成員、工業創新者和研究組織均建立聯繫，基於這些聯繫，SEI：
identify future challenges in engineering software-reliant and intelligent systems in emerging, national-priority technical domains, including gaps between current engineering techniques and future domains that will be more reliant on continuous evolution and AI
識別在國家優先發展的新興技術領域中，工程軟體依賴系統和智能系統在未來所面臨的挑戰，包括當前工程技術與更依賴於持續演變和人工智慧的未來領域之間的差距
develop a research roadmap that will drive advances in foundational software engineering principles across a range of system types, such as intelligent, safety-critical, and data-intensive systems
開發一個研究路線圖，該路線圖將驅動形成一系列系統類型（如智能、安全關鍵和數據密集型系統）的基礎軟體工程原則
raise the visibility of software to the point where it receives the sustained recognition commensurate with its importance to national security and competitiveness
提高軟體的可見度，使軟體獲得與其對國家安全和競爭力的重要性相匹配的持續認可
enable strategic partnerships and collaborations to drive innovation among industry, academia, and government.
建立戰略夥伴關係和合作，推動行業、學術界和政府之間的創新。
Guided by an Advisory Board ofU.S. Visionaries and Senior Thought Leaders
由遠見卓識之人和高級思想領袖組成的顧問委員會進行指導
To succeed in developing our visionand roadmap for software engineering research and development, it is vital to coordinatethe academic, defense, and commercial communities to define an effective agendaand implement impactful results. To help represent the views of all these softwareengineering constituencies, the SEI formed an advisory board from DoD, industry,academia, research labs, and technology companies to offer guidance. Members ofthis advisory board include the following:
為成功開發軟體工程研究與開發的願景和路線圖，協調學術、國防和商業團體來定義有效的議程並實現有影響力的成果是至關重要的。為了能代表所有這些軟體工程支持者的觀點，SEI成立了一個由國防部、工業界、學術界、研究實驗室和技術公司組成的顧問委員會來提供指導。這個顧問委員會的成員包括以下人員：
Deb Frincke, advisory board chair, Associate Laboratory Director for National Security Sciences, Oak Ridge National Laboratory
Deb Frincke，橡樹嶺國家實驗室顧問委員會主席，國家安全科學實驗室副主任
Michael McQuade, vice president for research, Carnegie Mellon University
Michael McQuade，卡內基梅隆大學負責科研的副校長
Vint Cerf, vice president and chief internet evangelist, Google
Vint Cerf，谷歌副總裁兼首席網際網路布道官
Penny Compton, vice president for software systems, cyber, and operations, Lockheed Martin Space
Penny Compton，洛克希德馬丁公司軟體系統、網絡和運營副總裁
Tim Dare, deputy director for prototyping and software, Office of the Under Secretary of Defense for Research and Engineering (previous position)
Tim Dare，國防部研究和工程副部長辦公室原型設計和軟體副主任 (曾任)
Sara Manning Dawson, chief technology officer enterprise security, Microsoft
Sara Manning Dawson，微軟企業安全首席技術官
Jeff Dexter, senior director of flight software & cybersecurity, SPACEX
Jeff Dexter，SPACEX公司飛行軟體與賽博安全高級總監
Yolanda Gil, president, Association for the Advancement of Artificial Intelligence (AAAI); Director of Knowledge Technologies, Information Sciences Institute at University of Southern California
Yolanda Gil，美國人工智慧促進會（AAAI）主席；南加州大學信息科學研究所知識技術主任
Tim McBride, president, Zoic Studios
Tim McBride，ZOIC工作室總裁
Nancy Pendleton, vice president and senior chief engineer for mission systems, payloads and sensors, Boeing Defense, Space and Security
Nancy Pendleton，波音國防、空間和安全副總裁兼任務系統、有效載荷和傳感器高級總工程師
William Scherlis, director Information Innovation Office, DARPA
William Scherlis，DARPA信息創新辦公室主任
In June 2020, the SEI assembledthis board to leverage their diverse perspectives and provide strategic advice,influence stakeholders, develop connections, assist in executing the roadmap, andadvocate for the use of our results.
2020年6月，SEI召集這一委員會，採集他們的不同觀點、提供戰略建議、影響利益相關方、建立聯繫、協助執行路線圖，並倡導使用我們的研究成果。
Future Systems and FundamentalShifts in Software Engineering Require New Research Focus
軟體工程的未來系統和根本性轉變需要新的研究重點
Rapidly deploying software withconfidence requires fundamental shifts in software engineering. New types of systemswill continue to push beyond the bounds of what current software engineering theories,tools, and practices can support, including (but not limited to):
要使快速部署軟體具有信心，則需要軟體工程的根本性轉變。新的系統類型將繼續推動超越當前軟體工程理論、工具和實踐所能支持的界限，包括（但不限於）：
Systems that fuse data at a huge scale, whether for news, entertainment, or intelligence: We will need to continuously mine vast amounts of open-source data streams (e.g., YouTube videos and Twitter feeds) for important information that will in turn drive decision making. This vast stream of data will also drive new ways of constructing systems.
無論是新聞、娛樂還是情報的大規模融合數據系統：我們將需要不斷挖掘大量開源數據流（如YouTube視頻和Twitter feeds），以獲取重要信息，進而驅動決策。這種巨大的數據流還將驅動構建系統的新方法。
Smart cities, buildings, roads, cars, and transport: How will these highly connected systems work together seamlessly? How will we enable safe and affordable transportation and living?
智慧城市、建築、道路、汽車和交通：這些高度互聯的系統將如何無縫地協作？我們將如何實現安全的和價格實惠的交通和生活？
Personal digital assistants: How will these assistants learn, adapt, and engage in home and business workflows?
個人數字助理：這些助理將如何學習、適應和參與家庭和商業工作流程？
Dynamically integrated healthcare: Data from your personal device will be combined with hospital data. How do we meet stringent safety and privacy requirements? How do we evaluate assurance in a highly data-driven environment?
動態集成的醫療保健：來自個人設備的數據將與醫院數據相結合。我們如何滿足嚴格的安全和隱私要求？我們如何在一個高度數據驅動的環境中評估保證能力？
Mission-level adaptation for DoD systems: DoD systems will feature mission-level construction of new integrated systems that combine a range of capabilities, such as intel, weapons, and human/machine teaming. The DoD is already moving in this direction, but how can we increase confidence that there will be no unintended consequences?
國防部系統任務級別的適應能力：國防部系統將以任務級的新型集成系統建設為特色，該系統將結合一系列功能，如情報、武器和人/機團隊。國防部已經在朝著這一方向努力，但我們如何才能增強信心，確保不會出現意想不到的後果？
A Guiding Vision of the Futureof Software Engineering
軟體工程未來的指導性願景
Our guiding vision is one in whichthe current notion of software development is replaced by the concept of a softwarepipeline consisting of humans and software as trustworthy collaborators who rapidlyevolve systems based on user intent. To achieve this vision, we anticipate the needfor not only new development paradigms but also new architectural paradigms forengineering new kinds of systems.
我們的指導願景是，當前的部分軟體開發概念被軟體流水的概念所取代，軟體流水由人和軟體組成，是值得信賴的協作組合，根據用戶的意圖快速演變系統。為了實現這一願景，我們不僅需要新的開發範例，還需要新的架構範例，用於設計新型系統。
Advanced development paradigms,such as those listed below, lead to efficiency and trust at scale:
先進的開發範例可以大大提高效率和信任程度，如下面所列出的：
Humans leverage trusted AI as a workforce multiplier for all aspects of software creation.
在軟體創造的各個方面，人類都將可信的人工智慧作為加倍提升勞動力的利器。
Formal assurance arguments are evolved to assure and efficiently re-assure continuously evolving software.
正式的保證論點是為了確保並有效地再次確保不斷演變的軟體。
Advanced software composition mechanisms enable predictable construction of systems at increasingly large scale.
先進的軟體組合機制使系統的可預測結構能夠以越來越大的規模進行。
Advanced architectural paradigms,as outlined below, enable the predictable use of new computational models:
如下面所列出的，先進的體系結構範例允許可預測地使用新的計算模型：
Theories and techniques drawn from the behavioral sciences are used to design large-scale socio-technical systems, leading to predictable social outcomes.
來自行為科學的理論和技術被用來設計大規模的社會技術系統，導致可預測的社會結果。
New analysis and design methods facilitate the development of quantum-enabled systems.
新的分析和設計方法促進了量子支持系統的發展。
AI and non-AI components interactin predictable ways to achieve enhanced mission, societal, and business goals.
人工智慧和非人工智慧組件以可預測的方式交互，以實現使命、社會和業務目標。
Research Focus Areas
重點研究領域
The fundamental shifts and neededadvances in software engineering described above require new areas of research.In close collaboration with our advisory board and other leaders in the softwareengineering community, we have developed a research roadmap with six focus areas.Figure 1 shows those areas and outlines a suggested course of research topics toundertake. Short descriptions of each focus area and its challenges follow.
上面描述的軟體工程基本轉變和所需要的進步均需要新的研究領域。通過與顧問委員會和軟體工程社區的其他領導者的密切合作，我們已經制定了一個有六個重點領域的研究路線圖。圖1給出了這些領域，並概述了要進行的研究主題所對應的建議課程。下面是對每個重點領域及其挑戰的簡短描述。
Figure 1: Software EngineeringResearch Roadmap with Research Focus Areas and Research Objectives (10-15 Year Horizon)
圖1 包含研究熱點領域和研究目標的軟體工程研究路線圖（10-15年）
AI-Augmented Software Development. At almost every stage of the software development process, AI holds the promise of assisting humans. By relieving humans of tedious tasks, they will be better able to focus on tasks that require the creativity and innovation that only humans can provide. To reach this goal, we need to re-envision the entire software development process with increased AI and automation tool support for developers, and we need to ensure we take advantage of the data generated throughout the entire lifecycle. The focus of this research area is on what AI-augmented software development will look like at each stage of the development process and during continuous evolution, where it will be particularly useful in taking on routine tasks.
人工智慧增強軟體開發。幾乎在軟體開發過程的每個階段，人工智慧都有望幫助人類。通過將人類從繁瑣的任務中解脫出來，人們將能夠更好地專注於那些只有人類才勝任的需要創造力和創新的任務。為了達到這一目標，我們需要重新設想整個軟體開發過程，增加對開發人員的人工智慧和自動化工具支持，我們需要確保在整個生命周期中利用所生成的數據。這一研究領域的重點是，人工智慧增強軟體開發在開發過程的每個階段和持續演變過程中會是什麼樣子，在處理日常任務時它會特別有用。
Assuring Continuously Evolving Systems. When we consider the software-reliant systems of today, we see that they are not static (or even infrequently updated) engineering artifacts. Instead, they are fluid—meaning that they are expected to undergo continuing updates and improvements throughout their lifespan. The goal of this research area is therefore to develop a theory and practice of rapid and assured software evolution that enables efficient and bounded re-assurance of continuously evolving systems.
保證不斷演變的系統。當我們思考當今的依賴軟體系統時，我們看到它們不是靜態的（或者甚至是經常更新的）工程構件。相反，它們是動態的，這意味著它們將在整個生命周期中經歷不斷的更新和改進。因此，這一研究領域的目標是開發一種快速和有保證的軟體演變理論和實踐，使持續演變的系統能夠高效和有邊界的得到再次保證。
Software Construction through Compositional Correctness. As the scope and scale of software-reliant systems continues to grow and change continuously, the complexity of these systems makes it unrealistic for any one person or group to understand the entire system. It is therefore necessary to integrate (and continually re-integrate) software-reliant systems using technologies and platforms that support the composition of modular components, many of which are reused from existing elements that were not designed to be integrated or evolved together. The goal of this research area is to create methods and tools (such as domain specific modeling language and annotation-based dependency injection) that enable the specification and enforcement of composition rules that allow (1) the creation of required behaviors (both functionality and quality attributes) and (2) the assurance of these behaviors.
通過組合的正確性來構建軟體。隨著軟體依賴系統的範圍和規模持續增長和變化，這些系統的複雜性使得任何一個人或團隊都不可能理解整個系統。因此，有必要使用技術和平臺來集成（並不斷地重新集成）軟體依賴系統，這些技術和平臺需支持模塊化組件的組合，其中許多組件重用了現有元素，這些現有元素並沒有被設計為集成的或是整合在一起的。這一研究領域的目標是創建方法和工具（如特定領域建模語言和基於註解的依賴注入），使組合規則的說明和執行允許（1）創建必需的行為（包括功能和質量屬性）和（2）這些行為的保證。
Engineering Socio-Technical Systems. Societal-scale software systems, such as today’s commercial social media systems, are designed to keep users engaged to influence them. However, avoiding bias and ensuring the accuracy of information are not always goals or outcomes of these systems. Engineering societal-scale systems focuses on prediction of such outcomes (which we refer to as socially inspired quality attributes) that arise when we humans as integral components of the system. The goal is to leverage insights from the social sciences to build and evolve societal-scale software systems that consider qualities such as bias and influence.
設計社會技術系統。社會層面的軟體系統，例如今天的商業社交媒體系統，是為了讓用戶參與並影響他們而設計的。然而，避免偏見和確保信息的準確性並不總是這些系統的目標或結果。設計社會層面的系統的重點是預測這樣的結果（我們稱之為社會激勵的質量屬性），即當我們人類作為系統的組成部分時，這些結果就會出現。目標是利用來自社會科學的見解來構建和演變社會層面的軟體系統，這些軟體系統會考量諸如偏見和影響等特性。
Engineering AI-enabled Software Systems. AI-enabled systems, which are software-reliant systems that include AI and non-AI components, have some inherently different characteristics than those without AI. However, AI-enabled systems are, above all, a type of software system. These systems have many parallels with the development and sustainment of more conventional software-reliant systems. This research area focuses on exploring which existing software engineering practices can reliably support the development of AI systems, as well as identifying and augmenting software engineering techniques for the specification, design, architecture, analysis, deployment, and sustainment of systems with AI components.
設計支持人工智慧的軟體系統。支持人工智慧的系統是一種軟體依賴系統，包括人工智慧和非人工智慧組件，與沒有人工智慧的系統有一些內在的不同特徵。然而，支持人工智慧的系統首先是一種軟體系統。這些系統與更傳統的軟體依賴系統的開發和維護有許多相似之處。該研究領域的重點是探索哪些現有的軟體工程實踐可以可靠地支持人工智慧系統的開發，以及識別和增強軟體工程技術，從而支持人工智慧組件系統的規範、設計、架構、分析、部署和維護。
Engineering Quantum Computing Systems. Advances in software engineering for quantum are as important as the hardware advances. The goals of this research area are to first enable current quantum computers so they can be programmed more easily and reliably, and then enable increasing abstraction as larger, fully fault-tolerant quantum computing systems become available. Eventually, it should be possible fully integrate these types of systems into a unified classical and quantum software development lifecycle.
設計量子計算系統。量子軟體工程的發展與硬體的發展同樣重要。這一研究領域的目標是首先使目前的量子計算機能夠更容易和可靠地編程。其次當更大的、完全容錯的量子計算系統變得可用時，增加其抽象程度。最終，應該可以將這些類型的系統完全集成到一個統一的經典和量子軟體開發生命周期中。
Help Shape Our National SoftwareResearch Agenda
協助制定國家軟體研究議程
Along with the advisory board,our research team has examined future trends in the computing landscape and emergingtechnologies; conducted a series of expert interviews; and convened multiple workshopsfor broad engagement and diverse perspectives, including a workshop on SoftwareEngineering Grand Challenges and Future Visions co-hosted with the Defense Advanced Research Projects Agency(DARPA). This workshop brought together leaders in the softwareengineering research and development community to describe (1) important classesof future software-reliant systems and their associated software engineering challenges,and (2) research methods, tools, and practices that are needed to make those systemsfeasible. An upcoming SEI blog post will provide a synopsis of what was coveredin this workshop.
我們的研究團隊與顧問委員會一起研究了計算領域和新興技術的未來趨勢；進行了一系列專家訪談；為了多方廣泛參與和吸納不同觀點，召開了多個研討會，包括與美國國防高級研究計劃局（DARPA）共同主辦的關於軟體工程重大挑戰和未來願景的研討會。這一研討會聚集了軟體工程研究和開發社區的領導者來論述（1）未來軟體依賴系統的重要類別及其相關的軟體工程挑戰，以及（2）使這些系統可行所需的研究方法、工具和實踐。即將發布的SEI博客文章將提供本研討會所涉及的內容概要。
Your feedback would be appreciatedon the software engineering challenges and proposed research focus areas to helpinform the National Agenda for Software Engineering Study. Please email info@sei.cmu.eduto send your thoughts and comments on the software engineering study & researchroadmap or to volunteer as a potential reviewer of study drafts. Thank you.