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The Past, Present, and Future of Software Evolution

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The Past, Present, and Future of Software Evolution The Past, Present, and Future of Software Evolution Michael W. Godfrey Daniel M. German Software Architecture Group (SWAG) Software Engineering Group School of Computer Science Department of Computer Science University of Waterloo, CANADA University of Victoria, CANADA email: [email protected] email: [email protected] Abstract How does our system compare to that of our competitors? How easy would it be to port to MacOS? Are users still Change is an essential characteristic of software devel- angry about the spyware incident? As new features are de- opment, as software systems must respond to evolving re- vised and deployed, as new runtime platforms are envis- quirements, platforms, and other environmental pressures. aged, as new constraints on quality attributes are requested, In this paper, we discuss the concept of software evolu- so must software systems continually be adapted to their tion from several perspectives. We examine how it relates changing environment. to and differs from software maintenance. We discuss in- This paper explores the notion of software evolution. We sights about software evolution arising from Lehman’s laws start by comparing software evolution to the related idea of software evolution and the staged lifecycle model of Ben- of software maintenance and briefly explore the history of nett and Rajlich. We compare software evolution to other both terms. We discuss two well known research results of kinds of evolution, from science and social sciences, and we software evolution: Lehman’s laws of software evolution examine the forces that shape change. Finally, we discuss and the staged lifecycle model of Bennett and Rajlich. We the changing nature of software in general as it relates to also relate software evolution to biological evolution, and evolution, and we propose open challenges and future di- discuss their commonalities and differences. Finally, we rections for software evolution research. survey the evolving road ahead for research into software evolution; in particular, we find that the very nature of a software system has begun to change, and we discuss the 1. Introduction: The inevitability of change open questions and research challenges that lie ahead. As Lehman famously observed, software systems must 2. Evolution versus maintenance be able to evolve or they risk an early death [27]. Software systems, like economic theories and Galapagos´ finches, are Historically, both “software evolution” and “software embedded in an environment that is also continually chang- maintenance” date from the 1960s but neither term was ing [9, 17, 42]. For software, the environment has both tech- adopted into common use until years later.1 “Maintenance” nical and social characteristics: the deployed system oper- was first to achieve widespread acceptance, due in part to ates within a technical run-time infrastructure, while at the Canning’s well known paper of 1972, “That Maintenance same time users form opinions of the system based on their Iceberg” [4], and also to Swanson’s typology of mainte- direct and indirect experiences with it. nance activities introduced in 1976 [41]. We now discuss As in economics and biology, it is the interactions of the both terms in more detail. software system with its environment that determine its ul- timate success: Does the system provide enough function- 2.1. Software maintenance ality to do its intended job? Is it easy to use? Is the data secure? Can I use it on my cell phone? Is it open source? It is Swanson who is responsible for the categories of Is the price reasonable? In turn, the lessons of these in- maintenance kinds — corrective, adaptive, and perfective teractions comprise feedback into the development of sub- — that are still in common use today [41]. Swanson’s sequent versions of the system: Which new features were original descriptions of the categories differ somewhat from enthusiastically adopted? What absent features are users asking for? In what surprising ways was the product used? 1Chapin et al. have provided a detailed discussion of this topic [7]. most modern formulations,2 but a reasonably faithful updat- change support. Kitchenham et al. described an ontology ing of the terms might be given as: of software maintenance terms in the form of a UML model [22]; their particular goal was to identify factors that might Corrective maintenance are changes that fix bugs in the affect the results of empirical studies on software mainte- codebase. nance and evolution. Adaptive maintenance are changes that allow a system to run within a new technical infrastructure. 2.2. Software evolution Perfective maintenance are any other enhancements in- While the terms “evolution” and “maintenance” are often tended to make the system better, such as adding new used interchangeably with respect to software, there are im- features, boosting performance, or improving system portant semantic differences between them. As Parnas and documentation. others have pointed out, “maintenance” connotes the idea of keeping an existing system running without changing the According to this categorization, corrective and adaptive design; thus, for physical systems, maintenance often en- maintenance tasks do not alter the (intended) outward se- tails replacing worn out parts. However, software does not mantics of the system, while perfective maintenance in- wear out in the same sense; rather, the impetus for change cludes a wide variety of possible changes to the system. comes from dissatisfaction with the current system [27, 36]. Some later taxonomies (e.g., [15]) add a fourth category: Thus, the practice of software maintenance requires chang- Preventive maintenance are changes made to ease future ing the design of the system: by fixing bugs so that the de- maintenance and evolution of the system, such as re- sign is correct, by adapting the system for use in new en- organizing internal dependencies to improve cohesion vironments, by adding new features, or by improving the and coupling. internal design so that the system is easier to manage and change. It is innovation, not preservation, that drives soft- In this view, preventive maintenance tasks should leave the ware change: a new system, better adapted to its environ- external semantics of the system unchanged, as the main ment, evolves from the old one. goal is to improve the internal design of the system. In practice, however, preventive maintenance activities often 2.2.1. Evolution as a perspective on change lead to improved design ideas that, in turn, result in outward changes. Since software maintenance is by nature a design activ- This last category is somewhat controversial; some con- ity, it tends to be more intellectually demanding and thus sider the term to be ill-defined, and others note that it can also riskier than the maintenance of physical systems. Con- be seen as fitting within the domain of perfective mainte- sequently, many have started to use the term “software evo- nance [6]. For example, the 1990 IEEE Standard on Soft- lution” as an alternative to describe the various phenomena ware Engineering Terminology defines preventive mainte- associated with modifying existing software systems. nance as “maintenance performed for the purpose of pre- This term has several advantages: First, evolution sub- venting problems before they occur”3 [15], while the sub- sumes the idea of essential change that maintenance sim- sequent 1998 IEEE Standard on Software Maintenance Ter- ply does not connote. Maintenance suggests preservation minology omits the term from the main body of definitions, and fixing, whereas evolution suggests new designs evolv- referring to it only in the appendix [16]. ing from old ones. Swanson’s taxonomy is based on the intent of the devel- Second, maintenance is usually considered to be a set of oper toward the system rather than the nature of the changes planned activities; one performs maintenance on a system. themselves; others have presented alternative taxonomies of Evolution, on the other hand, concerns whatever happens software change. Chapin et al. described an expanded clas- to a system over time; in addition to the planned activities, sification scheme of 12 categories based on how artifacts unplanned phenomena often manifest themselves also. For and activities were observed to have changed [7]. Mens example, no one ever plans for interfaces to become bloated, et al. proposed a taxonomy of software evolution based on for architectural drift to set in, or for fundamentally new the characterizing mechanisms of change and the factors uses of the system to emerge over time, but these are all that influence these mechanisms [33]. Their classification evolutionary phenomena. scheme is organized into the several logical groupings: tem- Finally, it can be argued that maintenance and evolution poral properties, objects of change, system properties, and offer different perspectives on the nature of change. Re- search on software maintenance can be seen as addressing 2Swanson also subsequently revised his own definitions [29, 28]. 3One wonders if the IEEE considers clairvoyance to be a job require- practical, engineering goals: What should we do next? How ment for software maintainers. risky is it? How should we validate our work? Research on software evolution, on the other hand, can be seen as asking 8. Feedback system — Successfully evolving a software questions of a broader, more scientific nature: How fast can system requires recognition that the development pro- a system grow before it becomes resistant to change?
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